",isbn:"978-1-83969-108-9",printIsbn:"978-1-83969-107-2",pdfIsbn:"978-1-83969-109-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"de4ec5bb46fa24bd45d7cc410bd95779",bookSignature:"Dr. Ghedira Kais and Dr. Yosr Hamdi",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10661.jpg",keywords:"Bioinformatics, Computational Approaches, Databases, Portals, Cancer Registries, E-Health Records, Novel Treatment, Drug Repurposing, Mutations, Biomarkers, Whole Exome Sequencing, Whole Genome Sequencing",numberOfDownloads:460,numberOfWosCitations:0,numberOfCrossrefCitations:1,numberOfDimensionsCitations:1,numberOfTotalCitations:2,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 14th 2021",dateEndSecondStepPublish:"July 26th 2021",dateEndThirdStepPublish:"September 24th 2021",dateEndFourthStepPublish:"December 13th 2021",dateEndFifthStepPublish:"February 11th 2022",remainingDaysToSecondStep:"10 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Kais Ghedira is an assistant professor at the Institute Pasteur of Tunis (IPT) holding a Ph.D. degree in bioinformatics. He has been involved in several international and national projects funded by European Commission, IPT, and NIH and is mainly devoted to bioinformatics education and training in Africa.",coeditorOneBiosketch:"Dr. Yosr Hamdi obtained her Ph.D. in Molecular Medicine at Laval University, Quebec, Canada. By combining genomics, molecular biology, and bioinformatics, she is implementing Precision Oncology in Africa.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"229844",title:"Dr.",name:"Ghedira",middleName:null,surname:"Kais",slug:"ghedira-kais",fullName:"Ghedira Kais",profilePictureURL:"https://mts.intechopen.com/storage/users/229844/images/system/229844.jpg",biography:"Dr. Kais Ghedira is an assistant professor in Institut Pasteur of Tunis (IPT) holding a PhD degree in bioinformatics. He has been involved in several international and national projects funded by European Commission, IPT, and NIH and is mainly involved in bioinformatics education and training in Africa. Dr. Ghedira is a bioinformatician with biological background. He is mainly interested in functional genomics and integrative biology, analysis of NGS high-throughput data (genome assembly, metagenomics), comparative genomics, gene expression (microarrays) and gene regulation analysis, and database and web tools development.",institutionString:"Institut Pasteur de Tunis",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Institut Pasteur de Tunis",institutionURL:null,country:{name:"Tunisia"}}}],coeditorOne:{id:"344524",title:"Dr.",name:"Yosr",middleName:null,surname:"Hamdi",slug:"yosr-hamdi",fullName:"Yosr Hamdi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000033oAvSQAU/Profile_Picture_1608285761815",biography:"Dr. Hamdi holds a PhD in Molecular Medicine from Laval University, Quebec, she is currently an Assistant Biologist at the Laboratory of Biomedical Genomics and Oncogenetics in Institute Pasteur de Tunis, Tunisia. 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1. Introduction
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Disaster management planning is structured around the disaster management cycle model. The cycle consists of four stages – reduction, readiness, response and recovery. Remotely sensed data can provide a valuable source of information at each of these stages, helping to understand spatial phenomena, and providing scientists and authorities with objective data sources for decision making. The challenge with disaster management is that the inherent unpredictability and range of hazards does not allow for a single all-encompassing solution to be developed and explored. Instead, there are a multitude of different remote sensing platforms and sensors that can and should be employed for image acquisition. An extensive coverage of each, including optimal processing regimes for their data would be prohibitively long; instead this chapter aims to give some general examples of the use of remote sensing in disaster management, while directing the reader to more specific studies in the literature. The types of data required and information provision needs for each stage will be discussed including optical, thermal, and synthetic aperture radar as data sources over a variety of spatial and temporal scales.
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Remote sensing can be used to assist risk reduction initiatives through identification of hazard zones associated with flood plains, coastal inundation and erosion, and active faults. It can also be used to verify hazard models by measuring the location and magnitude of actual events. Imagery is widely used by meteorologists for providing weather forecasting and warnings of potentially severe weather events, providing the public and emergency responders with information that can assist decision making around short term readiness. These images are commonly presented in print, television and on the internet, and they are well accepted by viewers around the world. Imagery of fires, volcanic eruptions and flooding are often used during the response phase for the visual impact that they provide. If people in potentially at-risk locations personalise the risk, they are more likely to take readiness actions such as making emergency plans for contact and evacuation or assembling emergency kits. Remote sensing images of similar communities experiencing hazards, or the progress of a hazard such as a fire front, can assist with this personalisation process. For agencies that respond to emergencies, remote sensing imagery provides a rapid method of assessing the magnitude of hazard impacts, areas most affected, and where key transport and other infrastructure links have been disrupted or destroyed. Remote sensing can also be used to provide an indication of the rate of recovery in an area post disaster based on indicators such as vegetation regrowth, debris removal, and reconstruction.
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There are few examples where remote sensing is incorporated seamlessly into all stages of the disaster management cycle for planning purposes. This requires a collaborative effort from emergency managers, policy planners and remote sensing technical staff that may not always be co-located, or even working for the same organisation. However, data is becoming more readily available, and some satellites and constellations are even targeting at least partially the disaster management / emergency response community in recognition of the value remotely sensed imagery can provide. If this current trend continues, integrating remote sensing and emergency management will become increasingly more commonplace.
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2. The disaster management cycle
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The traditional approach to hazard risk and disaster management has been one primarily focussed on response to events as they occur (Gregg & Houghton 2006), managing residual risk through warning systems and emergency management plans, and more recently attempting to reduce risk through changing the hazard process or impacts (Board on Natural Disasters 1999). Examples of attempts at hazard modification include: the use of stopbanks and levees to provide opportunities to build in areas vulnerable to flood hazard; building codes for strengthened buildings to allow development in earthquake prone locations; and building seawalls along coasts to reduce susceptibility to erosion and coastal inundation. These measures have allowed greater development in hazardous areas, and are typically designed for protection up to a certain magnitude of event, but there always exists the potential for design limits to be exceeded (Burby 1998). Because of reliance on technological solutions, risk is increasing in the developed world as infill and migration increases in “protected” areas (Mileti 1999). In less-developed nations, risk is also increasing, although the drivers differ. Reliance on decreasing natural resources, population increase, poverty, and political drivers push communities into hazardous areas traditionally left un-settled (Donner & Rodriguez 2008). The body of research into the evolution of hazards and disaster management now recognises that it is primarily social drivers that create vulnerability to hazards, and consequently increase the potential for disasters (Board on Natural Disasters 1999, Cutter & Finch 2008, Donner & Rodriguez 2008, Pertrow et al. 2006, Wisner et al. 2004). The overall focus of emergency management has shifted to consider disaster management planning as part of a broader system of planning for sustainable, resilient communities. Whether a hazardous event will become a disaster - an event that is beyond the capacity of responding agencies, resources, and community coping capacity (Quarantelli 1985), can be influenced by effective disaster management planning.
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This recognition of the importance of social drivers has brought about a change in how disaster planning is considered and undertaken. Many nations now plan using a variation of the Disaster Management Cycle, an integrated, four–phase planning system. Although the cycle can be considered as a continuum, traditionally the first phase of the cycle is considered to be reduction, followed by readiness, response, and recovery (Figure 1).
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Figure 1.
The disaster management cycle
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Reduction incorporates all measures and planning that reduce the likelihood of a disaster occurring. This is done through the process of risk identification and reduction; either by modifying the hazard process using traditional structural methods such as stopbanks or seawalls, or by modifying behaviours and the assets at risk (Gregg & Houghton 2006). Behaviour modification includes land use planning to: prevent development in hazardous areas; incorporate good access for response and evacuation; and foster interconnected and resilient communities (Burby 1998). In theory, land use planning can reduce all risk from disasters, but centuries of settlement in hazardous locations make this option unrealistic and impractical. Modifying assets at risk includes such methods as strengthening buildings and infrastructure and raising floor heights to reduce hazard impacts.
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Readiness planning accepts that some residual risk is present for communities and that measures must be in place to ensure any response to hazards is efficient and reduces hazard impacts. Readiness planning includes: public education on hazards and their consequences, and how these consequences can be reduced; training of emergency planners and responders; installing monitoring and warning systems for hazards; exercising response plans; and fostering community resilience through increased uptake in home preparedness such as learning first aid, having an emergency kit and an evacuation plan (Ronan & Johnston 2005).
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The phase of disaster management that has traditionally received the most recognition, funding and planning effort is Response (Gregg & Houghton 2006). This fact is also reflected in the remote sensing community, with an overwhelming number of research papers dedicated to the use of imagery for disaster response, despite the fact that data often cannot be provided in the timeframe required to be of use for decision makers. The reality is that most nations do not have the capability to prevent disasters occurring; the best option for reducing the chance of a disaster is through reducing risk. However, response capability is important in any disaster as it involves the processes of coordinated effort to manage resources, including life essentials and personnel, for activities such as evacuation, relief, search and rescue and needs assessment (Quarantelli 1997).
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Recovery, the fourth phase of the cycle has traditionally been focussed on restoration of lifeline utilities, and building reconstruction. There is now considerable research into holistic recovery processes, which recognise that for community recovery to be sustainable, the social, economic, built and natural environments must be considered (Norman 2004). The four environments are interlinked as communities rely on:
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Natural environment for amenity (recreation, psychological wellbeing), and resources (to provide opportunities for construction and employment);
Built environment for lifeline utilities and structures to enable people to live, work and recreate;
Economic environment to provide goods, services and livelihoods; and
Social environment, to provide opportunities for political participation, community building, networking and psychological wellbeing.
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The recovery phase of a disaster can be considered to have several steps, the initial restoration of lifeline essentials, and the longer term rebuilding of communities. The recovery phase is often considered to be an optimal time to include measures that will reduce the risk of future disasters (Becker et al. 2008).
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The four phases of the disaster management cycle are not discreet; they are interrelated and ideally integrated throughout the planning process. Decisions about risk reduction methods will affect the degree of readiness planning and response that will be required. Readiness levels of affected communities and responders can determine whether an event becomes a disaster, as can be seen in the failure to provide evacuation options for the 20% of the New Orleans population with no vehicle or resources to leave the city prior to hurricane Katrina’s landfall (Laska & Morrow 2006/7). The effectiveness of the response phase will play a significant role in how affected communities recover, both physically and psychologically. Lessons from the response phase can be incorporated into risk reduction and readiness planning. Finally, the recovery phase can include risk reduction measures to increase resilience and reduce future vulnerability.
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3. Remotely sensed data types
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In order to successfully use remote sensing for disaster management, physical indicators of features or attributes within the disaster management cycle that are measureable in imagery need to be identified. At that point, selection of the most appropriate remotely sensed data set is possible by identifying the spatial, spectral, temporal, and radiometric requirements. The use of a framework for selecting appropriate remotely sensed data has been demonstrated for mapping and monitoring coastal and tropical wetlands, tropical rainforests, coastal ecosystems and coral reefs (Phinn 1998, Phinn et al. 2006). This is an approach that can be modified and applied under many different circumstances and for various environments. Here we look to apply aspects of the framework to disaster management. During the reduction, readiness and recovery phases, there may be sufficient time to develop and apply the framework as the cycle is progressing. However, as timeliness is a critical factor in the response phase, it is of most use to already have systems in place to aid with appropriate data selection so that crucial decisions need not be made under the severe time constraints that are necessitated by rapid response. Preparation may therefore involve developing a range of scenarios representing potential situations that require rapid response at a set location, and applying the principles of data selection and processing in advance. In this way, the decisions regarding remote sensing in the response phase can actually be made during the readiness phase instead. This should be done as a collaborative exercise between both remote sensing experts and emergency management agencies.
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The types of satellite and airborne sensors that can be used to support phases of the disaster management cycle are many and varied. It is most important to consider the spatial scale of the hazard, in addition to determining the most appropriate data type to address the problem. For example, geostationary satellites provide data over a large area, but with minimal spatial detail, and are appropriate for monitoring weather patterns (readiness) and volcanic ash and gas distribution (response). Conversely, very high spatial resolution data (e.g. aerial photography, Quickbird, Ikonos, Worldview) are appropriate for targeting relatively small areas where they can provide a great deal of detail. Examples of their use include baseline infrastructure mapping for scenario development and model validation (reduction and readiness), building damage (response), and observations of debris removal and reconstruction (recovery).
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In the disaster reduction phase, the focus for remote sensing is often on mapping landscape features such as land cover / land use, and the location of potentially hazardous features or processes to avoid when developing infrastructure (e.g. active faults, flood plains). During the readiness phase, the emphasis is on monitoring these features or processes, developing models for forecasting purposes, and using maps and model for training and education. In the response phase, the timely acquisition of data and provision of information to emergency services is critical. Much of the attention will be placed on identifying infrastructure that has been damaged or is likely to be at risk in the near future (e.g. housing in the path of a bush fire). Finally during the recovery phase, the focus will shift to long term monitoring of debris removal, vegetation regeneration, and reconstruction.
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3.1. Optical
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There are a large number of applications for which optical remotely sensed imagery can be used to aid the disaster management cycle. Optical data can be of particular use to the disaster management community as it is generally simple to understand and interpret raw data, particularly when collected using standard true colour spectral bands (blue, green, and red). The characteristics of the sensor are important in selecting the most appropriate data type for use in individual situations. Consideration should be primarily given to the spatial and temporal resolution of the sensor. These factors will differ depending on the disaster management activity. For example, during the response phase, rapid acquisition of data following the event is crucial. During the recovery phase, the speed of acquisition is less important than repetition on a consistent basis. In the early stages of recovery, imagery may be useful on a monthly basis, though as time passes, an annual acquisition may suffice.
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Optical data can be used for activities in all stages of the disaster management cycle, however the greatest potential contributions are for monitoring recovery, and helping to plan for reduction and readiness. The use of satellite optical data for immediate response at a local scale is currently hindered by the speed of data acquisition and delivery with polar orbiting satellites. For large events, a more regional synoptic view is possible using geostationary satellites; however the amount of detail able to be extracted from these images is reduced.
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The greatest limitation of optical sensors under many hazard or disaster scenarios is the inability to obtain imagery through clouds, smoke or haze. Events such as wildfires, volcanic eruptions, and tropical cyclones or other severe storms are characterised by cloud and smoke, which can effectively obscure damage on the ground both during and immediately subsequent to an event.
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3.2. Thermal
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As energy decreases with increasing wavelength, thermal wavelengths have comparatively low energy levels and consequently thermal image data have a lower spatial resolution than that capable of being achieved with optical imagery. As yet there are no very high spatial resolution thermal satellite sensors commercially available. Nonetheless, thermal imagery provides a valuable source of information about volcanic eruptions and the location of wildfires. Robust techniques for automatic extraction of anomalous high temperatures or ‘hotspots’ have been thoroughly tested and considered operational on a global scale using MODIS, AVHRR or GOES imagery (Wright et al. 2002, Wright et al. 2004). The University of Hawai’i and Geoscience Australia both apply automated hotspot detection algorithms for the detection of volcanic activity and bushfires respectively and serve the information in near real time via the internet. These algorithms have primarily been developed to detect features above the background or average temperature values, and to avoid large numbers of false alarms, they are not sensitive to merely warm features. They are also unable to differentiate between the types of heat source, so addition spatial information or manual interpretation may be required.
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Higher spatial resolution thermal imagery for analysis at local scales can be obtained using ASTER or Landsat TM/ETM+, though neither of these sensors have the ability to provide imagery of rapidly changing thermal features, as their orbits only allow them an overpass frequency of approximately 16 days. Nevertheless, both sensors are useful for tracking longer term temperature fluctuations, such as the warming and cooling cycles of volcanic lakes (Joyce et al. 2008b, Oppenheimer 1993, Oppenheimer 1997, Trunk & Bernard 2008). The higher resolution imagery can also be of use in calibrating and validating data obtained from the likes of MODIS.
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As the temperature of an object increases, the wavelength of peak radiation decreases. Very hot features can therefore be seen in visible or shortwave infra red (SWIR) imagery and often become saturated in thermal infra red data if they are sufficiently large with respect to the pixel size. This relationship has been demonstrated using forest fire size and the temperature difference between a smouldering and flaming fire that could be of use in understanding different stages of fire development (Giglio et al. 2008). Unfortunately the SWIR bands on ASTER were declared non-functional in January 2009 after experiencing technical difficulties since May 2007. These five SWIR bands fall within a similar spectral range as Landsat TM/ETM+ band 7 that could be used as an alternative.
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3.3. Synthetic Aperture Radar
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Synthetic Aperture Radar (SAR) is an active microwave sensor that is capable of acquiring data in harsh weather and lighting conditions not suitable for optical sensors, such as dense cloud or smoke coverage (Elachi 1987, Franceschetti & Lanari 1999, Hanssen 2001). Most modern SAR sensors are designed to acquire data of various ground resolution elements ranging from 100s of metres to 1-3 metres, but higher spatial resolution images usually have significantly smaller spatial coverage and are limited by satellite storage and processing capacities. The incidence angle of SAR sensors can be manipulated in order to image different areas without changing the satellite orbit, thus decreasing necessary revisit time.
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Both backscatter intensity and the phase of SAR images can be utilised. In most studies only the relative variability of backscatter intensity within the image is used but absolute values can be required for some multi-temporal studies. The precise interpretation of backscatter intensity can be complicated because of its dependence on the dielectric properties of the reflecting material, surface roughness, and sensor wavelength but at the same time the variety of useful information still can be easily observed (landslides, tsunami, flooding, and damage to infrastructure). Phase information of a single SAR image has no value but comparison of phases from two SAR images acquired at distinct times are utilised in SAR interferometry or InSAR. InSAR is capable of producing high resolution ground deformation maps with sub-centimetre accuracy (Rosen et al. 2000). These maps can then be used for studying the causes of deformation such as earthquakes or volcanic activity (Massonnet & Feigl 1998). Modern satellite SAR systems are capable of acquiring simultaneous data with more than one polarisation (e.g. Radarsat-2, ALOS PALSAR and TerraSAR-X). This information can be used in various studies utilising SAR polarimetry and POLInSAR techniques, such as land classification, detection of areas affected by fire or flooding (Cloude & Papathanassiou 1988, Pottier & Ferro-Famil 2008, van Zyl et al. 1990).
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At present, commonly used satellite SAR data is acquired in three wavebands: X (3.1 cm); C (5.6 cm); and L (23.6 cm). Waveband selection depends on the type of application, land-cover, time span, and availability. The analysis of backscatter intensity by determining thresholds associated with certain features can be performed in standard GIS or image processing software, such as ArcGIS or ERDAS Imagine, but InSAR, SAR polarimetry and POLInSAR processing require specialised software (or add-on modules to basic packages) and extensive processing experience. The price of the data greatly varies from a few dollars per image for purely scientific applications to a few thousand of dollars for commercial applications. Several recently launched commercial satellites are available to acquire data of any hazardous event with a very short delay and deliver the data rapidly to the user, though the cost of priority commissioned data is significantly greater than that of archived imagery (RADARSAT-2, TerraSAR-X and Cosmo-Skymed).
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4. Remote sensing applications
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4.1. Reduction
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Disasters are social constructs in that social drivers such as migration (forced and voluntary), conflict, modification of natural buffer systems, reliance on shrinking resources, private property rights, urban intensification, artificial protection structures, and economic and political vulnerability are all contributors to people living in hazardous locations or at levels of vulnerability that make a disaster more likely. Remote sensing technology can assist with addressing some of these “disaster drivers”, through providing the data required to assist land use planners, emergency managers, and others tasked with disaster management. Reduction of risk, and therefore reduction in the probability of a disaster occurring, is an important part of the disaster management cycle. Remote sensing can be applied in disaster reduction initiatives through identification and understanding of hazards (Table 1). This knowledge is then applied to mitigation activities such as land use planning, engineering structures, building codes and hazard consequences modelling to determine methods for reducing vulnerability (Gregg & Houghton 2006). Note that the sensor examples given in Table 1 and subsequent tables are indicative of current or potential instrument use. Many alternative sensors with similar characteristics could also be used.
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Understanding of hazards, their magnitude, frequency, duration, location, range and manifestation (e.g. heavy rainfall, tephra, strong winds) has long been accepted as essential to disaster management. Although it is primarily social factors that amplify a hazard event into a disaster (Quarantelli 1985, Wisner 2004), improved knowledge of hazards and their potential consequences is essential for decision making about modifying hazard characteristics, or modifying vulnerability of people and assets. Remote sensing can be used directly for hazard identification (e.g. flood plain modelling, slope stability and landslide susceptibility), but can also be used to derive hazard-independent information that can be used for disaster reduction (e.g. baseline building, infrastructure, and topographic mapping). An excellent example of the use of remote sensing for hazard identification is provided with LiDAR mapping of active fault location (Begg & Mouslpoulou 2009 in press). Traditionally fault location is conducted using stereo aerial photography interpretation followed by intensive field survey. However the horizontal and vertical resolution provided by airborne LiDAR imagery provides the capability for identifying fault traces and extracting elevation offsets with digital data in an objective manner. The identification of many previously unknown faults in northern New Zealand is shown in Figure 2.
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Type of information
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Data required
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Sensor example
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Application example
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Location of fault traces and rupture zones
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High resolution DEM
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Airborne LiDAR, SAR
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Use for land use planning around active faults to reduce risk from future development in fault hazard locations
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Fault displacement
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Interferometric SAR
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1/2, ENVISAT ASAR, ALOS PALSAR
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Knowledge of fault displacement rates are used in numerical models in order to forecast the magnitude of possible earthquakes
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Flood plain mapping
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DEM
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Airborne LiDAR, 1/2, ENVISAT ASAR, ALOS PALSAR
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Identification of flood plains can help inform changes in land use, and identify areas developing protective measures (e.g. stopbanks)
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Land cover / land use
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Optical and polarimetric SAR
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SPOT, ASTER RADARSAT-2
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Used for catchment management planning to reduce flood and landslide risk
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Vegetation change
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Consistent time series of data
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SPOT, ASTER RADARSAT-2
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Determine drought zones, inform fire hazard mapping
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Determining lahar and lava flow paths
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DEM, high resolution optical imagery
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SAR, Airborne LiDAR, , AVNIR-2, ASTER
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Hazard zonation, public awareness, determining location of safety shelters
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Locating potential and actual unstable slopes
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DEM, Interferometric SAR, high resolution stereo optical imagery
Assist with hazard mapping to identify key infrastructure at risk - the risk can then be addressed through mitigation or built in redundancy. Can also be used for later damage assessment post-disaster
Examples of information and data requirements during the reduction phase
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Figure 2.
Identification of known and new active faults using high resolution airborne LiDAR data acquired in late 2006 (Begg & Mouslpoulou 2009 in press). Landsat ETM+ false colour composite (5,4,2) acquired in 2001 is inset for a contextual overview of the site. Of the active fault traces shown here, approximately 85% were unknown before undertaking this study. Also of note also is the discovery of a large inland area that is below sea level (elevation <0m) and is a potentially hazardous region for tsunami related inundation
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Remotely sensed data acquisitions can be used to inform land use planning, a key tool that authorities and communities employ to avoid or mitigate hazard risk (Burby 1998). By identifying the location and characteristics of hazards, land use planning methods can be applied to address the risk these hazards pose. Planning methods include mapping hazard zones (location and range of hazard impact) and identifying the probability of occurrence. Hazard maps are applied to developed and green field (undeveloped) land and options for risk treatment determined. Treatment options can include measures such as setback zones (no development within the hazard zone, e.g. proximal to active faults or within coastal erosion or inundation zones), or special building codes (e.g. minimum floor heights above base flood level) can be introduced to reduce the risk to assets and people (Godschalk et al. 1998). Understanding of hazard information is one of a number of critical factors influencing individual and group decision making for risk management (Paton & Johnston 2001). Where hazard information is readily available to the public in a variety of forms, including maps, there is a greater likelihood of public support for risk reduction initiatives introduced through land use planning (Burby 2001).
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Other methods for land use planning based on remote sensing data include identifying changes in land use on flood plains to assist with flood hazard modelling. In the city of London, Canada, Landsat images taken over a 25 year period have been used to determine the spread of urban development (Nirupama & Simonovic 2007). The consequent increase in impermeable surface cover facilitated more rapid runoff and less natural absorption of rainfall. When compared with flood hydrographs, the rate of land use change correlates with smaller rainfall events producing flooding. The benefits to future land use planning are that it can be determined how land use changes affect the flood hazard risk, and this will guide future development in a way that mitigates the effects of continued urban sprawl.
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Collecting asset data via high resolution remote sensing allows for identification of infrastructure and buildings in hazardous locations, which can then be targeted for strengthening or re-location. Asset data is also essential for hazard consequence modelling, whereby hazard data is combined with asset data and fragility (vulnerability) information to determine potential losses. Building fragility to hazards is based on such factors as construction materials (earthquake, volcanic ash fall, tsunami), engineering design (tsunami, landslide, earthquake), building height (wind), floor areas (earthquake), proximity of other structures and vegetation (fire) and roof pitch angle (ash fall, snow), and floor height (flood, tsunami). Remote sensing methods for collecting building and infrastructure data require high to very high resolution satellite or airborne imagery and is often completed using manual digitizing or more recently, segmentation and object oriented classification. Optical imagery is often complemented by LiDAR data, which can not only aid in detecting building edges, but is also used for calculating building heights. Incorporation of remotely sensed data into a GIS is vital during this phase for recording spatial attributes and combining with other data sets.
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Remote sensing technology can also be applied to measure the success of risk reduction initiatives. A common method for addressing flood risk is the construction of stopbanks to contain flood waters for an event of a given magnitude. Aerial reconnaissance during major flooding events can identify whether stopbanks are performing to design standard and identify areas of weakness, overtopping or failure. Monitoring of non-structural risk reduction initiates is also possible. To address coastal hazard erosion and inundation risk, many communities choose non-structural options such as beach renourishment and dune restoration. In Florida, airborne LiDAR captured over time has been applied to measure coastal erosion from hazards, alongside the success of non-structural beach restoration methods through determining changes to beach morphology (Shrestha et al. 2005). Another example of measuring the effects of risk reduction initiatives is analysing post-disaster images of rainfall induced landslides on land under different vegetation covers for large events. From analysis of aerial photographs (oblique and vertical) of an event in 2004 which impacted the lower North Island of New Zealand, it was determined that vegetation cover played an important role in reducing loss of productive soil, and reducing landslide hazard to assets (Hancox & Wright 2005).
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4.2. Readiness
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Readiness planning and activities are undertaken in the realisation that residual risk from hazards has the potential to create emergencies, and in some cases, disasters for affected populations. Readiness is the identification and development of necessary systems, skills and resources before hazard events occur. The desired outcome of readiness planning and activities is that response to hazards is more coordinated and efficient, communities experience less trauma, and recovery times are reduced (Quarantelli 1997). Examples of readiness activities include public education, preparedness activities, trainng and exercising, evacuation planning, developing hazard monitoring and public alerting systems, and putting in place state, national and international plans and agreements for assistance and aid. Readiness activities and planning are undertaken at a number of levels to increase resilience and response capability for individuals, households, organisations, and states or nations. The provision of good hazard and asset information to assist these activities is essential and examples where remote sensing can assist this phase are given in Table 2. It is important in this phase to prepare an archive of and gain familiarity with the most up to date spatial information including (but not limited to) imagery, DEMs, and vector data. This information is required to assist with damage assessment during the response and recovery phases.
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At the individual and household level there are identified factors that contribute to whether people will take actions to prepare for disasters. Personalisation of risk is essential (Barnes 2002, Slovic et al. 2000), e.g. “Will it affect me?”, “Do I need to do something about it”, and “What can I do about it?”. Other factors include belief in the benefits of hazard mitigation (outcome expectancy) and their belief that what they personally can do will make a difference (reduce negative outcome expectancy) (Paton 2006). At a community level, participation in community affairs and projects, and individual’s ability to influence what happens in their community (empowerment) and the level of trust they have in different organisations (trust) have also be shown to be key predicators of resilience. Therefore, communication of risk in a meaningful way is an essential part of preparedness planning. Remotely sensed data such as LiDAR are used to produce high resolution hazard and risk maps, which are used by authorities to communicate information about location and range of hazards to their communities. If individuals believe that a hazard is likely to affect them detrimentally within an understandable and pertinent timeframe, they are more likely to take actions to prepare. These actions might include having emergency supplies in the home, an action plan for evacuation and emergency contact with other household members, first aid training or training as a civil defence volunteer. The principle of risk perception aiding preparedness applies to both static and dynamic hazards, e.g. fault trace or flood plain mapping vs. cyclone or bushfire progression. Remotely sensed images showing the progression of a bushfire front or the track of a cyclone are commonly used by the media to inform the public of where hazards are occurring and where they are likely to impact as they evolve. As community resilience research has shown, awareness of hazards is not the only factor in triggering actual preparedness actions; however it is one significant driver (Paton 2006, Paton & Johnston 2001, Ronan & Johnston 2005).
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Type of information
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Data required
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Sensor example
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Application example
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Severe weather warnings
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RADAR, broadscale visible and infra red imagery
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GOES, NOAA, Meteosat
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Provide valuable advanced warning of severe events to the public and emergency planners via meteorologists
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Movement and ground deformation
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InSAR and PS-InSAR
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-1/2, ENVISAT ASAR, ALOS PALSAR
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Rate of movement for slow moving landslides. Often acceleration of deformation rates means that a large event is about to follow. Early detection of deformation in volcanic regions is used for forecasting of possible eruptions
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Soil moisture
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Long wavelength SAR
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SMAP
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Water shortage leading to drought and agricultural productivity decline, ability of soils to retain water to indicate flood and landslide potential
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Ground temperature variability
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Thermal imagery, or SWIR in the case of very hot features
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ASTER, MODIS, AVHRR
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Monitoring heating and cooling cycles of volcanoes to understand pre-eruptive characteristics for forecasting purposes
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Coastal and bathymetric mapping
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SONAR, Laser depth ranging
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LADS, Topex Poseidon / Jason
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Tsunami hazard modelling
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Display and advertisement of potential hazards
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Moderate to high resolution optical imagery, often overlaying a DEM
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Aerial photography, Quickbird, Ikonos - usually using black and white or true colour composites for ease of understanding
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For use in public education about hazards and risks to foster greater readiness of individuals, households and organisations Use in civil defence emergency management exercises to provide realistic scenarios that will assist with staff professional development and planning
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Detecting sea temperature or atmospheric pressure change in cyclone/hurricane/ typhoon generating latitudes
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Broad scale thermal imagery, geostationary
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MODIS, GOES, AVHRR
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Advance warning of severe weather approaching to commence
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Table 2.
Examples of information and data requirements during the readiness phase
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At the institutional level, a strong focus is placed on the development of plans and relationships. A primary way to test the effectiveness of these preparedness plans and relationship functions is through civil defence emergency management exercises. In order for exercises to provide an effective learning experience for participants, realistic hazard scenarios must be developed. Remotely sensed data can assist this process through the creation of hazard maps, providing realism to exercise injects (new information about hazards or consequences as the exercise plays out).
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At local to national scales, obtaining an overall picture of the hazardscape; identifying at risk areas, and priority hazards for resources and planning is essential. Granger (2000) discusses the development of information infrastructure for disaster management in Pacific island nations, based on remotely sensed data, and GIS interpretation. For countries with limited budgets, collaboration to purchase remotely sensed data for disaster planning is beneficial because of cost savings, the opportunities for skill and process sharing, and the consistency of data for modelling (Granger 2000).
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As discussed previously, hazard modelling is important for risk reduction (section 4.1); it is also important for readiness, as for many hazards residual risk dictates that an effective emergency response will be the most practical solution for disaster management. For example, New Zealand has several active volcanoes; Mt Ruapehu is the largest of these. Ruapehu is a national park and has two commercial ski fields in operation on its slopes. Depending on the time of year, visitors to the mountain are engaged in a variety of recreational, educational and scientific activities. The greatest hazards associated with the volcano are eruptive events and lahar flow (Carrivick et al. 2009). The volcano has a crater lake at the summit which produces periodic large lahars during eruptions and tephra dam bursts. These lahars follow channels which are bridged by the main trunk railway line and State Highway 1, as well as passing through ski field and hiking areas. A lahar event in 1953, before bridges were raised and strengthened, destroyed the Tangiwai rail bridge, and a passenger train unable to stop was derailed resulting in the death of 151 people. While bridges have been modified to reduce risk, considerable readiness planning has also been undertaken to ensure that the events such as the 1953 disaster cannot happen again (Galley et al. 2004).
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Following eruptions in 1995 and 1996 a large tephra dam formed on the crater rim allowing the lake to fill to higher than normal levels. The volcanic rocks of Crater Lake rim now had a weakness, a section of the rim comprised of weaker tephra, which would fail when lake levels reached a certain height. Extensive modelling of potential lahar flow paths and velocities was undertaken based on high resolution remotely sensed data (Carrivick et al. 2009). The path was verified using aerial photography, LiDAR, ASTER and PALSAR imagery after the event (Joyce et al. 2009b). The modelling provided the necessary hazard information for authorities to manage the risk through a suite of preparedness activities. A bund (levee) has been constructed to prevent lahar flow onto the main highway; and a comprehensive monitoring and alarm system was constructed to detect lahar break outs. An integrated response plan involving emergency managers, police, the fire service, road managers, railways operators, ski field staff, scientists and national park managers, was developed to stop all trains outside the hazard zone, close the highway, trigger warnings and response plans at the ski fields (move to ridges away from flow paths) (Leonard et al. 2005), and locate and evacuate any hikers or workers in hazard zones within the national park. The tephra dam burst early in 2007, and the response based on high quality modelling went as planned. The lahar was of considerable size but remained within expected channels and the only significant damage was to an unoccupied public toilet building at the Tangiwai memorial site.
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Lahar flows and eruptions remain an ongoing hazard at Ruapehu. To assist with preparedness for these hazards, remote sensing is part of the suite of monitoring systems employed to detect changes in volcanic activity. A combination of synthetic aperture radar, ASTER thermal imagery (Figure 3), and OMI UV/visible imagery is acquired on a routine basis for monitoring deformation, Crater Lake temperatures and gaseous emissions respectively.
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Figure 3.
Thermal monitoring of Mt Ruapehu. (a) SPOT-5 image obtained 15 March 2008 demonstrates land cover for contextual purposes; (b) Average temperature image calculated from night-time ASTER thermal data between 3 September 2007 and 28 September 2008; and (c) Mt Ruapehu Crater lake subsets using ASTER night-time thermal data. Note the temperature scale change for illustrative purposes.
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The use of remotely sensed data of a previous event can be used in this phase to constrain geophysical models and help provide realistic scenarios for future events. For example, InSAR can be used to examine the deformation effects of a single event (such as an earthquake) by acquiring only two images as close in time as possible, one before and one after the event. Using this technique, the PALSAR L-band sensor on board the ALOS satellite was successfully used to map co-seismic deformation of a magnitude 6.7 earthquake in the vicinity of George Sounds, off the coast of the lower South Island on 16th October 2007 (Petersen et al. 2009 in review). After processing two PALSAR images (22 July and 22 October 2007) displacements were apparent in the coastal region closest to the epicentre (Figure 4). Landslides were also experienced in the area (though not evidenced in this figure). The long wavelength L-band is of particular use in this region due to its ability to penetrate dense vegetation to retrieve the ground signal. The amount and location of deformation is used in modelling studies to estimate earthquake parameters in order to learn more about the tectonics of this remote region. As this is an uninhabited area of New Zealand, there was no observed infrastructure damage that may have otherwise necessitated acquisition of high resolution optical imagery for response or recovery purposes.
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Figure 4.
Ground deformation following George Sounds earthquake in October 2007. Background image is a Landsat 7 ETM+ true colour composite scene
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Monitoring longer term ground deformation effects such as that produced by ground water extraction, volcanic activity or slow moving landslides is conducted using multiple SAR images over a period of time. Using this technique it is possible to detect sub centimetre scale ground movement over large areas that could otherwise only be monitored or detected using networks of in-situ GPS. With this method, the C-band sensor on board the ENVISAT satellite was able to detect sub-centimetre deformation in the Auckland region (Figure 5). This figure was created using a stack of 117 images, spanning the period 17 July 2003 and 9 November 2007. InSAR is used in this manner for long term monitoring and produces a rate of change over time. It is believed that most of the observed InSAR signal shown here is caused by extraction of groundwater; however the link to volcanic activity has also been investigated (Samsonov et al. 2009 in review).
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Figure 5.
Monitoring uplift and subsidence in Auckland. Background image is a green band grey scale mosaic of SPOT-5 and Landsat 7 ETM+ imagery.
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4.3 Response
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Response activities are primarily focussed on protecting life and property during disasters. Activities such as evacuations, search and rescue, sandbagging along riverbanks, evaluating building safety, establishing immediate emergency shelter, setting up command posts and other short-term tasks fall into the response phase. Remote sensing can be used here to provide immediate damage assessment if the data can be provided in a timely manner, and also to assist evacuation plans through the combination of observing weather patterns and hazard behaviour (e.g. fire front approaches, water level rises). Other examples of the use of remote sensing during the response phase are given in Table. 3. Ideally, recovery activities commence when the response phase begins, to ensure an integrated process for holistic recovery. This means that damage assessments undertaken via remote sensing during the response phase will also be integral to the recovery phase.
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Type of information
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Data required
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Sensor example
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Application example
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Inundation
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SAR, optical
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Radarsat, , ASTER Quickbird, Ikonos
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Determine magnitude, location and duration of impacts. Use SAR when cloud cover is still problematic
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Widespread storm or earthquake induced landslides
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SAR, moderate - high resolution optical
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Radarsat, , ASTER Quickbird, Ikonos
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Determine magnitude, location and duration of impacts.
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Volcanic ash and gases
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Shortwave infra red, thermal infrared
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GOES, TOMS/ , MODIS
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Highly temporally variable, so minimum of daily imagery required. Used for volcanic ash advisories and to warn airlines of hazardous flight paths
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Public information during events
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High resolution optical imagery
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Quickbird, Ikonos
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Assist those at risk to personalise hazard threat
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Ship location
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SAR
\n\t\t\t\t\t\t
Terra SAR-X, Cosmo Sky-Med
\n\t\t\t\t\t\t
Locating ships in the ocean during storm
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Co-seismic and post-seismic deformation
\n\t\t\t\t\t\t
InSAR
\n\t\t\t\t\t\t
-1/2, ENVISAT ASAR, ALOS PALSAR
\n\t\t\t\t\t\t
Confirming magnitude of earthquake and forecasting possible aftershocks
\n\t\t\t\t\t
\n\t\t\t\t
Table 3.
Examples of information and data requirements during the response phase
\n\t\t\t
During the response phase, the temporal relevancy of remote sensing information is crucial to allow disaster managers to plan effective mitigation strategies on dynamic situations. In the case of wildfire events, it is critical to have current and timely intelligence on the fire location, fire-front, and fuel conditions. Near-real-time information allows the fire management team to plan fire attack appropriately, consequently saving resources, time and possibly lives. Concurrently, the information must be of sufficient spatial resolution to allow detailed tactical assessments and decisions to be made on the wildfire condition, and be spectrally-relevant to the phenomenon being observed or measured.
\n\t\t\t
Despite the spectacular nature of imagery often captured during a disaster event, the use of remote sensing during the response phase has experienced mixed levels of success, particularly in the case of satellite platforms. Regional scale imagery of effects associated with the development of fire fronts (hot spot detection), volcanic eruptions (gas and ash emissions), or tropical cyclones (inundation) is generally successful where the area of impact is sufficiently large. For example, the wildfire management agencies in the United States currently utilize thermal-infrared (TIR) satellite data provided by MODIS to provide synoptic, 2-4 times-daily hot-spot detection of fire at continental scales (U.S. Forest Service 2009). The spatial resolution of MODIS is low / moderate (1000 meters), and is used to derive a regional estimate of fire distribution. Although the temporal frequency of the MODIS data is sufficient for regional fire assessment, its spatial resolution is insufficient for more localised events, or for assessing the specific on-ground impact. Conversely, polar orbiting satellites with appropriately high spatial resolution generally do not have the overpass frequency or data relay capability to provide imagery quickly enough to be of use for immediate response. The space science community is attempting to address this issue with the launch of satellite constellations such as Rapid Eye and the Disaster Monitoring Constellation (International collaboration between Algeria, China, Nigeria, Turkey and the UK). There are also avenues for collaboration between international organisations for data acquisition and provision in the event of disasters, such as the International Charter for Space Based Disasters (Ito 2005), and Sentinel Asia (Kaku et al. 2006). While potentially providing a considerable amount of data, neither of these tools can yet be used for immediate or first response due to the current time delay between requesting and receiving data. As such, research into airborne platforms has proven to be of greater utility for rapid data and information provision.
\n\t\t\t
In 2006, 2007 and 2008, the National Aeronautics and Space Administration (NASA) and the U.S. Forest Service collaborated to evaluate and demonstrate the use of long-duration, large Unmanned Airborne Systems (UAS), innovative sensing systems, real-time onboard processing, and data delivery and visualisation technologies to improve the delivery and usefulness of remote sensing data on wildfire events. The objectives were to demonstrate the capabilities of providing sensor-derived, GIS-compatible, geo-rectified, processed data on wildfire conditions to incident management teams within 15-minutes of acquisition from the sensors on the UAS. The characteristics of this system render it ideal for emergency response that is not just isolated to wildfire events.
\n\t\t\t
During the 2006, 2007 and 2008 U.S. wildfire season, a series of missions were flown over wildfires in the western U.S. to demonstrate the integration of the above-mentioned technologies to provide near-real-time information to disaster managers. The missions were flown on the NASA Ikhana, a modified General Atomics – Aeronautical Systems, Inc. Predator-B (MQ-9) Unmanned Aerial Vehicle (UAV), designed specifically for supporting NASA science missions. The Ikhana is capable of medium / high altitude and long-duration (24-hours) operations, making it an ideal platform for disaster event monitoring. The Ikhana UAS flew missions with the NASA AMS-Wildfire sensor onboard, which can be remotely operated and provides autonomous data processing capabilities (Ambrosia & Wegener 2009).
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The use of the Ikhana and accompanying systems has proven successful over a number of events. In October 2007, four missions were flown over the Santa Ana wildfires in a five-day period (Figure 6a) and the resultant information was used to deploy fire fighting resources. In late June 2008, lightning storms in northern California ignited thousands of fires, that grew together to become over 25 major incidents covering millions of acres of forestlands. The national airborne remote sensing assets were overwhelmed and with a state emergency declared, the Ikhana and AMS-Wildfire were requested to support wildfire data collection operations. During the remainder of the summer, the Ikhana flew four missions in California, providing near-real-time data on numerous wildfires. The AMS-Wildfire real-time data were used effectively to locate a major fire surge encroaching on Paradise, California (Figure 6b). The data was used to support the emergency evacuation decision of the entire population of the community, an effective demonstration of the criticality of near-real-time remote sensing information supporting disaster management operations.
\n\t\t\t
Figure 6.
a) Flight routes required to cover 11 major wildfires California over four days in October 2007; and (b) AMS-Wildfire 3-band graphic image overlay and fire hot-spot detects (yellow areas) of the Canyon Complex fire approaching Paradise, California. The data was acquired on 8 July 2008. The hot-spot detect data, showing the fire moving rapidly towards Paradise, assisted in the evacuation determination for residents in the vicinity. This north-viewing 3-D data is displayed on Google Earth background information.
\n\t\t\t
One of the key factors to the success of this system is the provision of not only data, but information that can be ingested and utilised immediately by emergency managers to aid their decision making. Part of this speed of information delivery is attributed to the autonomous processing onboard the UAS to create geo-rectified image raster products (GeoTIFF) and hot-spot detection vector files (.shp files). An emergency situation is not the time to be experimenting with new algorithms or processing techniques, thus it is necessary to ensure robust techniques have been thoroughly trialled and considered operational pre-event (Joyce et al. 2009a). The vector and raster products generated with this system are transmitted via the Ikhana telemetry system, through a communications satellite to servers on the ground, where they are automatically processed into Keyhole Markup Language (KML) files, compatible with Google Earth and made available in near-real-time at NASA servers. The combination of the near-real-time imagery and the simple Google Earth visualisation capabilities are a powerful tool that requires minimal (or no) training in its employment. Embedding a remote sensing specialist within the emergency management team can further assist with data integration, information understanding, and fielding specialized requests.
\n\t\t\t
Although the Western States UAS Fire Imaging Missions were focused on demonstrating remote sensing capabilities to wildfire management entities, they resulted in direct emergency support to national incidents in all three years. Those missions allowed a comprehensive assessment of the technologies and resulted in the adaptation and integration of various components into operational use. The key components to the “usefulness” of the data were the timeliness of the data (from acquisition to product delivery) and the simple format which the data was available for visualisation and decision-making. While these factors are important at all stages of the disaster management cycle, they become particularly critical during the response phase, where rapid decision making is most important. The provision of simple hotspot information also means that the emergency management team is not overwhelmed with too much data or too many visualisation options. The choice of using Google Earth as a “front-end” display of the data was a careful decision to provide information in a format and software system that was easily operated and readily available to the fire management community. Fire Incident Command team members do not have the time to “learn” new software capabilities or new tools while they are in the midst of a major wildfire management activity. Google Earth provided a user-friendly capability to allow quick data integration, zoom capabilities, 3-D visualisation and ease of use.
\n\t\t\t
The use of UAVs presents opportunities as well as risks. UAVs provide increased range and flight time and the ability to penetrate environments that might be too hazardous for piloted aircraft (Henson 2008). Mission and platform costs currently precludes immediate adaptation of UAS systems by disaster management agencies, but the disaster support missions we showcased are major steps forward in demonstrating UAS utility and sensor and processing capabilities available right now! These technologies need not be considered for use only with unmanned vehicles, but can be adopted for piloted aircraft, and hopefully for satellite platforms in the future. Autonomous onboard processing has been trialled with Hyperion for identifying hotspots associated with volcanic eruptions (Davies et al. 2006), though the challenge remains to progress these techniques to operational status.
\n\t\t\t
\n\t\t\t\t
4.4. Recovery
\n\t\t\t\t
The use of remote sensing to aid or monitor disaster recovery is perhaps the least developed application of this technology. However, this is an area where the remote sensing community could contribute a great deal through the provision of objective time series analysis over large areas with both high and medium levels of spatial detail. In other specialisations, time series analysis of remotely sensed data is an established technique. Environmental applications such as deforestation and urban sprawl are common targets. In each case, the monitoring objective is clear. In disaster recovery, there are often some very clear indicators that can easily be measured and monitored with remote sensing imagery. Some of these indicators include construction and subsequent removal of medium and long-term emergency shelters; debris removal; commencement and completion of new construction or reconstruction (buildings, bridges, roads); vegetation regrowth; and reduction of siltation from waterways after flooding events (Table 4).
\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Type of information
\n\t\t\t\t\t\t\t
Data required
\n\t\t\t\t\t\t\t
Sensor example
\n\t\t\t\t\t\t\t
Application example
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Rate of recovery e.g. debris removal, vegetation regrowth, reconstruction
\n\t\t\t\t\t\t\t
Moderate to very high resolution imagery in a continuous time series
\n\t\t\t\t\t\t\t
Aerial photography, Quickbird, Worldview, Ikonos
\n\t\t\t\t\t\t\t
Compare the effectiveness of different recovery strategies; Determine if aid funding is being used appropriately; Wildlife habitat recovery (eg after fire); Identify "eresidual risk" - areas not recovered are more vulnerable to future events
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Infrastructure and facilities locations
\n\t\t\t\t\t\t\t
Very high resolution imagery
\n\t\t\t\t\t\t\t
Aerial photography, Quickbird, Worldview, Ikonos
\n\t\t\t\t\t\t\t
Create new baseline maps
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Revised DEM
\n\t\t\t\t\t\t\t
InSAR, LiDAR
\n\t\t\t\t\t\t\t
-1/2, ENVISAT ASAR, ALOS PALSAR
\n\t\t\t\t\t\t\t
Necessary after large earthquake or volcanic eruption if the local and regional elevation changes
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Status Quo
\n\t\t\t\t\t\t\t
Very high resolution imagery
\n\t\t\t\t\t\t\t
Aerial photography, Quickbird, Worldview, Ikonos
\n\t\t\t\t\t\t\t
Plan areas for funding allocation
\n\t\t\t\t\t\t
\n\t\t\t\t\t
Table 4.
Examples of information and data requirements during the recovery phase
\n\t\t\t\t
Using high spatial resolution the amount of housing reconstruction can at least be visually identified by the presence and absence of blue tarpaulins covering roofs following Hurricane Katrina (Hill et al. 2006). Conceivably an automated detection method could be developed to identify these quickly and repeatedly in a time series dataset. The authors also provide a list of other recovery related features observable over time with Quickbird data. In Figure 7, the progression of recovery in a small area of New Orleans can be seen with high resolution data. Notable features in the image acquired a week before the hurricane are a large car park, sporting fields, and residential housing (Figure 7a). The progression clearly shows inundation in this area (Figure 7b), and remaining sediment shortly after the water subsidence. By March 2006, temporary housing is evident in the location of the car park, and is still visible three years after the event, though the number of roofs covered in blue tarpaulins has decreased. An analysis of the relative rate of change is given in Figure 7k, demonstrating that impervious surfaces and lines of communication such as roads moved towards recovery quite quickly after the event, while mature vegetation takes somewhat longer. Some roofing damage and a swimming pool appear to remain in an unrepaired state three years after the event. The key here is that a time series of data is vital to determine if any change is occurring, and to further extract rates of change.
\n\t\t\t\t
Recovery rates following a widespread landsliding event in northern New Zealand can also be seen from a series of SPOT-5 and ALOS AVNIR-2 imagery (Figure 8). Here the landsliding is apparent as bright scars in the colour infra red imagery acquired four months after the event (Figure 8b). One year later, recovery of many of the grassy slopes on the eastern portion of the image can be seen, while the landslides in the western region are also becoming overgrown (Figure 8c). This recovery becomes even more apparent in the series of NDVI images, which highlight the contrast between landslides (black) and surrounding vegetation (various shades of grey) (Figure 8d-f). In an area that was covered with many thousand landslides (Joyce et al. 2008a), satellite remote sensing is the only time and cost effective manner of data collection for understanding recovery in the area. Similar techniques could be used to look at native habitat regeneration following bushfires.
Recovery of vegetation after a widespread landsliding event in northern New Zealand, July 2007. (a) SPOT-5 CIR obtained before the event; (b) SPOT-5 CIR obtained shortly after the event; (c) ALOS AVNIR-2 CIR imagery obtained one year later; and (d-e) NDVI images of the aforementioned data.
\n\t\t\t\t
Analysis of time series imagery could also help to monitor the effectiveness of different recovery strategies. By extracting recovery rates from data acquired at appropriate time intervals, this assessment could help guide recovery plans for future events of a similar nature. This would also help identify areas of residual risk that require ongoing monitoring until the physical recovery process completed.
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\n\t\t
\n\t\t
\n\t\t\t
5. Conclusions
\n\t\t\t
Remote sensing can be used to inform many aspects of the disaster management cycle. An exhaustive coverage of all potential applications would be impossible in a single book chapter, however we have shown several good examples from which inspiration can be sought for future use. It is important to consider all aspects of disaster management, rather than focussing on emergency response. By incorporating remote sensing into reduction and readiness activities, this can also educate both emergency management staff and the community about this type of information so that they are familiar with its use under a response and inherently pressured situation.
\n\t\t\t
The key elements to facilitate the usefulness of remote sensing data in support of the disaster management community are being able to provide the appropriate information in a spectrally, temporally, and spatially relevant context. Additionally, one must be aware of the information requirements of that disaster management community, and tailor the remote sensing information to meet those needs. That can only come through close collaborations between the disaster management community and the remote sensing / geospatial community.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/9556.pdf",chapterXML:"https://mts.intechopen.com/source/xml/9556.xml",downloadPdfUrl:"/chapter/pdf-download/9556",previewPdfUrl:"/chapter/pdf-preview/9556",totalDownloads:6633,totalViews:1085,totalCrossrefCites:4,totalDimensionsCites:24,totalAltmetricsMentions:3,impactScore:9,impactScorePercentile:97,impactScoreQuartile:4,hasAltmetrics:1,dateSubmitted:null,dateReviewed:null,datePrePublished:null,datePublished:"October 1st 2009",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/9556",risUrl:"/chapter/ris/9556",book:{id:"3343",slug:"advances-in-geoscience-and-remote-sensing"},signatures:"Karen E. Joyce, Kim C. Wright, Sergey V. Samsonov and Vincent G. Ambrosia",authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. The disaster management cycle ",level:"1"},{id:"sec_3",title:"3. Remotely sensed data types",level:"1"},{id:"sec_3_2",title:"3.1. Optical",level:"2"},{id:"sec_4_2",title:"3.2. Thermal",level:"2"},{id:"sec_5_2",title:"3.3. Synthetic Aperture Radar",level:"2"},{id:"sec_7",title:"4. Remote sensing applications",level:"1"},{id:"sec_7_2",title:"4.1. Reduction",level:"2"},{id:"sec_8_2",title:"4.2. Readiness",level:"2"},{id:"sec_10",title:"4.3 Response",level:"1"},{id:"sec_10_2",title:"4.4. Recovery",level:"2"},{id:"sec_12",title:"5. Conclusions ",level:"1"},{id:"sec_14",title:"Acknowledgments",level:"1"},{id:"sec_13",title:"8. Glossary",level:"1"},{id:"sec_15",title:"8. Glossary",level:"2"}],chapterReferences:[{id:"B1",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAmbrosia\n\t\t\t\t\t\t\tV. G.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWegener\n\t\t\t\t\t\t\tS. S.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2009\n\t\t\t\t\tUnmanned airborne platforms for disaster remote sensing support. 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In: At Risk: Natural Hazards, people’s vulnerability and disasters, Wisner B, Blaikie P, Cannon T, Davis I (Eds.), 3\n\t\t\t\t\t48 , Routledge, London & New York\n\t\t\t'},{id:"B56",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWright\n\t\t\t\t\t\t\tR.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFlynn\n\t\t\t\t\t\t\tL.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tGarbeil\n\t\t\t\t\t\t\tH.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHarris\n\t\t\t\t\t\t\tA.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tPilger\n\t\t\t\t\t\t\tE.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2002\n\t\t\t\t\tAutomated volcanic eruption detection using MODIS. Remote Sensing of Environment, 82, 1, 135 \n\t\t\t\t\t\n\t\t\t\t\n\t\t\t'},{id:"B57",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWright\n\t\t\t\t\t\t\tR.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFlynn\n\t\t\t\t\t\t\tL. P.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tGarbeil\n\t\t\t\t\t\t\tH.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHarris\n\t\t\t\t\t\t\tA. J. L.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tPilger\n\t\t\t\t\t\t\tE.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2004\n\t\t\t\t\tMODVOLC: near-real-time thermal monitoring of global volcanism. Journal of Volcanology and Geothermal Research, 135, 1-2, 29 \n\t\t\t\t\t 49\n\t\t\t\t\n\t\t\t'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Karen E. Joyce",address:null,affiliation:'
GNS Science, New Zealand
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GNS Science, New Zealand
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GNS Science, New Zealand
'},{corresp:null,contributorFullName:"Vincent G Ambrosia",address:null,affiliation:'
California State University – Monterey Bay, United States of America
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1. Introduction
Living organisms are constitutionally wired to store energy for survival in periods of scarcity. Eel and salmon are reported to survive long periods without food [1, 2, 3]. The excess intake of calories leads to energy accumulation in the form of fat, glycogen, or starch. Plants store energy reserves as starch and oil. We were unable to find reports of adverse consequences of excess energy storage in plants and lower organisms. The stored energy helps the organism to tide over periods of calorie scarcity and during hibernation, aestivation, or migration in animals. In higher organisms, deposition of excess calories results in impairment of body functions with adverse effects on health and longevity. Obesity with adverse health effects has been reported in zebrafish [4], reptiles [5, 6], and birds [7].
Energy in humans is stored as glycogen or triacylglycerols (TAGs). Relative to the amount of calories that can be stored as triacylglycerols (TAGs), only a small amount of calories can be stored as glycogen. An adult liver can store up to 120 g glycogen, while the skeletal muscles can store up to 400 g glycogen. Triacylglycerols are hydrophobic energy-dense molecules that can be stored in large amounts in the adipocytes. Adipose tissue is the loose collection of adipocytes in a mesh of collagen fibers, deposited at various sites in the body. Preadipocytes, fibroblasts, vascular endothelial cells, adipose tissue macrophages, and small blood vessels are also present in the adipose tissue.
Increased mass of adipose tissue, abnormal site of deposition, or abnormal size of adipocytes can result in adverse consequences on health and quality of life (Table 1).
Type of problems
Examples of associated conditions
Physical problems
1. Musculoskeletal disorders
Decreased mobility
Loss of balance
Osteoarthritis
Gout
2. Respiratory problems
Decreased lung compliance
Increased risk of asthma
Sleep apnea
3. Lower limb venous disease
Thrombosis
Varicose veins
Venous insufficiency
4. Skin-related problems
5. Stress incontinence in females
Metabolic disorders
1. Hyperglycemia
2. Dyslipidemia
3. Gout Hyperglycemia increases risk of skin infections, eye diseases, and kidney diseases. Both hyperglycemia and dyslipidemia cause insulin resistances, leading to increased risk of type 2 diabetes, cardiovascular disease, stroke, and cancers.
Gut-associated diseases
1. Cholelithiasis
2. Pancreatitis
3. Fatty liver
4. Gastroesophageal reflux disease
Reproductive Health Issues
A. Males 1. Hypogonadism
2. Gynecomastia
3. Decreased fertility
B. Females
1. Polycystic Ovarian Syndrome (PCOS)
2. Anovulation
3. Endometrial hyperplasia
C. Increased risk of complications in pregnancy
1. Gestational diabetes
2. Preeclampsia
3. Cesarian section
Economic issues
1. Increased expense on obesity-related diseases
2. Decreased pay
3. Decreased job opportunity
Mental and social issues
1. Social stigma
2. Bullying
3. Binge eating
4. Depression
Quality of life and mortality
1. Increased risk of morbidity, mortality decreased quality of life
Table 1.
Multiple consequences of obesity.
2. Physical problems associated with obesity
These result from the abnormally high weight of the affected person and are closely related to each other and to the other consequences of obesity including metabolic dysfunction and insulin resistance. For convenience, we have classified them into musculoskeletal disorders, skin-related problems, respiratory problems, lower-limb venous diseases, and urinary incontinence.
2.1 Musculoskeletal disorders
These include decreased mobility, loss of balance, and osteoarthritis, which are associated with abnormal increase in body weight (Figure 1).
Figure 1.
Association of obesity with musculoskeletal disorders.
2.1.1 Decreased functional mobility
Obesity is one of the major causes for the loss of functional mobility. Altered posture and gait resulting from abnormal fat deposition, compromised bone strength, pain, and breathlessness compromise the mobility [8], which must be taken into account by treating physicians advising increased physical activity for weight loss. Decreased mobility results in further increase in weight.
2.1.2 Loss of balance
Increased weight, decreased mobility, and altered posture result in loss of balance, increasing the risk of falls and injury [9]. In spite of the cushioning effect of the fat mass, falls in patients with obesity are more serious and require higher treatment costs and specialized care [10].
2.1.3 Osteoarthritis (OA)
Progressive loss of articular cartilage and formation of osteophytes (bony spurs usually caused by local inflammation) result in osteoarthritis [11]. Obesity is a risk factor for OA of knee, hands, and wrist (but not of hip) [12]; thus excessive body weight alone cannot fully explain the increased incidence of OA in people with obesity. Increased body mass index (BMI) in obesity results in altered gait and increased strain on the knee, causing biomechanical joint loading [13]. This is associated with increased expression of matrix metalloproteinases in chondrocytes and increased degradation of proteoglycans [14]. Synthesis of DNA, proteoglycans, and collagen is decreased, contributing to the loss of cartilage in joints [14]. Chondrocytes subjected to high loading show increased expression of pro-inflammatory cytokines including TNF-α and IL-1(β), along with an increased expression of cyclooxygenase-2 leading to increased PGE2 (responsible for inflammatory pain) synthesis [15].
Increase in the amount of adipose tissue leads to metabolic dysfunction: obesity-related sarcopenia, deposition of intramuscular lipid, and chronic low-grade systemic inflammation, all of which contribute to osteoarthritis [16].
2.1.4 Gout
Insulin resistance, often seen in patients with obesity, causes decreased excretion of uric acid, leading to hyperuricemia [17, 18]. Adipose tissue is known to express all the components of renin-angiotensin system (RAS), including angiotensinogen [19]. The resulting hypertension may cause glomerular arteriolar damage and reduce uric acid excretion. Hyperuricemia and gout have been associated with osteoarthritis [20, 21].
2.2 Respiratory problems
Obesity is associated with various respiratory problems that are correlated with each other (Figure 2).
Figure 2.
Association of obesity with respiratory disorders.
2.2.1 Reduced compliance of lungs
Increased fat deposition in the mediastinum and abdominal cavity increases intra-abdominal and pleural pressure, thus reducing compliance of the lungs. Altered breathing pattern, with decrease in expiratory reserve volume (ERV), functional reserve capacity (FRC), and tidal volume (TV), with slight increase in mean respiratory rate have been reported in subjects with obesity [22, 23], Obesity has little effect on the residual volume (RV) and total lung capacity (TLC) [24].
2.2.2 Obesity and asthma
The relationship between obesity and asthma has been established by a meta-analysis involving more than 300,000 adults [25]. The expression of adipokines secreted by adipose tissue is different in persons with obesity. Decreased expression of adiponectin (anti-inflammatory adipokine) and increased expression of leptin (pro-inflammatory adipokine) have been reported in asthmatic patients with obesity [26]. Leptin, an anorexigenic hormone, increases metabolic rate and is involved in surfactant production and neonatal lung development [27]. Sood et al. [28] have reported a strong association between high BMI and high levels of serum leptin with asthma in adults.
Inflammatory cytokines such as TNF-α, IL-8, and monocyte chemoattractant protein-1 (MCP-1) have also been reported to be raised in persons with obesity. However, their role in asthma associated with obesity is not clear [29]. In older patients, abdominal obesity and metabolic syndrome have been reported to be associated with restrictive lung disease [30].
2.2.3 Obstructive sleep apnea (OSA)
The prevalence of obstructive sleep apnea in adult persons with obesity is about 45%, compared with 25% in persons with normal weight [31]. Increased fat deposit in tissues surrounding the upper airway decreases the size of lumen and increases collapsibility of the upper airway. OSA may cause sleep fragmentation, which may lead to sleep deprivation [32]. Since experimental sleep deprivation and self-reported short sleep have been linked with metabolic dysregulation, it is possible that OSA may also be a contributing factor in metabolic dysregulation associated with obesity.
2.3 Lower limb venous diseases
Venous diseases (blood clots, deep vein thrombosis, superficial venous thrombosis or phlebitis, chronic venous insufficiency or CVI, varicose and spider veins, and venous stasis ulcers) may be caused by one or more of the following factors: immobility (as in bed-ridden patients) leading to stagnation of blood), blood vessel injury caused by trauma/needles/intravenous catheters/infections, central venous hypertension, conditions that increase the blood coagulation, and pregnancy. Different cancers are associated with deep vein thrombosis.
Varicose veins and chronic venous insufficiency are more common in aged women compared with men. Obesity has been found to be associated with all types of lower limb venous diseases (Figure 3). Willenberg et al. [33] showed that lower limb venous flow parameters are different in healthy persons with and without obesity. Various epidemiological studies show that obesity is associated with chronic venous disease, phlebitis, and thromboembolism [34, 35, 36, 37]. Untreated CVI results in increased pressure and swelling leading to rupture of capillaries. The skin may appear reddish-brown and becomes sensitive to bumps and scratches. Burst capillaries may lead to inflammation and even ulcers.
Figure 3.
Obesity as a cause of lower limb venous diseases.
Increased intra-abdominal pressure caused by central obesity is transmitted to the extremities via femoral veins leading to resistance to venous return, producing venous valvular insufficiency. The self-perpetuating cycle of worsening venous insufficiency causes venous stasis and distension of veins in the lower limb. Obesity produces a chronic low-grade inflammation, which damages the affected veins and increases the risk of thromboembolism [33].
2.4 Skin problems
Different problems of the integumentary system associated with obesity can be classified on the basis of their pathophysiologic origin (Figure 4). Skin lesions associated with mechanical causes include striae, lipodystrophy, plantar hyperkeratosis, and venous insufficiency. Acanthosis nigricans and skin tags or acrochordons are due to insulin resistance. Obesity-related hyperandrogenism may cause acne, hirsutism, and androgenic alopecia. Skin folds created by obesity increase the risk of intertrigo and infections.
Figure 4.
Dermatological manifestations associated with obesity.
2.4.1 Mechanical causes of dermatologic manifestations associated with obesity
Striae or stretch marks are a type of scarring of the dermis associated with stretching of the dermis. Striae distensae may appear as a consequence of pregnancy, puberty, or obesity and appear on abdomen, breasts (in females), and shoulders (in body builders). They are more common in females. [38]. Striae atrophicans due to thinning of the skin may appear in adrenal gland disorders [39].
Other dermatological conditions with mechanical causes include intertrigo, conditions associated with chronic venous insufficiency, and lymphedema [40]. Intertrigo is an inflammation of skin resulting from friction between opposing skin surfaces of skin folds. It may have an infectious component. Axilla, groin, intergluteal, and inframammary areas may be involved [41]. Hot, humid climates and obesity (BMI > 30 kg/m2) are known to promote intertrigo. Persons with obesity tend to sweat more.
Dermatologic sequelae of chronic venous insufficiency (discussed above) are often seen in patients with obesity and include pitting edema, varicose veins, telangiectasia, hyperpigmentation, venous stasis ulcers, and scaling of the skin (stasis dermatitis) [42].
Blocking or damage of the lymphatic system resulting in accumulation of lymph in soft tissues, especially legs or arms, is called lymphedema. Obesity is a risk factor for secondary lymphedema [40].
2.4.2 Obesity-related endocrine disorders of skin
These include skin tags, acanthosis nigricans, keratosis pilaris, hidradenitis suppurativa and hirsutism, and plantar hyperkeratosis.
Skin tags or acrochordons. Skin tags are soft cutaneous growths, usually benign, more commonly seen in persons with obesity, metabolic syndrome, type 2 diabetes, or in persons with family history of skin tags [43]. They occur in both males and females, usually later on in life, but are less common after the seventh decade. The polypoid lesions are skin-colored, brown, or red, 1–5 mm in size (rarely larger) with a loose edematous fibrovascular core, and may be attached to a fleshy stalk. They are more common in skin folds: axilla, groin, eyelids, and neck [44]. Although not painful, they can cause trouble by getting caught in clothing or jewelry, resulting in itching or bleeding. However, skin tags in large numbers may be seen in patients with Birt-Hogg-Dube (BHD) syndrome and tuberous sclerosis, where they appear around the neck: the molluscum pendulum necklace sign [45, 46].
Acanthosis nigricans (AN). Hyperpigmented velvety plaques usually in body folds, neck, knuckles, and scalp may be seen in patients with obesity. The condition was first reported more than an hundred years ago in the Atlas for Rare Skin Diseases. The term acanthosis nigricans was proposed by Paul Gerson Unna and published in 1891 in a case report by Sigmund Pollitzer [47]. Obesity-associated AN was previously called pseudo acanthosis nigricans; however, this term is incorrect. This is because the initial cases identified in Europe were associated with abdominal or pelvic malignancies. Association of AN with obesity was first reported by Robertson and Tasker in 1947 [48]. Like acrochordons, AN is also associated with insulin resistance often seen in obesity. Probably, the hyperinsulinemia seen in insulin resistance leads to direct and indirect activation of the insulin-like growth factor receptor, triggering proliferation of the dermal fibroblast and epidermal keratinocyte [49]. Friction and perspiration may also be involved in the development of AN [50].
Keratosis pilaris (chicken skin) is a benign condition of the skin in which sterile papules occur on the skin (collections of dead skin cells). Though these papules may occur anywhere on the body (except palms and soles), they are more common on the posterior aspect of upper arms, anterior aspects of thighs, face, and buttocks [51].
Hidradenitis suppurativa or acne inversa is a chronic painful condition of the terminal follicular epithelium in the apocrine gland–bearing skin (groin, bottom, axilla, breasts) [51]. It affects about 1% of the population and is strongly associated with smoking and obesity. It is also linked with hyperandrogenemia, as many patients have acne and hirsutism [52].
Hirsutism, acne vulgaris, and androgenic alopecia seen in some female patients with obesity (with or without polycystic ovarian syndrome, PCOS) are due to hyperandrogenemia, often associated with peripubertal obesity [51, 52, 53, 54]. Increased insulin production (hyperinsulinemia) due to insulin resistance in obesity increases IGF-1 levels and augments ovarian androgen production [55]. Hyperinsulinemia produces a decrease in serum level of steroid hormone binding globulin (SHBG), resulting in a further increase in the level of free testosterone. Treatments that reduce insulin levels usually correct hyperandrogenemia and ovulatory dysfunction [56].
Plantar hyperkeratosis (thickening of skin over metatarsophalangeal joints, caused due to increased pressure and mechanical stress placed on the feet) is seen in almost 50% patients with obesity [40]. Increased circulating levels of IGF-1 seen in hyperinsulinemia lead to overactivation of IGF-1 receptors on fibroblasts and keratinocytes. The abnormal IGF-1 signaling causes cellular hyperproliferation (Figure 4).
2.4.3 Increased risk of skin infections
Obesity has been associated with an increased risk of skin, respiratory tract, and urinary tract infections [57]. An increased risk of community-acquired infections has been reported by Harpsoe et al. [58] in both overweight and underweight women. Obesity alters the function of skin, sebum, and sweat glands, affects the structure of collagen and subcutaneous fat, and slows wound healing. A number of skin infections that are more common in persons with obesity include candidiasis, candida folliculitis, furunculosis, tinea cruris, and folliculitis. Cellulitis is less common [42].
Normal adipose tissue in a nonobese person has a population of anti-inflammatory/regulatory immune cells: M2-macrophages and regulatory T cells. These are replaced by pro-inflammatory cells: M1 macrophages, Th1, Th17, and cytotoxic T cells in adipose tissue in persons with obesity [59]. Systemic immune adaptations in obesity include increased number of circulating monocytes, neutrophils, Th1, Th17, and Th22 cells. The pro-inflammatory cytokines produced by pathogenic adipose tissue (IL-1β, IL-6, IL-17, and IFN-γ) result in a chronic low-grade inflammation. Skin conditions such as psoriasis, atopic dermatitis, and eczema are strongly associated with obesity [60]. Hashba et al. [61] have suggested the association of lichen planus with obesity.
2.5 Urinary incontinence (UI)
Urinary incontinence may be of different types: stress incontinence when pregnancy, childbirth, etc., weaken the muscles supporting and controlling bladder; urge incontinence caused by involuntary action of bladder muscles; and mixed incontinence that shares the causes of both stress and urge incontinence. Thyroid problems, uncontrolled diabetes, and medicines such as diuretics can worsen the problem of UI. High BMI, especially BMI higher than 40 kg/m2, has been strongly associated with stress predominant incontinence including mixed incontinence [62]. Central obesity increases the abdominal pressure, which increases the bladder pressure and urethral mobility, leading to UI. Chronic strain and stretching seen in pregnancy and abdominal obesity weaken the muscles and other structures of the pelvic floor. Surgical and non-surgical weight loss has been reported to decrease incontinence and improved quality of life.
3. Metabolic disorders associated with obesity
3.1 Organization of the adipose tissue
Adipose tissue is a loose connective tissue in which about half the cells are adipocytes, the remaining is stromal vascular fraction containing preadipocytes, fibroblasts, endothelial cells, and macrophages [63]. The adipose tissue may be considered the largest endocrine gland in the body.
Based on the metabolic features of the adipocytes, adipose tissue (AT) can be white adipose tissue (WAT), which stores excess energy as fat, and brown adipose tissue (BAT), which dissipates stored energy as heat (Figure 5). Both WAT and BAT are present in mammals and are formed throughout life. In humans, WAT development begins during early to mid-gestation period. WAT adipocytes contain a large single (unilocular) droplet of triacylglycerols occupying 90% of the cell volume, with the cytoplasm and the nucleus squeezed to the periphery. Adipocytes of BAT are smaller, multilocular, and contain mitochondria and uncoupling protein-1 (UCP-1), which is involved in non-shivering thermogenesis. The brown appearance of BAT is due to high vasculature and high mitochondrial content. It has a high density of noradrenergic parenchymal fibers. BAT is 5–10 times more vascularized than WAT. A third type of adipose tissue, the beige or brite (brown in white) adipose tissue with paucilocular adipocytes is dispersed in the WAT [64, 65, 66]. Browning of WAT has been suggested under the influence of the hormone irisin, which is produced by the skeletal muscle during exercise [67]. Adipocytes of WAT and beige adipose tissue are predominantly derived from the Myf 5 negative progenitor cells, while adipocytes of BAT are predominantly from Myf 5 positive progenitor cells. Myf 5 or myogenic factor 5 is a gene for transcriptional factor expressed during embryonic myogenesis [68]. Brown and beige AT show anatomical decline with aging and protect from obesity and type 2 diabetes mellitus (T2DM).
Figure 5.
Types of adipose tissue.
Based on the location of the white adipose tissue, it is broadly classified as subcutaneous and visceral (Figure 5). The subcutaneous adipose tissue (SAT) stores excess energy, provides insulation from heat and cold, and functions as an endocrine organ. Visceral adipose tissue (VAT) provides a protective padding around organs. Specialized adipose tissue is associated with the bone marrow, breast, retroorbital adipose tissue, and epicardium [69]. In persons having the same BMI, females tend to have more adipose tissue than males. Females also have more subcutaneous adipose tissue (SAT) compared with males. Localized fat pads, e.g., the synovia are considered as SAT. The SAT of lower trunk and gluteal-thigh region is further organized in two separate layers: the superficial SAT, SSAT (evenly distributed around the circumference of the abdomen), and the deep SAT, DSAT (most of which is located in the posterior half of the abdomen). The SSAT and DSAT are separated by the fascia of Scarpa. SSAT has a higher expression of metabolic regulatory genes, while DSAT has a higher level of expression of inflammatory genes and higher lipolytic activity. Thus, higher volume of DSAT is associated with higher levels of free fatty acids [70].
3.2 Specialized adipose tissue
Bone marrow contains adipose tissue called the marrow adipose tissue (MAT), which increases in amount in periods of calorie restriction, in contrast to adipose tissue present at other sites in the body. Exercise results in decrease in the size of MAT, as well as of the adipocytes present in MAT. Adipocytes of MAT develop from the mesenchymal stem cells.
3.3 Diseases associated with adipose tissue
In some persons there is a variable lack of adipose tissue, which may be generalized or specific (abnormal distribution of adipose tissue). This condition is called lipodystrophy. Lack of sufficient adipose tissue results in increased levels of fatty acids in blood, as they cannot be stored as TGs in the adipocytes. Raised levels of fatty acids cause lipotoxicity, characterized by ectopic fat deposition in the muscle, liver, and pancreas, thus contributing to T2DM [71].
3.3.1 Development of insulin resistance
The mechanism of development of insulin resistance is complicated and is influenced by diverse factors, including the location and type of adipose tissue that increases in mass.
Depending on the location, WAT is further classified into different types (Figure 5) [72, 73]. Excess calorie intake leads to enlargement of adipocytes (hypertrophy) as well as increase in the number of adipocytes (hyperplasia) [74]. The new adipocytes may develop from preadipocytes or from adipocytes of BAT. Adipogenesis through differentiation of progenitor cells to adipocytes occurs through transcription factors such as peroxisome proliferator-activated receptor-γ (PPAR-γ), and CCAAT/enhancer binding protein-α [75]. Increase in the size of the adipocytes is associated with insulin resistance and inflammation. Adipose hypertrophy seen in morbid adiposity results in heterogeneity of cell size within the same depot of adipose tissue, with cell size ranging from 20 microns to 300 microns [76]. Usually, SAT contains more preadipocytes compared with VAT, so adipose hypertrophy is less in SAT [77]. Normal adipose tissue produces adipokines (leptin, adiponectin) that regulate appetite and energy metabolism and cytokines. Pro-inflammatory cytokines include TNF-α, visfatin, resistin, angiotensin II, serum amyloid alpha, plasminogen activator inhibitor, and IL-6, while anti-inflammatory cytokines include apelin, transforming growth factor beta (TGFβ), IL-10, IL-4, IL-13, and IL-1 receptor antagonist (IL-1Ra) [78]. Male hormones promote hypertrophy, while female hormones promote hyperplasia [79]. In lean adipose tissue, the adipose cells are 5–10% of all cells in the tissue; in obese adipose tissue, this number is as high as 60% [80]. Although the life span of adipocytes is about 8 years, increase in size beyond a critical cell size and nutrient excess produce endoplasmic reticulum stress, hypoxia, and death of adipocyte, attracting infiltration of macrophages. This is more in VAT. Adipocyte remnants are absorbed by macrophages, which become activated. In lean adipose tissue, the adipose tissue macrophages (ATMs) are predominantly M2 (anti-inflammatory) type. Pathologic adipose has greater number of M1 ATMs, which are pro-inflammatory and produce cytokines in large amounts after absorbing dead adipocytes. This results in chronic low-grade inflammation and insulin resistance.
In some persons with obesity, excess calories are preferentially stored in SAT, which does not produce inflammation. This type of obesity is also called metabolically healthy obesity (MHO) [81]. In contrast, increase in VAT is associated with abnormal blood lipid profile, i.e., dyslipidemia, insulin resistance, metabolic syndrome, type 2 diabetes, and hypertension. This type of obesity is called metabolically unhealthy obesity (MUHO) and is due to deposition of intraabdominal fat.
Hypertrophic stressed adipocytes are unable to take up free fatty acids, which are therefore diverted to other non-fat-storing organs such as muscle, liver, pancreas, and heart, where they are stored as ectopic fat. This results in impaired glucose uptake by muscle cells, decreased glucose utilization by liver and adipose causing hypertriglyceridemia, hyperglycemia, reduced amounts of HDL cholesterol, increased amounts of LDL and VLDL cholesterol, increased proportion of small, dense LDL particles, and insulin resistance. Products of fatty acid metabolism such as long-chain fatty acyl-Co A, diacyl glycerol (DAG), and ceramide are harmful to cells and aggravate insulin resistance by causing phosphorylation of the serine residues on the insulin receptor substrate (IRS) [82]. In skeletal muscle, lipid can be stored in adipocytes between muscle fibers, or as cytosolic triacylglycerols within the muscle cells (intramyocellular lipids, IMCLs). IMCLs are an adaptive response in endurance athletes and are present in close proximity to mitochondria. Increased IMCL stores in insulin resistance or T2DM is a consequence of raised free fatty acid levels in blood and impaired fatty acid oxidation in the muscle [83]. This may also be due to mitochondrial dysfunction.
Recent evidence suggests the role of leptin resistance and hyperleptinemia of obesity causes production of reactive oxygen species (ROS) and increases oxidative stress, promoting the risk of hypertension, heart disease, and cancer [84, 85, 86]. Endoplasmic reticulum stress, protein tyrosine phosphatase 1B, and suppressor of cytokine 3 (SOC3) signaling mediate leptin resistance and are also involved in insulin resistance [87].
3.3.2 Type 2 diabetes
Insulin resistance in the liver, adipose, and muscles coupled with ectopic fat in the pancreas contributes to hyperglycemia and T2DM. Deposition of ectopic fat in the pancreas is seen in almost two-thirds of patients with obesity. Most of this is due to adipocyte infiltration into pancreatic tissue rather than accumulation of intracellular lipid. Ectopic pancreatic fat is associated with an increased risk of T2DM and cardiovascular disease (CVD). Increased lipolysis and inflammation caused by ectopic pancreatic fat are also reported to promote acute pancreatitis [88].
3.3.3 Fatty liver
Hepatic insulin resistance caused by DAG and ceramide promotes lipotoxicity, ectopic fat deposition, insulin resistance, and steatosis, leading to nonalcoholic fatty liver disease (NAFLD) [89].
3.3.4 Obesity and cardiovascular disease
Excess free fatty acids reaching the heart can be stored as epicardial adipose tissue (EAT), also called pericardial fat (present between the visceral and parietal pericardia), or surrounding the blood vessels (perivascular adipose tissue or PVAT). Although the cardiac muscle uses free fatty acids for obtaining energy, when delivered in excess these fatty acids are stored as ectopic fat in the cardiac myocyte, disrupting its function. Higher levels of LDL and VLDL receptors are expressed in the epicardial tissue from patients with T2DM. The PVAT produces adipokines and many molecules that affect vascular reactivity: monocyte chemotactic protein-1 (MCP-1)], nitric oxide, prostacyclin, and angiotensin II. PVAT present around the thoracic aorta resembles BAT, while the PVAT around the abdominal aorta resembles WAT [90, 91]. Healthy PVAT is largely anti-inflammatory, while dysfunctional PVAT promotes atherosclerosis.
3.3.5 Obesity and cancer
Different types of cancers associated with obesity include breast, endometrial, prostrate, pancreatic, adenocarcinoma of esophagus, colon cancer, meningioma, and cancers of ovary, kidney, thyroid, liver, etc. [92, 93, 94]. Though different mechanisms have been proposed, chronic inflammation is a major factor for cancer initiation and progression. Excess nutrients activate metabolic signaling pathways such as c-Jun N-terminal kinase (JNK), nuclear factor κ B (NFκB), and protein kinase R that may promote development of neoplasm [95, 96]. Synthesis of IGF-1 is stimulated by insulin. IGF-1 promotes tumor growth via the PI3K/Akt/mTOR and the Ras/Raf/MAPK pathways [96]. IL-6, a pro-inflammatory cytokine produced during adipose tissue inflammation, activates the androgen receptor and promotes cell survival and proliferation in prostate cancer [97]. Aromatase, the rate-limiting enzyme of estrogen synthesis, is also stimulated by inflammatory cytokines and PGE2 [98, 99, 100, 101].
Risk of gallstones is increased in obesity. Chronic gall bladder inflammation from gallstones may predispose to cancer of the gall bladder [102]. Similarly, chronic inflammation of hepatitis may increase the risk of liver cancer [103].
Cancer survivorship, including cancer progression, prognosis, recurrence, and quality of life are reported to be worsened by obesity [104, 105]. Obesity is associated with an increased risk of treatment-related lymphedema in breast cancer survivors and incontinence in prostate cancer survivors (treated with radial prostatectomy) [106, 107]. Risk of local recurrence was higher in obese/overweight male patients with stage II or stage III renal cancer [108]. Similarly, obesity increases the risk of mortality in patients with multiple myeloma [109].
3.3.6 Eye diseases associated with obesity
Ocular manifestations of obesity are less known and not well documented. Its association with age-related cataract, glaucoma, age-related maculopathy, and diabetic retinopathy has been reported [110, 111]. Cortical and posterior subcapsular or PSC cataracts have been most consistently associated with obesity. Obesity-induced leptin resistance and hyperlipidemia promote formation of reactive oxygen species, which are involved in cataract formation. Other complications of obesity: insulin resistance, hyperglycemia, diabetes, diabetes, and hypertension (see above) are known to be risk factors for cataract.
Increased retroorbital adipose tissue seen in obesity has been reported to be associated with increased intraocular pressure (IOP) [112, 113]. Raised IOP may be a risk factor for glaucoma. The AREDS (Age-Related Eye Disease Study) Report [114] has reported an association between obesity and age-related macular degeneration. (AMD) Oxidative stress secondary to hyperleptinemia may cause damage to lipids in Bruch membrane and secretion of excessive vascular endothelial growth factor (VEGF), which elicit invasion of neovascularization in Bruch membrane in neovascular AMD [115]. Inflammation may also play a role in AMD development. Diabetic retinopathy, a common complication of T2DM (which is associated with diabetes), can result in loss of vision [116]. Other diseases of the eye that may be associated with obesity include retinal vein occlusion, oculomotor nerve palsy, recurrent lower eyelid entropion, keratoconus, papilledema, floppy eyelid syndrome and benign intracranial hypertension (pseudotumor cerebri) [117, 118, 119, 120, 121].
4. Gut-associated diseases
Besides fatty liver and pancreatitis (discussed above), obesity is associated with increased risk of cholelithiasis (gall bladder stones) and gastroesophageal reflux disease (GERD).
4.1 Cholelithiasis
About 90% gallstones are cholesterol stones while the rest are made of calcium bilirubinate, calcium complexes, mucin glycoproteins, or unconjugated bilirubin. Obesity and metabolic syndrome are two risk factors for the development of cholelithiasis, other factors being genetics, age, gender, parity, and presence of hepatitis C virus infection and chronic kidney disease [122]. Recent study by Su et al. [123] shows that obesity reduces the age of onset of gallstone formation. Energy-dense food such as increased consumption of refined carbohydrates and saturated fats with decreased intake of fiber, and medicines such as estrogen and progesterone can promote cholelithiasis [124]. Rapid weight loss of more than 1.5 kg/week can also promote gallstone formation [125].
4.2 Gastroesophageal reflux disease (GERD)
Heartburn and regurgitation are typical manifestations of GERD. Epidemiologic data show an association of obesity with GERD and Barrett’s esophagus, a condition in which the lower part of the esophagus is damaged by repeated exposure to stomach acid [126, 127].
5. Effect of obesity on reproductive health
Obesity has been shown to cause sub-fecundity and infertility in both sexes [128, 129, 130]. Overweight and obesity result in changes in the hypothalamus-pituitary-gonadal (HPG) axis in both men and women, affecting hormone levels and gametogenesis.
5.1 Reproductive problems in males
Chronic inflammation along with insulin and leptin resistance is associated with increase in adipose tissue (see above), affecting reproductive issues.
5.1.1 Hypogonadism and pseudo-gynecomastia
Insulin resistance may be responsible for obesity-induced hypogonadism in males. Male obesity secondary hypogonadism or MOSH is caused by hyperestrogenism, metabolic endotoxemia, and hyperleptinemia. Hyperestrogenism decreases pituitary secretion of luteinizing hormone through a negative feedback action that impairs the synthesis and production of testosterone from Leydig cells. Hypercaloric diet with excess lipids causes breakdown of the normal leaky gut, facilitating passage of bacterial endotoxin from gut lumen into the blood stream (metabolic endotoxemia). Some animal studies suggest that bacterial endotoxin (Lipopolysaccharides-LPS) reduces testicular function by binding toll-like receptor 4 (TLR4) on Leydig cells, stimulating production of inflammatory cytokines [131, 132, 133, 134].
Obesity is associated with elevated levels of leptin and leptin resistance. Leptin prevents the neuropeptide Y (NPY) neurons from inhibiting the release of GnRH. Leptin resistance results in reduced release of GnRH, FSH, and LH and impairs spermatogenesis [135].
Kisspeptin, a hypothalamic peptide encoded by the KiSS1 gene, is an important neuromodulator involved in HPG axis and fertility control. Most kisspeptin cells are localized at the hypothalamic level in humans. Kisspeptin and its G-protein-coupled receptor (KISS 1R or GPR-54) increase the delivery of GnRH into portal circulation, resulting in enhanced secretion of LH and FSH from the anterior pituitary. Decreased endogenous kisspeptin secretion is seen in obesity-related hypogonadotropic hypogonadism (HH) [136, 137, 138, 139]. Increased leptin levels are associated with decreased total and free testosterone levels in males.
Hyperinsulinemia results in decreased production of sex hormone binding globulin (SHBG) by the hepatocytes, causing increased availability of free testosterone for reaction by aromatase in the adipose tissue. Aromatase converts testosterone to estradiol [140], further decreasing testosterone level with increase in estrogen level. This may result in pseudo-gynecomastia, with excess adipose deposition in breast area [134]. Sleep apnea associated with obesity disrupts the nocturnal rise in testosterone [134].
High waist circumference is associated with erectile dysfunction due to atherogenic effect on peripheral vasculature [141]. Low ejaculatory volume and oligo-zoospermia have been noted in males with increased BMI and waist circumference [142]. Increased testicular heat, elevated inflammatory mediators, and increased presence of reactive oxygen species in men with obesity affect the quality of sperms [143].
5.2 Reproductive problems in females
Earlier onset of menarche has been reported in adolescent females with overweight or obesity, compared with their normal-weight counterparts. The association of obesity with menstrual disorders, infertility, and recurrent miscarriages was recognized early [144, 145].
Insulin resistance promotes hyperandrogenemia and decreases the level of steroid hormone binding globulin (SHBG) resulting in elevated levels of free testosterone (discussed above). Aromatization of testosterone to estrogens by aromatase in the adipose tissue suppresses the release of gonadotrophin from the pituitary [140]. Elevated levels of leptin impair follicle development, ovulation, and oocyte maturation in women with obesity [146, 147].
5.2.1 Polycystic ovarian syndrome (PCOS)
This hormonal disorder is one of the most common endocrine disorder in premenopausal women, is also associated with obesity, metabolic syndrome, and T2DM. Irregular periods, anovulatory cycles, oligo-amenorrhea, excess androgen, hirsutism, and polycystic ovaries are the main characteristics of PCOS [148, 149]. Most women with PCOS have elevated levels of plasma free fatty acids, are insulin resistant, and have compensatory hyperinsulinemia. High levels of free fatty acids induce mitochondrial dysfunction, inflammation, oxidative stress, and immune disorders [150]. High levels of plasma free fatty acids cause increased synthesis of androgens in the ovary as well as in the zona reticularis of the adrenal gland. Insulin stimulates androgenesis by stimulating P450c17 activity in zona reticularis of the adrenal gland to produce DHEA and androstenedione [151]. Hyperinsulinemia causes decreased expression of SHBG by hepatocytes (see above), thus further increasing free testosterone levels. Aromatase (CYP19A1) in adipocytes as well as in the tissue of endometriosis converts androgens to estradiol, which inhibits the secretion of gonadotropin releasing hormone, resulting in decreased release FSH and LH from the pituitary. This affects maturation of follicles, production of estrogen, ovulation, maintenance of function of corpus luteum.
Women with PCOS may have problems in conceiving and increased risk of gestational diabetes and miscarriage or premature birth. Impairment of the hypothalamus-pituitary-gonadal (HPG) axis and follicular environment caused by obesity results in fertility problems, miscarriages, and complications in pregnancy.
5.2.2 Anovulation and quality of oocyte
Ovulation disorders account for at least 30% cases of infertility. Menstrual cycle without the release of ovum is called anovulatory cycle. Women with obesity have higher rates of anovulatory menstrual cycles [152, 153], the exact mechanism of which is not known. Common causes of anovulation include hyperandrogenism (as in PCOS, congenital adrenal hyperplasia, androgen-producing tumors), hyperprolactinemia, anorexia, excessive strenuous exercise, stress, thyroid dysfunction, primary pituitary dysfunction, premature ovarian failure, and certain medications. Obesity and strenuous exercise are known to alter profiles of insulin and adiponectin, thus impairing fertility in women. Obese women remain sub-fertile even in the absence of ovulatory dysfunction [154, 155].
Obesity affects the quality of sperm, ovum, embryo, placenta, and the uterine environment. The competence of the oocyte is defined in terms of its ability to become fertilized and support embryo development. Oocyte competence may be influenced by obesity. Machtinger et al. [156] have shown that oocytes from women with obesity are smaller in size, have more abnormal spindles and chromosome misalignment than those from women with normal BMI. Negative outcomes for women undergoing in vitro fertilization (IVF) are more common in women with higher BMI, due to the poor oocyte quality, lower preimplantation rate, and uterine receptivity [157]. Decreased rate of conception, infertility, early pregnancy loss, and reduced success of assisted reproductive technology (ART) have been reported in females with obesity [158].
High serum levels of insulin, insulin resistance, high levels of glucose, lactate, triglycerides, and C-reactive protein in the follicular fluid have a negative impact on oocyte maturation.
Mitochondria of the oocyte must be fully functional, as ATP generated by them are required for oocyte maturation and blastocyst formation. High levels of fuel molecules (glucose, free fatty acids, triglycerides, and cholesterol) in environment increase intracellular lipid accumulation and cause damage to the endoplasmic reticulum and mitochondria. Mice fed on high-fat diet have oocytes with accumulated lipid, increased reactive oxygen species (ROS), and have altered structure of mitochondria [159].
5.2.3 Endometrial hyperplasia
Abnormally thickened lining of the uterus due to disordered proliferation of endometrial glands or endometrial hyperplasia is caused by excess androgen with a relative deficiency of progesterone [160]. Untreated endometrial hyperplasia may develop into endometrial cancer [161]. Endogenous estrogen excess may occur in anovulatory cycles (during perimenopause or PCOS), obesity, and estrogen secreting tumors of the ovary. The most common symptom of endometrial hyperplasia is abnormal uterine bleeding.
5.3 Obesity-related complications in pregnancy
Women with obesity have a higher risk of miscarriage, gestational diabetes, preeclampsia, premature delivery, cesarean section, and post-partum hemorrhage. Maternal obesity with poor glycemic control may result in fetal macrosomia and associated complications. Twenty percent less detection of fetal anomalies has been reported in women with obesity [162].
5.3.1 Risk of miscarriage
A Danish cohort study [163] involving more than 5000 women reported a hazard ratio for miscarriage of 1.23 for women with obesity conceiving spontaneously. Risk of miscarriage is higher in women with obesity who conceive with IVF, even when using donor eggs from women with normal BMI.
5.3.2 Gestational diabetes
Schummers et al. [164] studied 226,000 singleton pregnancies in British Columbia. They have reported an incidence of gestational diabetes of 7.9%. The risk of gestational diabetes was doubled with a BMI > 30, and more than tripled at BMI > 40 kg/m2.
5.3.3 Risk of preeclampsia
Women with overweight have double the risk of preeclampsia, while women with obesity have triple the risk, compared with women with normal BMI [164, 165]. Increased physical activity during pregnancy may reduce the risk of both gestational diabetes and preeclampsia.
5.3.4 Preterm labor
Obesity has been shown to increase the risk of preterm delivery [165, 166]. This may be due to increased levels of circulating cytokines and inflammatory proteins in women with obesity.
5.3.5 Cesarean section
The rate of Cesarean section increases with increase in maternal BMI [165, 167]. There is also an increased risk of wound infection, dehiscence, post-partum hemorrhage, and deep vein thrombosis. Duration of labor is longer in women with obesity. There is an increased risk of fetal distress, instrumental delivery, and shoulder dystocia in women with obesity.
6. Economic consequences of obesity
Obesity is a risk factor for various diseases (see above). Expenses on medicine, loss of pay due to absence from work caused by illness, reduced job opportunities, etc., lead to constraint on family budget [168].
6.1 Direct expenses
These include the medical expenses on obesity-related diseases. Expense on medicines for hypertension, type 2 diabetes, dyslipidemia, kidney diseases, stroke; and medical expenses incurred on hospitalization for various conditions affect the family budget as well as the budget of the country [169].
6.2 Indirect expenses
Absence from work due to disease results in decreased pay and early mortality affects the family income. Kjellberg et al. [170] report a 2% decrease in income, 3% increase in social transfer payments, and a 4% increase in healthcare costs per BMI point above 30. Thus, the indirect costs constitute the greatest proportion of total costs associated with obesity. Lee et al. [171] have reported that women with higher BMI are 0.33 times less likely to have service jobs, earn 9% lower monthly wages, and are half as likely to have jobs with bonuses compared with those with normal BMI.
7. Mental and social issues
Obesity is considered a social stigma in most societies. People with obesity are considered responsible for their condition and are often the victims of teasing and bullying, at all ages, from preschool through adolescence to adulthood [172, 173, 174, 175, 176].
7.1 Bullying
Bullying is intentional unprovoked aggression that may be physical (hitting, shoving), mental (name calling, spreading rumors, social exclusion, fat shaming on social media) or both, which causes harm to the victim. It involves an imbalance of physical or psychological power. Weight-based victimization is more common at younger age, but may be observed in adults also [177]. It has been noted that pre-adolescent or adolescent boys with overweight or obesity who are stronger than their peer may show bullying behavior, victimizing those who are physically weaker than them [178].
7.2 Binge eating
Binge eating disorder (BED) is a type of disordered eating in which the individual consumes a relatively large amount of food in a short span of time, compared with other people of the same age, gender, and weight. BED affects 1–3% of the general population. People with BED are 3–6 times more likely to be overweight or obese than persons without eating disorders [179]. Around 30% persons with BED report a history of childhood obesity [180].
7.3 Depression
Meta-analysis conducted by Luppino et al. [181] shows a reciprocal link between depression and obesity. Obesity increases the risk of depression, and depression is predictive of developing obesity. Both obesity and depression are common and both are risk factors for cardiovascular diseases [182]. Depression is also an important cause of premature mortality, primarily due to suicide.
8. Quality of life and mortality
Obesity and the associated diseases affect the quality of life and influence the length of life span [183].
8.1 Decreased quality of life
Health-related quality of life encompasses physical, mental, and social health and is influenced by factors such as socioeconomic status, culture, and environment of the person concerned. The degree of obesity is inversely proportional with the quality of life, as persons with higher BMI values are more likely to have obesity-associated diseases [184].
8.2 Risk of mortality
At least 2.8 million people die annually as a consequence of being overweight or obese. Many complications of obesity are mentioned above that deteriorate the quality of life and may promote early death. Most of the deaths are a direct consequence of cardiovascular problems or cancer [185].
9. Conclusion
Obesity is a condition that can compromise health and is closely associated with various medical conditions caused by increased body mass, metabolic derangement, psychological effects, or economic or social aspects. Awareness about the causes and consequences of obesity should be created among the general public so that persons with obesity may receive timely care with empathy.
Conflict of interest
None.
\n',keywords:"obesity, metabolic syndrome, insulin resistance, type 2 diabetes mellitus, obesity-related health",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/81662.pdf",chapterXML:"https://mts.intechopen.com/source/xml/81662.xml",downloadPdfUrl:"/chapter/pdf-download/81662",previewPdfUrl:"/chapter/pdf-preview/81662",totalDownloads:9,totalViews:0,totalCrossrefCites:0,dateSubmitted:"January 1st 2022",dateReviewed:"March 31st 2022",datePrePublished:"May 5th 2022",datePublished:null,dateFinished:"May 5th 2022",readingETA:"0",abstract:"Increase in body weight due to excess accumulation of fat can lead to obesity, a chronic, progressive, relapsing, multifactorial, neurobehavioral disease caused by adipose tissue dysfunction. Obesity often results in adverse biomechanical, metabolic, psychosocial, and economic consequences. In humans, effects of obesity are diverse and interrelated and can be classified on the basis of organ/organ system affected. Physical problems associated with weight gain are musculoskeletal problems, respiratory problems, lower limb venous diseases, skin-related problems, and stress incontinence in females. Metabolic conditions caused by obesity include gout, insulin resistance and metabolic syndrome, type 2 diabetes mellitus, certain cancers, CVD, fatty liver, gall bladder disease, etc. Obesity is known to affect the reproductive health. Hypogonadism and pseudo-gynecomastia are more common in males with obesity. Decreased fertility is reported in both the sexes. Polycystic ovarian syndrome (PCOS), anovulation, endometrial hyperplasia, and increased risk of complications in pregnancy have been reported in females. Persons with obesity have increased healthcare expense, pay more insurance premium, take more illness-related leaves, thus suffering economic loss due to their condition. Persons with obesity are often considered legitimate targets for teasing and bullying, which may cause social isolation, depression, eating disorders, etc. Obesity affects the morbidity and mortality. This chapter deals with the different consequences of obesity.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/81662",risUrl:"/chapter/ris/81662",signatures:"Indu Saxena, Amar Preet Kaur, Suwarna Suman, Abhilasha, Prasenjit Mitra, Praveen Sharma and Manoj Kumar",book:{id:"11022",type:"book",title:"Weight Management - Challenges and Opportunities",subtitle:null,fullTitle:"Weight Management - Challenges and Opportunities",slug:null,publishedDate:null,bookSignature:"Dr. Hassan M. Heshmati",coverURL:"https://cdn.intechopen.com/books/images_new/11022.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80355-187-6",printIsbn:"978-1-80355-186-9",pdfIsbn:"978-1-80355-188-3",isAvailableForWebshopOrdering:!0,editors:[{id:"313921",title:"Dr.",name:"Hassan M.",middleName:null,surname:"Heshmati",slug:"hassan-m.-heshmati",fullName:"Hassan M. Heshmati"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Physical problems associated with obesity",level:"1"},{id:"sec_2_2",title:"2.1 Musculoskeletal disorders",level:"2"},{id:"sec_2_3",title:"2.1.1 Decreased functional mobility",level:"3"},{id:"sec_3_3",title:"2.1.2 Loss of balance",level:"3"},{id:"sec_4_3",title:"2.1.3 Osteoarthritis (OA)",level:"3"},{id:"sec_5_3",title:"2.1.4 Gout",level:"3"},{id:"sec_7_2",title:"2.2 Respiratory problems",level:"2"},{id:"sec_7_3",title:"2.2.1 Reduced compliance of lungs",level:"3"},{id:"sec_8_3",title:"2.2.2 Obesity and asthma",level:"3"},{id:"sec_9_3",title:"2.2.3 Obstructive sleep apnea (OSA)",level:"3"},{id:"sec_11_2",title:"2.3 Lower limb venous diseases",level:"2"},{id:"sec_12_2",title:"2.4 Skin problems",level:"2"},{id:"sec_12_3",title:"2.4.1 Mechanical causes of dermatologic manifestations associated with obesity",level:"3"},{id:"sec_13_3",title:"2.4.2 Obesity-related endocrine disorders of skin",level:"3"},{id:"sec_14_3",title:"2.4.3 Increased risk of skin infections",level:"3"},{id:"sec_15_3",title:"2.4.4 Obesity-associated immune disorders affecting skin",level:"3"},{id:"sec_17_2",title:"2.5 Urinary incontinence (UI)",level:"2"},{id:"sec_19",title:"3. Metabolic disorders associated with obesity",level:"1"},{id:"sec_19_2",title:"3.1 Organization of the adipose tissue",level:"2"},{id:"sec_20_2",title:"3.2 Specialized adipose tissue",level:"2"},{id:"sec_21_2",title:"3.3 Diseases associated with adipose tissue",level:"2"},{id:"sec_21_3",title:"3.3.1 Development of insulin resistance",level:"3"},{id:"sec_22_3",title:"3.3.2 Type 2 diabetes",level:"3"},{id:"sec_23_3",title:"3.3.3 Fatty liver",level:"3"},{id:"sec_24_3",title:"3.3.4 Obesity and cardiovascular disease",level:"3"},{id:"sec_25_3",title:"3.3.5 Obesity and cancer",level:"3"},{id:"sec_26_3",title:"3.3.6 Eye diseases associated with obesity",level:"3"},{id:"sec_29",title:"4. Gut-associated diseases",level:"1"},{id:"sec_29_2",title:"4.1 Cholelithiasis",level:"2"},{id:"sec_30_2",title:"4.2 Gastroesophageal reflux disease (GERD)",level:"2"},{id:"sec_32",title:"5. Effect of obesity on reproductive health",level:"1"},{id:"sec_32_2",title:"5.1 Reproductive problems in males",level:"2"},{id:"sec_32_3",title:"5.1.1 Hypogonadism and pseudo-gynecomastia",level:"3"},{id:"sec_34_2",title:"5.2 Reproductive problems in females",level:"2"},{id:"sec_34_3",title:"5.2.1 Polycystic ovarian syndrome (PCOS)",level:"3"},{id:"sec_35_3",title:"5.2.2 Anovulation and quality of oocyte",level:"3"},{id:"sec_36_3",title:"5.2.3 Endometrial hyperplasia",level:"3"},{id:"sec_38_2",title:"5.3 Obesity-related complications in pregnancy",level:"2"},{id:"sec_38_3",title:"5.3.1 Risk of miscarriage",level:"3"},{id:"sec_39_3",title:"5.3.2 Gestational diabetes",level:"3"},{id:"sec_40_3",title:"5.3.3 Risk of preeclampsia",level:"3"},{id:"sec_41_3",title:"5.3.4 Preterm labor",level:"3"},{id:"sec_42_3",title:"5.3.5 Cesarean section",level:"3"},{id:"sec_45",title:"6. Economic consequences of obesity",level:"1"},{id:"sec_45_2",title:"6.1 Direct expenses",level:"2"},{id:"sec_46_2",title:"6.2 Indirect expenses",level:"2"},{id:"sec_48",title:"7. Mental and social issues",level:"1"},{id:"sec_48_2",title:"7.1 Bullying",level:"2"},{id:"sec_49_2",title:"7.2 Binge eating",level:"2"},{id:"sec_50_2",title:"7.3 Depression",level:"2"},{id:"sec_52",title:"8. Quality of life and mortality",level:"1"},{id:"sec_52_2",title:"8.1 Decreased quality of life",level:"2"},{id:"sec_53_2",title:"8.2 Risk of mortality",level:"2"},{id:"sec_55",title:"9. Conclusion",level:"1"},{id:"sec_59",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Wang T, Hung CCY, Randall DJ. The comparative physiology of food deprivation: From feast to famine. Annual Review of Physiology. 2006;68:223-225'},{id:"B2",body:'Van Ginneken VJT, Antonissen E, Muller UK, Booms R, Eding E, Verreth J, et al. 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Body-mass index and mortality among 1.46 million white adults. NEJM. 2010;363(23):2211-2219'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Indu Saxena",address:"indu.saxena@rediffmail.com",affiliation:'
Department of Biochemistry, All India Institute of Medical Sciences Gorakhpur, India
Maharshi Vashishtha Autonomous State Medical College, India
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The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.
",metaTitle:"Our story",metaDescription:"The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.",metaKeywords:null,canonicalURL:"/page/our-story",contentRaw:'[{"type":"htmlEditorComponent","content":"
We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
\\n\\n
In the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
\\n\\n
The IntechOpen timeline
\\n\\n
2004
\\n\\n
\\n\\t
Intech Open is founded in Vienna, Austria, by Alex Lazinica and Vedran Kordic, two PhD students, and their first Open Access journals and books are published.
\\n\\t
Alex and Vedran launch the first Open Access, peer-reviewed robotics journal and IntechOpen’s flagship publication, the International Journal of Advanced Robotic Systems (IJARS).
\\n
\\n\\n
2005
\\n\\n
\\n\\t
IntechOpen publishes its first Open Access book: Cutting Edge Robotics.
\\n
\\n\\n
2006
\\n\\n
\\n\\t
IntechOpen publishes a special issue of IJARS, featuring contributions from NASA scientists regarding the Mars Exploration Rover missions.
\\n
\\n\\n
2008
\\n\\n
\\n\\t
Downloads milestone: 200,000 downloads reached
\\n
\\n\\n
2009
\\n\\n
\\n\\t
Publishing milestone: the first 100 Open Access STM books are published
\\n
\\n\\n
2010
\\n\\n
\\n\\t
Downloads milestone: one million downloads reached
\\n\\t
IntechOpen expands its book publishing into a new field: medicine.
\\n
\\n\\n
2011
\\n\\n
\\n\\t
Publishing milestone: More than five million downloads reached
\\n\\t
IntechOpen publishes 1996 Nobel Prize in Chemistry winner Harold W. Kroto’s “Strategies to Successfully Cross-Link Carbon Nanotubes”. Find it here.
\\n\\t
IntechOpen and TBI collaborate on a project to explore the changing needs of researchers and the evolving ways that they discover, publish and exchange information. The result is the survey “Author Attitudes Towards Open Access Publishing: A Market Research Program”.
\\n\\t
IntechOpen hosts SHOW - Share Open Access Worldwide; a series of lectures, debates, round-tables and events to bring people together in discussion of open source principles, intellectual property, content licensing innovations, remixed and shared culture and free knowledge.
\\n
\\n\\n
2012
\\n\\n
\\n\\t
Publishing milestone: 10 million downloads reached
\\n\\t
IntechOpen holds Interact2012, a free series of workshops held by figureheads of the scientific community including Professor Hiroshi Ishiguro, director of the Intelligent Robotics Laboratory, who took the audience through some of the most impressive human-robot interactions observed in his lab.
\\n
\\n\\n
2013
\\n\\n
\\n\\t
IntechOpen joins the Committee on Publication Ethics (COPE) as part of a commitment to guaranteeing the highest standards of publishing.
\\n
\\n\\n
2014
\\n\\n
\\n\\t
IntechOpen turns 10, with more than 30 million downloads to date.
\\n\\t
IntechOpen appoints its first Regional Representatives - members of the team situated around the world dedicated to increasing the visibility of our authors’ published work within their local scientific communities.
\\n
\\n\\n
2015
\\n\\n
\\n\\t
Downloads milestone: More than 70 million downloads reached, more than doubling since the previous year.
\\n\\t
Publishing milestone: IntechOpen publishes its 2,500th book and 40,000th Open Access chapter, reaching 20,000 citations in Thomson Reuters ISI Web of Science.
\\n\\t
40 IntechOpen authors are included in the top one per cent of the world’s most-cited researchers.
\\n\\t
Thomson Reuters’ ISI Web of Science Book Citation Index begins indexing IntechOpen’s books in its database.
\\n
\\n\\n
2016
\\n\\n
\\n\\t
IntechOpen is identified as a world leader in Simba Information’s Open Access Book Publishing 2016-2020 report and forecast. IntechOpen came in as the world’s largest Open Access book publisher by title count.
\\n
\\n\\n
2017
\\n\\n
\\n\\t
Downloads milestone: IntechOpen reaches more than 100 million downloads
\\n\\t
Publishing milestone: IntechOpen publishes its 3,000th Open Access book, making it the largest Open Access book collection in the world
We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
\n\n
In the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
\n\n
The IntechOpen timeline
\n\n
2004
\n\n
\n\t
Intech Open is founded in Vienna, Austria, by Alex Lazinica and Vedran Kordic, two PhD students, and their first Open Access journals and books are published.
\n\t
Alex and Vedran launch the first Open Access, peer-reviewed robotics journal and IntechOpen’s flagship publication, the International Journal of Advanced Robotic Systems (IJARS).
\n
\n\n
2005
\n\n
\n\t
IntechOpen publishes its first Open Access book: Cutting Edge Robotics.
\n
\n\n
2006
\n\n
\n\t
IntechOpen publishes a special issue of IJARS, featuring contributions from NASA scientists regarding the Mars Exploration Rover missions.
\n
\n\n
2008
\n\n
\n\t
Downloads milestone: 200,000 downloads reached
\n
\n\n
2009
\n\n
\n\t
Publishing milestone: the first 100 Open Access STM books are published
\n
\n\n
2010
\n\n
\n\t
Downloads milestone: one million downloads reached
\n\t
IntechOpen expands its book publishing into a new field: medicine.
\n
\n\n
2011
\n\n
\n\t
Publishing milestone: More than five million downloads reached
\n\t
IntechOpen publishes 1996 Nobel Prize in Chemistry winner Harold W. Kroto’s “Strategies to Successfully Cross-Link Carbon Nanotubes”. Find it here.
\n\t
IntechOpen and TBI collaborate on a project to explore the changing needs of researchers and the evolving ways that they discover, publish and exchange information. The result is the survey “Author Attitudes Towards Open Access Publishing: A Market Research Program”.
\n\t
IntechOpen hosts SHOW - Share Open Access Worldwide; a series of lectures, debates, round-tables and events to bring people together in discussion of open source principles, intellectual property, content licensing innovations, remixed and shared culture and free knowledge.
\n
\n\n
2012
\n\n
\n\t
Publishing milestone: 10 million downloads reached
\n\t
IntechOpen holds Interact2012, a free series of workshops held by figureheads of the scientific community including Professor Hiroshi Ishiguro, director of the Intelligent Robotics Laboratory, who took the audience through some of the most impressive human-robot interactions observed in his lab.
\n
\n\n
2013
\n\n
\n\t
IntechOpen joins the Committee on Publication Ethics (COPE) as part of a commitment to guaranteeing the highest standards of publishing.
\n
\n\n
2014
\n\n
\n\t
IntechOpen turns 10, with more than 30 million downloads to date.
\n\t
IntechOpen appoints its first Regional Representatives - members of the team situated around the world dedicated to increasing the visibility of our authors’ published work within their local scientific communities.
\n
\n\n
2015
\n\n
\n\t
Downloads milestone: More than 70 million downloads reached, more than doubling since the previous year.
\n\t
Publishing milestone: IntechOpen publishes its 2,500th book and 40,000th Open Access chapter, reaching 20,000 citations in Thomson Reuters ISI Web of Science.
\n\t
40 IntechOpen authors are included in the top one per cent of the world’s most-cited researchers.
\n\t
Thomson Reuters’ ISI Web of Science Book Citation Index begins indexing IntechOpen’s books in its database.
\n
\n\n
2016
\n\n
\n\t
IntechOpen is identified as a world leader in Simba Information’s Open Access Book Publishing 2016-2020 report and forecast. IntechOpen came in as the world’s largest Open Access book publisher by title count.
\n
\n\n
2017
\n\n
\n\t
Downloads milestone: IntechOpen reaches more than 100 million downloads
\n\t
Publishing milestone: IntechOpen publishes its 3,000th Open Access book, making it the largest Open Access book collection in the world
\n
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Shohel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"768",title:"Petroleum Engineering",slug:"engineering-energy-engineering-petroleum-engineering",parent:{id:"117",title:"Energy Engineering",slug:"engineering-energy-engineering"},numberOfBooks:5,numberOfSeries:0,numberOfAuthorsAndEditors:106,numberOfWosCitations:115,numberOfCrossrefCitations:118,numberOfDimensionsCitations:234,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"768",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"7609",title:"Enhanced Oil Recovery Processes",subtitle:"New Technologies",isOpenForSubmission:!1,hash:"62359d9c21b76f899be04fa0f8b46668",slug:"enhanced-oil-recovery-processes-new-technologies",bookSignature:"Ariffin Samsuri",coverURL:"https://cdn.intechopen.com/books/images_new/7609.jpg",editedByType:"Edited by",editors:[{id:"120519",title:"Prof.",name:"Ariffin",middleName:null,surname:"Samsuri",slug:"ariffin-samsuri",fullName:"Ariffin Samsuri"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7314",title:"Exploitation of Unconventional Oil and Gas Resources",subtitle:"Hydraulic Fracturing and Other Recovery and Assessment Techniques",isOpenForSubmission:!1,hash:"2eba15587cac74206f978e72a0cef2f9",slug:"exploitation-of-unconventional-oil-and-gas-resources-hydraulic-fracturing-and-other-recovery-and-assessment-techniques",bookSignature:"Kenneth Imo-Imo Eshiet",coverURL:"https://cdn.intechopen.com/books/images_new/7314.jpg",editedByType:"Edited by",editors:[{id:"195037",title:"Dr.",name:"Kenneth Imo-Imo Israel",middleName:null,surname:"Eshiet",slug:"kenneth-imo-imo-israel-eshiet",fullName:"Kenneth Imo-Imo Israel Eshiet"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6466",title:"Shale Gas",subtitle:"New Aspects and Technologies",isOpenForSubmission:!1,hash:"02763c6398f049c222acf6a774dd38ee",slug:"shale-gas-new-aspects-and-technologies",bookSignature:"Ali Al-Juboury",coverURL:"https://cdn.intechopen.com/books/images_new/6466.jpg",editedByType:"Edited by",editors:[{id:"58570",title:"Prof.",name:"Ali",middleName:"Ismail",surname:"Al-Juboury",slug:"ali-al-juboury",fullName:"Ali Al-Juboury"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5811",title:"Recent Insights in Petroleum Science and Engineering",subtitle:null,isOpenForSubmission:!1,hash:"33b7777178f4a179ba475e3e15405427",slug:"recent-insights-in-petroleum-science-and-engineering",bookSignature:"Mansoor Zoveidavianpoor",coverURL:"https://cdn.intechopen.com/books/images_new/5811.jpg",editedByType:"Edited by",editors:[{id:"92105",title:"Dr.",name:"Mansoor",middleName:null,surname:"Zoveidavianpoor",slug:"mansoor-zoveidavianpoor",fullName:"Mansoor Zoveidavianpoor"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4751",title:"Storage Stability of Fuels",subtitle:null,isOpenForSubmission:!1,hash:"bc73beb5dc74410e15c8ee19ee4de722",slug:"storage-stability-of-fuels",bookSignature:"Krzysztof Biernat",coverURL:"https://cdn.intechopen.com/books/images_new/4751.jpg",editedByType:"Edited by",editors:[{id:"155009",title:"Prof.",name:"Krzysztof",middleName:null,surname:"Biernat",slug:"krzysztof-biernat",fullName:"Krzysztof Biernat"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"3",chapterContentType:"chapter",authoredCaption:"Authored by"}}],booksByTopicTotal:5,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"58250",doi:"10.5772/intechopen.72207",title:"Microbial Bioremediation of Petroleum Hydrocarbon– Contaminated Marine Environments",slug:"microbial-bioremediation-of-petroleum-hydrocarbon-contaminated-marine-environments",totalDownloads:5105,totalCrossrefCites:20,totalDimensionsCites:38,abstract:"Petroleum pollution has become a serious environmental problem, which can cause harmful damage to the environment and human health. This pollutant is introduced into the environment from both natural and anthropogenic sources. Various physicochemical and biological treatments were developed for the cleanup of contaminated environments. However, bioremediation is based on the metabolic capabilities of microorganisms, and it is considered as the most basic and reliable way to eliminate contaminants, particularly petroleum and its recalcitrant compounds. It is more effective alternative comparing to classical remediation techniques. A high diversity of potential hydrocarbon degrader’s microorganisms was reported, and bacteria constitute the most abundant group, which has been well studied for hydrocarbon degradation. Several bioremediation approaches through bioaugmentation or/and biostimulation have been successfully applied. The interest on the optimizing of different parameters to achieve successful bioremediation technologies has been increased. In this chapter, we summarize the diversity and the hydrocarbon degradation potential of microorganism involved in the remediation of contaminated environments. We also present an overview of the efficient bioremediation strategies used for the decontamination of polluted marine environments.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Mouna Mahjoubi, Simone Cappello, Yasmine Souissi, Atef Jaouani\nand Ameur Cherif",authors:[{id:"107040",title:"Dr.",name:"Simone",middleName:null,surname:"Cappello",slug:"simone-cappello",fullName:"Simone Cappello"},{id:"219462",title:"Dr.",name:"Mouna",middleName:null,surname:"Mahjoubi",slug:"mouna-mahjoubi",fullName:"Mouna Mahjoubi"},{id:"223935",title:"Dr.",name:"Yasmine",middleName:null,surname:"Souissi",slug:"yasmine-souissi",fullName:"Yasmine Souissi"},{id:"223936",title:"Dr.",name:"Ameur",middleName:null,surname:"Cherif",slug:"ameur-cherif",fullName:"Ameur Cherif"}]},{id:"57237",doi:"10.5772/intechopen.71163",title:"Analytical Methods for Polycyclic Aromatic Hydrocarbons and their Global Trend of Distribution in Water and Sediment: A Review",slug:"analytical-methods-for-polycyclic-aromatic-hydrocarbons-and-their-global-trend-of-distribution-in-wa",totalDownloads:4424,totalCrossrefCites:21,totalDimensionsCites:34,abstract:"Polycyclic aromatic hydrocarbons (PAHs) are major organic pollutants in the environment, which are toxic to humans and biota, given their carcinogenic, mutagenic and teratogenic nature. In this chapter, we carried out an overview of the sources and toxicity of PAHs, their common analytical methods of determination in the water and sediment samples, and also their global trend of distribution, with a view to provide baseline guidance for relevant control authorities. The choice methods for determining these contaminants are high-performance liquid chromatography (HPLC) with UV/fluorescence detectors and GC/MS. Mass spectrometer coupled with GC is preferred because it offers robust identification of the analyte compounds both by retention time and mass spectrum, with additional structural information. Results collated revealed an extensive distribution of PAHs with total mean concentrations ranging from 0.0003 to 42,350 μg/L in water and 0 to 1.266 × 109 μg/kg (dw) in the sediment. PAHs in the two environmental matrices were much higher in the regions with intense oil exploration, shipping and industrial activities. It is therefore necessary to regularly monitor their levels in the aquatic environment, so as to provide mitigation options that will prevent risk to humans and aquatic animals.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Abiodun Olagoke Adeniji, Omobola Oluranti Okoh and Anthony\nIfeanyi Okoh",authors:[{id:"219919",title:"Dr.",name:"Abiodun",middleName:"Olagoke",surname:"Adeniji",slug:"abiodun-adeniji",fullName:"Abiodun Adeniji"},{id:"219920",title:"Prof.",name:"Omobola",middleName:null,surname:"Okoh",slug:"omobola-okoh",fullName:"Omobola Okoh"},{id:"219921",title:"Prof.",name:"Anthony",middleName:null,surname:"Okoh",slug:"anthony-okoh",fullName:"Anthony Okoh"}]},{id:"56472",doi:"10.5772/intechopen.70093",title:"Drilling Fluids for Deepwater Fields: An Overview",slug:"drilling-fluids-for-deepwater-fields-an-overview",totalDownloads:2689,totalCrossrefCites:11,totalDimensionsCites:16,abstract:"The increasing oil demand around the world along with the depletion of onshore and shallow water oil reserves have forced the oil companies moving into the development of deepwater subsea hydrocarbon reservoirs. Drilling fluids play a key role in all drilling operations, but they get a greater relevance in deepwater environments where the technological challenges of drilling at these extreme conditions generate significant operational risks as well as very high costs during the development of this kind of fields. The operational issues and concerns related to the drilling fluid design and application for deepwater fields are generally well known: narrow pore/fracture pressure gradient margins, wellbore stability, clay swelling, gas hydrates formation, formation damage, salt formations, lost circulation, stuck pipe, cuttings transport and environmental and safety aspects. Therefore, the present chapter aims to give an overview on the main challenges and research related to drilling fluid design and application for deepwater fields through the revision of the state of the art of the current and innovative technological solutions reported in literature.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Luis Alberto Alcázar-Vara and Ignacio Ramón Cortés-Monroy",authors:[{id:"149837",title:"Dr.",name:"Luis A.",middleName:null,surname:"Alcazar-Vara",slug:"luis-a.-alcazar-vara",fullName:"Luis A. Alcazar-Vara"},{id:"202407",title:"MSc.",name:"Ignacio R.",middleName:null,surname:"Cortés-Monroy",slug:"ignacio-r.-cortes-monroy",fullName:"Ignacio R. Cortés-Monroy"}]},{id:"56887",doi:"10.5772/intechopen.70092",title:"Petroleum Source Rocks Characterization and Hydrocarbon Generation",slug:"petroleum-source-rocks-characterization-and-hydrocarbon-generation",totalDownloads:7884,totalCrossrefCites:6,totalDimensionsCites:15,abstract:"This chapter is proposed to give the principal learning on the application of the formation of petroleum source rocks and hydrocarbon generation to exploration activities. The evaluation of petroleum source rocks and hydrocarbon generation is a very important skill for explorationists to define the location and type of petroleum prospects in a region. In this chapter, subsurface samples from case study (Sayun-Masilah basin) were used to determine the source rock characteristics and petroleum generative potentials of prospective source rocks. Qualitative and quantitative evaluation of the source rock in this basin was done by means of geochemical and geophysical approaches for four rock units. It is clear that Madbi Formation is considered the main source, in which the organic carbon content reached up to more than 5.2 wt%. The types of organic matter from rock-eval pyrolysis data indicated that type I kerogen is the main type, in association with type II, and a mixture of types II and III kerogens. The study of the different maturation parameters obtained from rock-eval pyrolysis, such as Tmax and vitrinite reflectance, reflects that the considered rock units are occurred in different maturation stages, ranging from immature to mature sources. One-dimensional basin modeling was performed to analyze the hydrocarbon generation and expulsion history of the source rocks in the study area based on the reconstruction of the burial and thermal maturity histories in order to improve our understanding of the hydrocarbon generation potential. Calibration of the model with measured vitrinite reflectance (%Ro) and borehole temperature (BHT) data indicates that the paleo-heat flow was high at Late Jurassic. The models also indicate that the early hydrocarbon generation in the Madbi source rock occurred during late Cretaceous and the main hydrocarbon generation has been reached approximately at Early Eocene. Therefore, the Madbi source rock can be considered as generative potentials of prospective source rock horizons in the Sayun-Masilah basin.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Nabil Mohammed Al-Areeq",authors:[{id:"198686",title:"Dr.",name:"Nabil",middleName:"Mohammed",surname:"Al-Areeq",slug:"nabil-al-areeq",fullName:"Nabil Al-Areeq"}]},{id:"68009",doi:"10.5772/intechopen.88056",title:"Hybrid EOR Methods Utilizing Low-Salinity Water",slug:"hybrid-eor-methods-utilizing-low-salinity-water",totalDownloads:1258,totalCrossrefCites:6,totalDimensionsCites:14,abstract:"Low-salinity water (LSW) flooding has been applied in sandstone and carbonate formations to improve oil recovery. Wettability alteration by LSW has been identified as the dominant driving mechanism for the incremental oil recoveries. LSW flooding has been combined with other EOR methods to develop new hybrid approaches to improve crude/brine/rock (CBR) interactions with the objective of overcoming some of the LSW flooding downsides, which include oil trapping and fine migration. Hybrid methods can provide higher oil recovery than each stand-alone technique. For instance, changes in gas solubility during LSW injection positively affect the performance of LSW/gas hybrid injection. LSW/surfactant flooding can contribute to incremental recovery by simultaneously lowering interfacial tension (IFT) and wettability alteration. The synergistic effect of fluid redistribution by LSW and enhanced water mobility by polymer flooding improves oil detachment and displacement in porous media through the application of the hybrid approach LSW/polymer flooding. Nanoparticles (NPs), mainly SiO2, can alter wettability toward more water wetness in combination with LSW, and hot LSW can improve heavy oil production by reducing viscosity. Hence, the synergistic effect of hybrid EOR methods based on LSW flooding is considered a novel EOR approach to improve oil recovery.",book:{id:"7609",slug:"enhanced-oil-recovery-processes-new-technologies",title:"Enhanced Oil Recovery Processes",fullTitle:"Enhanced Oil Recovery Processes - New Technologies"},signatures:"Peyman Pourafshary and Nikoo Moradpour",authors:null}],mostDownloadedChaptersLast30Days:[{id:"56887",title:"Petroleum Source Rocks Characterization and Hydrocarbon Generation",slug:"petroleum-source-rocks-characterization-and-hydrocarbon-generation",totalDownloads:7858,totalCrossrefCites:6,totalDimensionsCites:15,abstract:"This chapter is proposed to give the principal learning on the application of the formation of petroleum source rocks and hydrocarbon generation to exploration activities. The evaluation of petroleum source rocks and hydrocarbon generation is a very important skill for explorationists to define the location and type of petroleum prospects in a region. In this chapter, subsurface samples from case study (Sayun-Masilah basin) were used to determine the source rock characteristics and petroleum generative potentials of prospective source rocks. Qualitative and quantitative evaluation of the source rock in this basin was done by means of geochemical and geophysical approaches for four rock units. It is clear that Madbi Formation is considered the main source, in which the organic carbon content reached up to more than 5.2 wt%. The types of organic matter from rock-eval pyrolysis data indicated that type I kerogen is the main type, in association with type II, and a mixture of types II and III kerogens. The study of the different maturation parameters obtained from rock-eval pyrolysis, such as Tmax and vitrinite reflectance, reflects that the considered rock units are occurred in different maturation stages, ranging from immature to mature sources. One-dimensional basin modeling was performed to analyze the hydrocarbon generation and expulsion history of the source rocks in the study area based on the reconstruction of the burial and thermal maturity histories in order to improve our understanding of the hydrocarbon generation potential. Calibration of the model with measured vitrinite reflectance (%Ro) and borehole temperature (BHT) data indicates that the paleo-heat flow was high at Late Jurassic. The models also indicate that the early hydrocarbon generation in the Madbi source rock occurred during late Cretaceous and the main hydrocarbon generation has been reached approximately at Early Eocene. Therefore, the Madbi source rock can be considered as generative potentials of prospective source rock horizons in the Sayun-Masilah basin.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Nabil Mohammed Al-Areeq",authors:[{id:"198686",title:"Dr.",name:"Nabil",middleName:"Mohammed",surname:"Al-Areeq",slug:"nabil-al-areeq",fullName:"Nabil Al-Areeq"}]},{id:"56405",title:"Characterization of Crude Oils and the Precipitated Asphaltenes Fraction using UV Spectroscopy, Dynamic Light Scattering and Microscopy",slug:"characterization-of-crude-oils-and-the-precipitated-asphaltenes-fraction-using-uv-spectroscopy-dynam",totalDownloads:3135,totalCrossrefCites:2,totalDimensionsCites:5,abstract:"Analysis of crude oil composition provides important information that impacts on the recovery, handling, and transportation of hydrocarbons. Crude characterization also provides data in the analysis of geochemistry of the source of origin. Crude oil characterization by optical methods is usually difficult because of its dark color; however, those characterizations are crucial because they give information that can affect some analysis procedures. Ultraviolet-visible (UV-vis) spectroscopy is a simple and practical technique that allows the characterization of crude oil through dilution in solvents. A comparative study of crude oil solutions contrasted with their asphaltene fractions was performed. Each solution was analyzed in triplicate, on a UV-vis spectrophotometer. Calibration curves for both raw solutions showed no significant variations, indicating stability. Additionally, the results of dispersion and migration phenomena indicated stability only for crude oil solutions. The aggregate size dispersion was different for each type of crude and varied with respect to time. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed the type of morphology present for each type of asphaltene.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Ernestina Elizabeth Banda Cruz, Nohra Violeta Gallardo Rivas, Ulises\nPáramo García, Ana Maria Mendoza Martinez and José Aarón Melo\nBanda",authors:[{id:"174756",title:"Dr.",name:"Ernestina Elizabeth",middleName:null,surname:"Banda Cruz",slug:"ernestina-elizabeth-banda-cruz",fullName:"Ernestina Elizabeth Banda Cruz"},{id:"175028",title:"Dr.",name:"Ana María",middleName:null,surname:"Mendoza-Martínez",slug:"ana-maria-mendoza-martinez",fullName:"Ana María Mendoza-Martínez"},{id:"186469",title:"Dr.",name:"Ulises",middleName:null,surname:"Paramo-Garcia",slug:"ulises-paramo-garcia",fullName:"Ulises Paramo-Garcia"},{id:"198863",title:"Dr.",name:"Nohra",middleName:"Violeta",surname:"Gallardo Rivas",slug:"nohra-gallardo-rivas",fullName:"Nohra Gallardo Rivas"},{id:"198864",title:"Dr.",name:"José Aarón",middleName:null,surname:"Melo Banda",slug:"jose-aaron-melo-banda",fullName:"José Aarón Melo Banda"}]},{id:"58250",title:"Microbial Bioremediation of Petroleum Hydrocarbon– Contaminated Marine Environments",slug:"microbial-bioremediation-of-petroleum-hydrocarbon-contaminated-marine-environments",totalDownloads:5093,totalCrossrefCites:20,totalDimensionsCites:38,abstract:"Petroleum pollution has become a serious environmental problem, which can cause harmful damage to the environment and human health. This pollutant is introduced into the environment from both natural and anthropogenic sources. Various physicochemical and biological treatments were developed for the cleanup of contaminated environments. However, bioremediation is based on the metabolic capabilities of microorganisms, and it is considered as the most basic and reliable way to eliminate contaminants, particularly petroleum and its recalcitrant compounds. It is more effective alternative comparing to classical remediation techniques. A high diversity of potential hydrocarbon degrader’s microorganisms was reported, and bacteria constitute the most abundant group, which has been well studied for hydrocarbon degradation. Several bioremediation approaches through bioaugmentation or/and biostimulation have been successfully applied. The interest on the optimizing of different parameters to achieve successful bioremediation technologies has been increased. In this chapter, we summarize the diversity and the hydrocarbon degradation potential of microorganism involved in the remediation of contaminated environments. We also present an overview of the efficient bioremediation strategies used for the decontamination of polluted marine environments.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Mouna Mahjoubi, Simone Cappello, Yasmine Souissi, Atef Jaouani\nand Ameur Cherif",authors:[{id:"107040",title:"Dr.",name:"Simone",middleName:null,surname:"Cappello",slug:"simone-cappello",fullName:"Simone Cappello"},{id:"219462",title:"Dr.",name:"Mouna",middleName:null,surname:"Mahjoubi",slug:"mouna-mahjoubi",fullName:"Mouna Mahjoubi"},{id:"223935",title:"Dr.",name:"Yasmine",middleName:null,surname:"Souissi",slug:"yasmine-souissi",fullName:"Yasmine Souissi"},{id:"223936",title:"Dr.",name:"Ameur",middleName:null,surname:"Cherif",slug:"ameur-cherif",fullName:"Ameur Cherif"}]},{id:"68009",title:"Hybrid EOR Methods Utilizing Low-Salinity Water",slug:"hybrid-eor-methods-utilizing-low-salinity-water",totalDownloads:1254,totalCrossrefCites:6,totalDimensionsCites:13,abstract:"Low-salinity water (LSW) flooding has been applied in sandstone and carbonate formations to improve oil recovery. Wettability alteration by LSW has been identified as the dominant driving mechanism for the incremental oil recoveries. LSW flooding has been combined with other EOR methods to develop new hybrid approaches to improve crude/brine/rock (CBR) interactions with the objective of overcoming some of the LSW flooding downsides, which include oil trapping and fine migration. Hybrid methods can provide higher oil recovery than each stand-alone technique. For instance, changes in gas solubility during LSW injection positively affect the performance of LSW/gas hybrid injection. LSW/surfactant flooding can contribute to incremental recovery by simultaneously lowering interfacial tension (IFT) and wettability alteration. The synergistic effect of fluid redistribution by LSW and enhanced water mobility by polymer flooding improves oil detachment and displacement in porous media through the application of the hybrid approach LSW/polymer flooding. Nanoparticles (NPs), mainly SiO2, can alter wettability toward more water wetness in combination with LSW, and hot LSW can improve heavy oil production by reducing viscosity. Hence, the synergistic effect of hybrid EOR methods based on LSW flooding is considered a novel EOR approach to improve oil recovery.",book:{id:"7609",slug:"enhanced-oil-recovery-processes-new-technologies",title:"Enhanced Oil Recovery Processes",fullTitle:"Enhanced Oil Recovery Processes - New Technologies"},signatures:"Peyman Pourafshary and Nikoo Moradpour",authors:null},{id:"58096",title:"Organic Contaminants in Refinery Wastewater: Characterization and Novel Approaches for Biotreatment",slug:"organic-contaminants-in-refinery-wastewater-characterization-and-novel-approaches-for-biotreatment",totalDownloads:1800,totalCrossrefCites:7,totalDimensionsCites:10,abstract:"Addressing major environmental issues, such as water pollution, is essential nowadays in realizing sustainable development. The ever-increasing world population and industrial development have led to the introduction of different types of chemicals to the environment, leading to considerable deterioration in environmental quality. A major class of these chemicals is phenolic compounds, which are hazardous pollutants and highly toxic even at low concentrations. In recent years, researchers have realized the importance of extracting new bacterial strains that are effective in treating different types of highly contaminated wastewaters at different severe conditions. They also focused considerable amount of research on developing new types of reactors that would provide efficient mixing and reduce mass transfer limitations. The aim is to develop and evaluate effective reactor systems and biocatalysts for the biodegradation of major contaminants in petroleum refinery wastewater. This chapter examines the different available options for the treatment of refinery wastewater with more focus on novel biotreatment options.",book:{id:"5811",slug:"recent-insights-in-petroleum-science-and-engineering",title:"Recent Insights in Petroleum Science and Engineering",fullTitle:"Recent Insights in Petroleum Science and Engineering"},signatures:"Taghreed Al-Khalid and Muftah H. El-Naas",authors:[{id:"219926",title:"Prof.",name:"Muftah",middleName:null,surname:"El-Naas",slug:"muftah-el-naas",fullName:"Muftah El-Naas"},{id:"222785",title:"Dr.",name:"Taghreed",middleName:null,surname:"Al-Khalid",slug:"taghreed-al-khalid",fullName:"Taghreed Al-Khalid"}]}],onlineFirstChaptersFilter:{topicId:"768",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"25",title:"Environmental Sciences",doi:"10.5772/intechopen.100362",issn:"2754-6713",scope:"
\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems. \r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
",coverUrl:"https://cdn.intechopen.com/series/covers/25.jpg",latestPublicationDate:"April 13th, 2022",hasOnlineFirst:!1,numberOfPublishedBooks:1,editor:{id:"197485",title:"Dr.",name:"J. Kevin",middleName:null,surname:"Summers",slug:"j.-kevin-summers",fullName:"J. Kevin Summers",profilePictureURL:"https://mts.intechopen.com/storage/users/197485/images/system/197485.jpg",biography:"J. Kevin Summers is a Senior Research Ecologist at the Environmental Protection Agency’s (EPA) Gulf Ecosystem Measurement and Modeling Division. He is currently working with colleagues in the Sustainable and Healthy Communities Program to develop an index of community resilience to natural hazards, an index of human well-being that can be linked to changes in the ecosystem, social and economic services, and a community sustainability tool for communities with populations under 40,000. He leads research efforts for indicator and indices development. Dr. Summers is a systems ecologist and began his career at the EPA in 1989 and has worked in various programs and capacities. This includes leading the National Coastal Assessment in collaboration with the Office of Water which culminated in the award-winning National Coastal Condition Report series (four volumes between 2001 and 2012), and which integrates water quality, sediment quality, habitat, and biological data to assess the ecosystem condition of the United States estuaries. He was acting National Program Director for Ecology for the EPA between 2004 and 2006. He has authored approximately 150 peer-reviewed journal articles, book chapters, and reports and has received many awards for technical accomplishments from the EPA and from outside of the agency. Dr. Summers holds a BA in Zoology and Psychology, an MA in Ecology, and Ph.D. in Systems Ecology/Biology.",institutionString:null,institution:{name:"Environmental Protection Agency",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"38",title:"Pollution",coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",isOpenForSubmission:!0,editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",slug:"ismail-m.m.-rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",biography:"Ismail Md. Mofizur Rahman (Ismail M. M. Rahman) assumed his current responsibilities as an Associate Professor at the Institute of Environmental Radioactivity, Fukushima University, Japan, in Oct 2015. He also has an honorary appointment to serve as a Collaborative Professor at Kanazawa University, Japan, from Mar 2015 to the present. \nFormerly, Dr. Rahman was a faculty member of the University of Chittagong, Bangladesh, affiliated with the Department of Chemistry (Oct 2002 to Mar 2012) and the Department of Applied Chemistry and Chemical Engineering (Mar 2012 to Sep 2015). Dr. Rahman was also adjunctly attached with Kanazawa University, Japan (Visiting Research Professor, Dec 2014 to Mar 2015; JSPS Postdoctoral Research Fellow, Apr 2012 to Mar 2014), and Tokyo Institute of Technology, Japan (TokyoTech-UNESCO Research Fellow, Oct 2004–Sep 2005). \nHe received his Ph.D. degree in Environmental Analytical Chemistry from Kanazawa University, Japan (2011). He also achieved a Diploma in Environment from the Tokyo Institute of Technology, Japan (2005). Besides, he has an M.Sc. degree in Applied Chemistry and a B.Sc. degree in Chemistry, all from the University of Chittagong, Bangladesh. \nDr. Rahman’s research interest includes the study of the fate and behavior of environmental pollutants in the biosphere; design of low energy and low burden environmental improvement (remediation) technology; implementation of sustainable waste management practices for treatment, handling, reuse, and ultimate residual disposition of solid wastes; nature and type of interactions in organic liquid mixtures for process engineering design applications.",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",slug:"zinnat-ara-begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",biography:"Zinnat A. Begum received her Ph.D. in Environmental Analytical Chemistry from Kanazawa University in 2012. She achieved her Master of Science (M.Sc.) degree with a major in Applied Chemistry and a Bachelor of Science (B.Sc.) in Chemistry, all from the University of Chittagong, Bangladesh. Her work affiliations include Fukushima University, Japan (Visiting Research Fellow, Institute of Environmental Radioactivity: Mar 2016 to present), Southern University Bangladesh (Assistant Professor, Department of Civil Engineering: Jan 2015 to present), and Kanazawa University, Japan (Postdoctoral Fellow, Institute of Science and Engineering: Oct 2012 to Mar 2014; Research fellow, Venture Business Laboratory, Advanced Science and Social Co-Creation Promotion Organization: Apr 2018 to Mar 2021). The research focus of Dr. Zinnat includes the effect of the relative stability of metal-chelator complexes in the environmental remediation process designs and the development of eco-friendly soil washing techniques using biodegradable chelators.",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null},{id:"39",title:"Environmental Resilience and Management",coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",isOpenForSubmission:!0,editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",slug:"jose-navarro-pedreno",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",biography:"Full professor at University Miguel Hernández of Elche, Spain, previously working at the University of Alicante, Autonomous University of Madrid and Polytechnic University of Valencia. Graduate in Sciences (Chemist), graduate in Geography and History (Geography), master in Water Management, Treatment, master in Fertilizers and Environment and master in Environmental Management; Ph.D. in Environmental Sciences. His research is focused on soil-water and waste-environment relations, mainly on soil-water and soil-waste interactions under different management and waste reuse. His work is reflected in more than 230 communications presented in national and international conferences and congresses, 29 invited lectures from universities, associations and government agencies. Prof. Navarro-Pedreño is also a director of the Ph.D. Program Environment and Sustainability (2012-present) and a member of several societies among which are the Spanish Society of Soil Science, International Union of Soil Sciences, European Society for Soil Conservation, DessertNet and the Spanish Royal Society of Chemistry.",institutionString:"Miguel Hernández University of Elche, Spain",institution:null},editorTwo:null,editorThree:null},{id:"40",title:"Ecosystems and Biodiversity",coverUrl:"https://cdn.intechopen.com/series_topics/covers/40.jpg",isOpenForSubmission:!0,editor:{id:"209149",title:"Prof.",name:"Salustiano",middleName:null,surname:"Mato",slug:"salustiano-mato",fullName:"Salustiano Mato",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLREQA4/Profile_Picture_2022-03-31T10:23:50.png",biography:"Salustiano Mato de la Iglesia (Santiago de Compostela, 1960) is a doctor in biology from the University of Santiago and a Professor of zoology at the Department of Ecology and Animal Biology at the University of Vigo. He has developed his research activity in the fields of fauna and soil ecology, and in the treatment of organic waste, having been the founder and principal investigator of the Environmental Biotechnology Group of the University of Vigo.\r\nHis research activity in the field of Environmental Biotechnology has been focused on the development of novel organic waste treatment systems through composting. The result of this line of work are three invention patents and various scientific and technical publications in prestigious international journals.",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorTwo:{id:"60498",title:"Prof.",name:"Josefina",middleName:null,surname:"Garrido",slug:"josefina-garrido",fullName:"Josefina Garrido",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRj1VQAS/Profile_Picture_2022-03-31T10:06:51.jpg",biography:"Josefina Garrido González (Paradela de Abeleda, Ourense 1959), is a doctor in biology from the University of León and a Professor of Zoology at the Department of Ecology and Animal Biology at the University of Vigo. She has focused her research activity on the taxonomy, fauna and ecology of aquatic beetles, in addition to other lines of research such as the conservation of biodiversity in freshwater ecosystems; conservation of protected areas (Red Natura 2000) and assessment of the effectiveness of wetlands as priority areas for the conservation of aquatic invertebrates; studies of water quality in freshwater ecosystems through biological indicators and physicochemical parameters; surveillance and research of vector arthropods and invasive alien species.",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},editorThree:{id:"464288",title:"Dr.",name:"Francisco",middleName:null,surname:"Ramil",slug:"francisco-ramil",fullName:"Francisco Ramil",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003RI7lHQAT/Profile_Picture_2022-03-31T10:15:35.png",biography:"Fran Ramil Blanco (Porto de Espasante, A Coruña, 1960), is a doctor in biology from the University of Santiago de Compostela and a Professor of Zoology at the Department of Ecology and Animal Biology at the University of Vigo. His research activity is linked to the taxonomy, fauna and ecology of marine benthic invertebrates and especially the Cnidarian group. Since 2004, he has been part of the EcoAfrik project, aimed at the study, protection and conservation of biodiversity and benthic habitats in West Africa. He also participated in the study of vulnerable marine ecosystems associated with seamounts in the South Atlantic and is involved in training young African researchers in the field of marine research.",institutionString:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}}},{id:"41",title:"Water Science",coverUrl:"https://cdn.intechopen.com/series_topics/covers/41.jpg",isOpenForSubmission:!0,editor:{id:"349630",title:"Dr.",name:"Yizi",middleName:null,surname:"Shang",slug:"yizi-shang",fullName:"Yizi Shang",profilePictureURL:"https://mts.intechopen.com/storage/users/349630/images/system/349630.jpg",biography:"Prof. Dr. Yizi Shang is a pioneering researcher in hydrology and water resources who has devoted his research career to promoting the conservation and protection of water resources for sustainable development. He is presently associate editor of Water International (official journal of the International Water Resources Association). He was also invited to serve as an associate editor for special issues of the Journal of the American Water Resources Association. He has served as an editorial member for international journals such as Hydrology, Journal of Ecology & Natural Resources, and Hydro Science & Marine Engineering, among others. He has chaired or acted as a technical committee member for twenty-five international forums (conferences). Dr. Shang graduated from Tsinghua University, China, in 2010 with a Ph.D. in Engineering. Prior to that, he worked as a research fellow at Harvard University from 2008 to 2009. Dr. Shang serves as a senior research engineer at the China Institute of Water Resources and Hydropower Research (IWHR) and was awarded as a distinguished researcher at National Taiwan University in 2017.",institutionString:"China Institute of Water Resources and Hydropower Research",institution:{name:"China Institute of Water Resources and Hydropower Research",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:0,paginationItems:[]},overviewPagePublishedBooks:{paginationCount:1,paginationItems:[{type:"book",id:"10843",title:"Persistent Organic Pollutants (POPs)",subtitle:"Monitoring, Impact and Treatment",coverURL:"https://cdn.intechopen.com/books/images_new/10843.jpg",slug:"persistent-organic-pollutants-pops-monitoring-impact-and-treatment",publishedDate:"April 13th 2022",editedByType:"Edited by",bookSignature:"Mohamed Nageeb Rashed",hash:"f5b1589f0a990b6114fef2dadc735dd9",volumeInSeries:1,fullTitle:"Persistent Organic Pollutants (POPs) - Monitoring, Impact and Treatment",editors:[{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",slug:"mohamed-nageeb-rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",biography:"Prof. Mohamed Nageeb Rashed is Professor of Analytical and Environmental Chemistry and former vice-dean for environmental affairs, Faculty of Science, Aswan University, Egypt. He received his Ph.D. in Environmental Analytical Chemistry from Assiut University, Egypt, in 1989. His research interest is in analytical and environmental chemistry with special emphasis on: (1) monitoring and assessing biological trace elements and toxic metals in human blood, urine, water, crops, vegetables, and medicinal plants; (2) relationships between environmental heavy metals and human diseases; (3) uses of biological indicators for monitoring water pollution; (4) environmental chemistry of lakes, rivers, and well water; (5) water and wastewater treatment by adsorption and photocatalysis techniques; (6) soil and water pollution monitoring, control, and treatment; and (7) advanced oxidation treatment. Prof. Rashed has supervised several MSc and Ph.D. theses in the field of analytical and environmental chemistry. He served as an examiner for several Ph.D. theses in analytical chemistry in India, Kazakhstan, and Botswana. He has published about ninety scientific papers in peer-reviewed international journals and several papers in national and international conferences. He participated as an invited speaker at thirty international conferences. Prof. Rashed is the editor-in-chief and an editorial board member for several international journals in the fields of chemistry and environment. He is a member of several national and international societies. He received the Egyptian State Award for Environmental Research in 2001 and the Aswan University Merit Award for Basic Science in 2020. 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He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}}]}},subseries:{item:{id:"95",type:"subseries",title:"Urban Planning and Environmental Management",keywords:"Circular economy, Contingency planning and response to disasters, Ecosystem services, Integrated urban water management, Nature-based solutions, Sustainable urban development, Urban green spaces",scope:"
\r\n\tIf we aim to prosper as a society and as a species, there is no alternative to sustainability-oriented development and growth. Sustainable development is no longer a choice but a necessity for us all. Ecosystems and preserving ecosystem services and inclusive urban development present promising solutions to environmental problems. Contextually, the emphasis on studying these fields will enable us to identify and define the critical factors for territorial success in the upcoming decades to be considered by the main-actors, decision and policy makers, technicians, and public in general.
\r\n
\r\n\tHolistic urban planning and environmental management are therefore crucial spheres that will define sustainable trajectories for our urbanizing planet. This urban and environmental planning topic aims to attract contributions that address sustainable urban development challenges and solutions, including integrated urban water management, planning for the urban circular economy, monitoring of risks, contingency planning and response to disasters, among several other challenges and solutions.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/95.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11979,editor:{id:"181079",title:"Dr.",name:"Christoph",middleName:null,surname:"Lüthi",slug:"christoph-luthi",fullName:"Christoph Lüthi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHSqQAO/Profile_Picture_2022-04-12T15:51:33.png",biography:"Dr. Christoph Lüthi is an urban infrastructure planner with over 25 years of experience in planning and design of urban infrastructure in middle and low-income countries. He holds a Master’s Degree in Urban Development Planning from the University College of London (UCL), and a Ph.D. in Urban Planning & Engineering from TU Berlin. He has conducted applied research on urban planning and infrastructure issues in over 20 countries in Africa and Asia. In 2005 he joined Eawag-Sandec as Leader of the Strategic Environmental Sanitation Planning Group. Since 2015 he heads the research department Sanitation, Water and Solid Waste for Development (Sandec) at the Swiss Federal Institute of Aquatic Research and Technology (Eawag).",institutionString:"Swiss Federal Institute of Aquatic Science and Technology, Switzerland",institution:null},editorTwo:{id:"290571",title:"Dr.",name:"Rui Alexandre",middleName:null,surname:"Castanho",slug:"rui-alexandre-castanho",fullName:"Rui Alexandre Castanho",profilePictureURL:"https://mts.intechopen.com/storage/users/290571/images/system/290571.jpg",biography:"Rui Alexandre Castanho has a master\\'s degree in Planning, Audit, and Control in Urban Green Spaces and an international Ph.D. in Sustainable Planning in Borderlands. Currently, he is a professor at WSB University, Poland, and a visiting professor at the University of Johannesburg, South Africa. Dr. Castanho is a post-doc researcher on the GREAT Project, University of Azores, Ponta Delgada, Portugal. 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