Representative architectures of GANs in recent years.
\r\n\t
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Holistic Principles to Transform Cities for Sustainability",doi:"10.5772/23957",slug:"what-is-green-urbanism-holistic-principles-to-transform-cities-for-sustainability",body:'This book chapter first looks at the timeline of important publications on sustainable design that emerged from different schools of thought, and how gradually the notion of
Over the last thirty-five years or so, an international debate on eco-city theory has emerged and has developed as a relevant research field concerning the future of urbanism and the city itself. During that time, a number of architectural schools of thought have been implemented worldwide. One such school is
In 1972, the
At the end of the 20th century, Tokyo, Sao Paulo, Mexico-City, Mumbai, Calcutta, Shanghai and Beijing have grown to become endless urban landscapes. They are new types of mega-cities, which express an impossibility of orderly planning and strategic regulation. In his 1994 essay, Rem Koolhaas rightly asked `What ever happened to urbanism?’. In 2000, the term `Climate Change’ has been getting widely introduced. We find emerging Green Urbanism theory for the 21st century, which aims to transform existing cities from fragmentation to compaction. Eco-city theory focuses on adjusting the relationship between city and nature. Leading sociologists and urban theorists, including Ulrich Beck, Saskia Sassen, Richard Sennett, Jan Gehl, Manuel Castells, Anthony Giddens, Herbert Girardet, Thomas Sieverts, to name just a few, are exploring wider areas such as globalization, urban sustainability, ecology, network systems, information and communication technologies, and other related fields. Federico Butera, Ken Yeang, Richard Burdett, Jaime Lerner and Jeffrey Kenworthy also made some important contributions to the discussion of sustainable urban planning. Solar cities in Linz-Pichling (Austria), Freiburg-Vauban and the Solar District Freiburg-Schlierberg (Germany), Hanover-Kronsberg (Germany), Stockholm Hammarby-Sjöstad (Sweden), the BedZED Development in Sutton (South of London, UK), and the green district EVA Lanxmeer in Culemborg (The Netherlands) represent some of the built milestones in sustainable urban development at the beginning of the 21st century. The Swedish city of Vaexjö has been very successful in reducing its CO2 emissions and will be, by 2015, entirely independent from fossil fuels. The industrial park in Kalundborg (Denmark) is often cited as a model for industrial ecology, while the city of Waitakere, in the Western part of the greater Auckland urban region, is New Zealand’s first eco-city. More recently, excellent compilations of research on sustainable cities have been published by
Satterthwaite, Wheeler and Beatley. In the meantime, `Sustainability Science’ has emerged as a conceptual and theoretical basis for a new planning paradigm. Today, we can probably recognize two major breaks in the continuous development of cities. The first is connected to the introduction of the automobile, which made possible an entirely different, dispersed city model (the de-compacted `Functional City’ of the 20th century). The second, the full awareness of climate change, is of equal importance and just as far-reaching, raising the possibility of entirely new city models and typologies that are likely to emerge: Green Urbanism.
Cities can and must become the most environmentally-friendly model for inhabiting our earth. It is more important than ever to re-conceptualize existing cities and their systems of infrastructure, to be compact, mixed-use and polycentric cities.
This part introduces the
With all this technological progress, we should not lose sight of the fact that a key component in any society’s sustainability is more than its carbon footprint. The future of our societies is not just merely a technical matter of finding more eco-friendly energy solutions, but a question of holistic social sustainability and identifying principles for healthy communities.
The three pillars of Green Urbanism, and the interaction between these pillars. Diagram: courtesy the author, 2007.
The districts and cities where
respond well to their climate, location, orientation and context, optimizing natural assets such as sunlight and wind flow,
are quiet, clean and effective, with a healthy microclimate,
have reduced or have no CO2 emissions, as they are self-sufficient energy producers, powered by renewable energy sources,
eliminate the concept of waste, as they are based on a closed-loop ecosystem with significant recycling, reusing, remanufacturing and composting,
have high water quality, practicing sensitive urban water management,
The holistic concept of Eco-City has again a balanced relationship between the urban (city) and the rural (countryside). Diagram: courtesy the author, 2008.
integrate landscape, gardens and green roofs to maximize urban biodiversity and mitigate the urban heat island effect,
take only their fair share of the earth’s resources, using principles of urban ecology,
apply new technologies such as co-generation, solar cooling and electric-mobility,
provide easy accessibility and mobility, are well inter-connected, and provide an efficient low-impact public transport system,
use regional and local materials and apply prefabricated modular construction systems,
create a vibrant sense of place and authentic cultural identity, where existing districts are densified and make use of urban mixed-use infill projects,
are generally more compact communities around transport nodes (`green TODs’), with a special concern for affordable housing and mixed-use programs,
use deep green passive design strategies and solar architecture concepts for all buildings, with compact massing for reduced heat gain in summer,
are laid-out and oriented in a way that keeps the buildings cool in summer, but which catches the sun in winter,
have a local food supply through community gardens and urban farming and which achieve high food security and reduced `food miles’, and
use multi-disciplinary approach, best practice for urban governance and sustainable procurement methods.
All these criteria make it clear that our design focus should be on the neighbourhood and district scale, with projects on urban infill or redevelopment (brownfield) sites, adjacent to existing developed areas and transport nodes (avoiding further greenfield sites or master planned developments in non-urban areas). The following
The following is a short list of the principles; for full discussion, see my book ‘The Principles of Green Urbanism. Transforming the City for Sustainability’ (2010). It must be noted, though, that in order to enable sustainable urban development and to ensure that eco-districts are successful on many levels, all urban design components need to work interactively and cannot be looked at separately. The principles are based on the triple-zero framework (triple-bottom line) of:
zero fossil-fuel energy use
zero waste
zero emissions (aiming for low-to-no-carbon emissions).
`Zero waste’ means that buildings are fully demountable and fully recyclable at the end of their life-cycle, so that the site can return to being a greenfield site after use. Understandably, it requires a holistic approach to put the principles in action and to guide the available know-how to the advantage of the city. The principles describe the strategies necessary for eco-districts, although they need to be adapted to the location, context and scale of the urban development. It may be difficult at first to achieve some of the principles, but all are important; they can potentially save money, reach early payback, improve livability and increase opportunities for social interaction of residents. The principles offer practical steps on the path to sustainable cities, harmonizing growth and usage of resources. The truly `carbon-neutral’ city has not yet been built, but all projects introduced in this book are important steps towards turning this vision into a reality.
The sustainability matrix – the
Principle 1 Climate and context
The city based on its climatic conditions, with appropriate responses to location and site context. What are the unique site constraints, climatic conditions and opportunities?
Every site or place has its own unique individual conditions in regard to orientation, solar radiation, rain, humidity, prevailing wind direction, topography, shading, lighting, noise, air pollution and so on. The various aspects of this principle include: Climatic conditions, which are seen as the fundamental influence for form-generation in the design of any project; understanding the site and its context, which is essential at the beginning of every sustainable design project; optimizing orientation and compactness to help reduce the city district’s heat gain or losses; achieving a city with minimized environmental footprint by working with the existing landscape, topography and resources particular to the site, and the existing micro-climate of the immediate surroundings. Maintaining complexity in the system is always desirable (be it biodiversity, eco-system or neighbourhood layout), and a high degree of complexity is always beneficial for society. Enhancing the opportunities offered by topography and natural setting leads to a city well adapted to the local climate and its eco-system. We can use the buildings’ envelope to filter temperature, humidity, light, wind and noise. Due to the different characteristics of every location, each city district has to come up with its own methods and tailored strategies to reach sustainability and to capture the spirit of the place. Each site or city is different and the drivers for re-engineering existing districts will need to understand how to take full advantage of each location’s potential, and how to fine-tune the design concept to take advantage of local circumstances. As an aim, all urban development must be in harmony with the specific characteristics, various site factors and advantages of each location and be appropriate to its societal setting and contexts (cultural, historical, social, geographical, economical, environmental and political). In future, all buildings will have climate-adapted envelope technologies, with facades that are fully climate-responsive.
Principle 2 Renewable energy for zero CO2 emissions
The city as a self-sufficient on-site energy producer, using decentralized district energy systems. How can energy be generated and supplied emission-free and in the most effective way?
The various aspects of this principle include: Energy supply systems and services, as well as energy efficient use and operation, promoting increased use of renewable power, and perhaps natural gas as a transition fuel in the energy mix, but always moving quickly away from heavy fossil-fuels such as coal and oil; and the transformation of the city district from an energy consumer to an energy producer, with local solutions for renewables and the increasing de-carbonizing of the energy supply. The supply of oil will last shorter than the life-expectancy of most buildings. The local availability of a renewable source of energy is the first selection criteria for deciding on energy generation. In general, a
well-balanced combination of energy sources can sensibly secure future supply. A necessary aim is also to have a distributed energy supply through a decentralized system, utilizing local renewable energy sources. This will transform city districts into local power stations of renewable energy sources, which will include solar PV, solar thermal, wind (on- and off-shore), biomass, geothermal power, mini-hydro energy and other new technologies. Some of the most promising technologies are in building-integrated PV, urban wind turbines, micro CHP and solar cooling. That is to say, there should be on-site electrical generation and energy storage in combination with a smart grid, which integrates local solar and wind generation, utilizing energy-efficiency in all its forms. Solar hot water systems would be compulsory. Co-generation technology utilizes waste heat through CHP combined-heat-and-power plants. Energy-efficiency programs are not enough. Too often we find that savings from energy-efficiency programs are absorbed by a rise in energy use. Genuine action on climate change means that coal-fired power stations cease to operate and are replaced by renewable energy sources. Eco-districts will need to operate on renewable energy sources as close to 100 per cent as possible. As a minimum, at least 50 per cent of on-site renewable energy generation should be the aim of all urban planning, where the energy mix comes from decentralized energy generation and takes into account the resources that are locally available, as well as the cost and the availability of the technology. Optimizing the energy balance can be achieved by using exchange, storage and cascading (exergy) principles. It is, therefore, essential that the fossil-fuel powered energy and transportation systems currently supporting our cities are rapidly turned into systems that are supplied by renewable energy sources. High building insulation, high energy-efficiency standards and the use of smart metering technology is essential, so that if a part of an office building is not in use, the intelligent building management system will shut down lights and ventilation.
Principle 3 Zero-waste city
The zero-waste city as a circular, closed-loop eco-system. How to avoid the creation of waste in the first place – changing behaviour of consumption?
Sustainable waste management means to turn waste into a resource. All cities should adopt nature’s zero-waste management system. Zero-waste urban planning includes reducing, recycling, reusing and composting waste to produce energy. All material flows need to be examined and fully understood, and special attention needs to be given to industrial waste and e-waste treatment. We need to plan for recycling centres, for zero landfill and ‘eliminating the concept of waste’ and better understanding nutrient flows (Braungart, 2002). Eco-districts are neighbourhoods where we reuse and recycle materials and significantly reduce the volume of solid waste and toxic chemical releases. All construction materials as well as the production of goods (and building components) need to be healthy and fully-recyclable. Waste prevention is always better than the treatment or cleaning-up after waste is formed. Some other systems that need to be put in place are: the remanufacturing of metals, glass, plastics, paper into new products needs to be a routine (without down-grading the product); waste-to-energy strategies are needed for residual waste; and an `extended producer responsibility’ clause is needed for all products. In this context of waste, better management of the nitrogen cycle has emerged as an important topic: to restore the balance to the nitrogen cycle by developing improved fertilization technologies, and technologies in capturing and recycling waste. Controlling the impact of agriculture on the global cycle of nitrogen is a growing challenge for sustainable development. Essentially, we need to become (again) a `recycling society’, where it is common that around 60 to 90 per cent of all waste is recycled and composted. In future, optimizing waste streams and material flows in regard to urban development will be guided by resource recovery and supply chains that use local materials, for achieving closed-cycle urban ecology and reduced material consumption.
Principle 4 Water
The city with closed urban water management and a high water quality. What is the situation in regard to the sustainable supply of potable drinking water?
The various aspects of this principle include, in general, reducing water consumption, finding more efficient uses for water resources, ensuring good water quality and the protection of aquatic habitats. The city can be used as a water catchment area by educating the population in water efficiency, promoting rainwater collection and using wastewater recycling and storm water harvesting techniques (e.g. solar-powered desalination plants). Storm water and flood management concepts need to be adopted as part of the urban design, and this includes storm water run-offs and improved drainage systems and the treatment of wastewater. As part of the eco-district’s adequate and affordable health care provisions, it needs to ensure the supply of safe water and sanitation. This includes such things as algae and bio-filtration systems for grey water and improving the quality of our rivers and lakes so that they are fishable and swimmable again. An integrated urban water cycle planning and management system that includes a high-performance infrastructure for sewage recycling (grey and black water recycling), storm water retention and harvesting the substantial run-off through storage, must be a routine in all design projects. On a household level we need to collect rain water and use it sparingly for washing and install dual-water systems and low-flush toilets. On a food production level we need to investigate the development of crops that need less water and are more drought resistant.
Principle 5 Landscape, gardens and urban biodiversity
The city that integrates landscapes, urban gardens and green roofs to maximize biodiversity. Which strategies can be applied to protect and maximize biodiversity and to re-introduce landscape and garden ideas back in the city, to ensure urban cooling?
A sustainable city takes pride in its many beautiful parks and public gardens. This pride is best formed through a strong focus on local biodiversity, habitat and ecology, wildlife rehabilitation, forest conservation and the protecting of regional characteristics. Ready access to these public parks, gardens and public spaces, with opportunities for leisure and recreation, are essential components of a healthy city. As is arresting the loss of biodiversity by enhancing the natural environment and landscape, and planning the city using ecological principles based on natural cycles (not on energy-intensive technology) as a guide, and increasing urban vegetation. A city that preserves and maximizes its open spaces, natural landscapes and recreational opportunities is a more healthy and resilient city. The sustainable city also needs to introduce inner-city gardens, urban farming/agriculture and green roofs in all its urban design projects (using the city for food supply). It needs to maximize the resilience of the eco-system through urban landscapes that mitigate the `urban heat island’ (UHI) effect, using plants for air-purification and urban cooling. Further, the narrowing of roads, which calms traffic and lowers the UHI effect, allows for more (all-important) tree planting. Preserving green space, gardens and farmland, maintaining a green belt around the city, and planting trees everywhere (including golf courses), as trees absorb CO2, is an important mission. As is conserving natural resources, respecting natural energy streams and restoring stream and river banks, maximizing species diversity. At home, we need to de-pave the driveway or tear up parking lots. In all urban planning, we need to maintain and protect the existing eco-system that stores carbon (e.g. through a grove or a park), and plan for the creation of new carbon storage sites by increasing the amount of tree planting in all projects. The increase in the percentage of green space as a share of total city land is to be performed in combination with densification activities.
Principle 6 Sustainable transport and good public space: compact and poly-centric cities
The city of eco-mobility, with a good public space network and an efficient low-impact public transport system for post-fossil-fuel mobility. How can we get people out of their cars, to walk, cycle, and use public transport?
Good access to basic transport services is crucial, as it helps to reduce automobile dependency, as does reducing the need to travel. We need to see integrated non-motorized transport, such as cycling or walking, and, consequently, bicycle/pedestrian-friendly environments, with safe bicycle ways, free rental bike schemes and pleasant public spaces. It is important to identify the optimal transport mix that offers inter-connections for public transport and the integration of private and public transport systems. Some ideas here include: eco-mobility concepts and smart infrastructure (electric vehicles); integrated transport systems (bus transit, light railway, bike stations); improved public space networks and connectivity, and a focus on transport-oriented development (`green TODs’). It is a fact that more and wider roads result in more car and truck traffic, and CO2 emissions, and also allows for sprawling development and suburbs that increases electricity-demand and provides less green space. The transport sector is responsible for causing significant greenhouse-gas emissions (over 20 per cent). To combat this effect we need to change our lifestyles by, for example, taking public transport, driving the car less, or car-pooling. Alternatively, we can ride a bike or walk, if the city district has been designed for it. Personal arrangements have the potential to reduce commuting and to boost community spirit. We want a city district which is well-connected for pedestrians, a city with streetscapes that encourage a healthy, active lifestyle and where residents travel less and less by car. `Green TODs’ are the future, as these developments can create a range of medium-density housing typologies and provide a variety of transportation choices, achieving a balance of residences and employment.
Principle 7 Local and sustainable materials with less embodied energy
City construction using regional, local materials with less embodied energy and applying prefabricated modular systems. What kind of materials are locally available and appear in regional, vernacular architecture?
The various aspects of this principle include: advanced materials technologies, using opportunities for shorter supply chains, where all urban designs focus on local materials and technological know-how, such as regional timber in common use. Affordable housing can be achieved through modular prefabrication. Prefabrication has come and gone several times in modern architecture, but this time, with closer collaboration with manufacturers of construction systems and building components in the design phase, the focus will be on sustainability. We need to support innovation and be aware of sustainable production and consumption, the embodied energy of materials and the flow of energy in closing life-cycles. We need to emphasize green manufacturing and an economy of means, such as process-integrated technologies that lead to waste reduction. It is more environmentally friendly to use lightweight structures, enclosures and local materials with less embodied energy, requiring minimal transport. We need improved material and system specifications, supported by research in new materials and technological innovation; reduced material diversity in multi-component products to help facilitate the design for resource recovery, disassembly, value retention, and the possibility of reusing entire building components. Success in this area will increase the long-term durability of buildings, reduce waste and minimize packaging.
Principle 8 Density and retrofitting of existing districts
The city with retrofitted districts, urban infill, and densification/intensification strategies for existing neighbourhoods. What are the opportunities to motivate people to move back to the city, closer to workplaces in the city centre?
The various aspects of this principle include: encouraging the densification of the city centre through mixed-use urban infill, centre regeneration and green TODs; increasing sustainability through density and compactness (compact building design means developing buildings vertically rather than horizontally); promoting business opportunities around green transit-oriented developments; optimizing the relationship between urban planning and transport systems; retrofitting inefficient building stock and systematically reducing the city district’s carbon footprint. Consideration will need to be given to better land-use planning to reduce the impact of urban areas on agricultural land and landscape; to increasing urban resilience by transforming city districts into more compact communities and designing flexible typologies for inner-city living and working. Special strategies for large metropolitan areas and fast-growing cities are required. Here, examples of rapid development are being provided by Asian cities. Special strategies are also needed for small and medium-sized towns due to their particular milieu, and creative concepts are needed for the particular vulnerabilities of Small Island States and coastal cities. Public space upgrading through urban renewal programs will bring people back to the city centre. This will need some strategic thinking about how to use brownfield and greyfield developments and also the adaptive reuse of existing buildings. Remodeling and re-energizing existing city centres to bring about diverse and vibrant communities requires people to move back into downtown areas. This can be achieved through mixed-use urban infill projects, building the `city above the city’ by converting low density districts into higher density communities; and by revitalizing underutilized land for community benefit and affordable housing. In the compact city, every neighbourhood is sustainable and self-sufficient; and uses ESCo principles for self-financing energy efficiency and in all retrofitting programs.
Principle 9 Green buildings and districts, using passive design principles
The city that applies deep green building design strategies and offers solar access for all new buildings. How can we best apply sustainable design and passive design principles in all their forms and for all buildings?
The various aspects of this principle include: low-energy, zero-emission designs, applying best practice for passive design principles, for all buildings and groups of buildings; dramatically reducing building energy use; introducing compact solar architecture; and renovating and retrofitting the entire building stock. New design typologies need to be developed at low cost, and we need to produce functionally neutral buildings that last longer. We need to apply facade technology with responsive building skins for bio-climatic architecture, to take advantage of cooling breezes and natural cross-ventilation, maximizing cross-ventilation, day-lighting and opportunities for night-flush cooling; we need to focus on the low consumption of resources and materials, including the reuse of building elements; and design for disassembly. Other ideas include: mixed-use concepts for compact housing typologies; adaptive reuse projects that rejuvenate mature estates; solar architecture that optimizes solar gain in winter and sun shading technology for summer, catching the low winter sun and avoiding too much heat gain in summer. It is important to renew the city with energy-efficient green architecture, creating more flexible buildings of long-term value and longevity. Flexibility in plan leads to a longer life for buildings. Technical systems and services have a shorter life-cycle. This means, first of all, applying technical aids sparingly and making the most of all passive means provided by the building fabric and natural conditions. Buildings that generate more energy than they consume, and collect and purify their own water, are totally achievable. We need to acknowledge that the city as a whole is more important than any individual building.
Principle 10 Livability, healthy communities and mixed-use programs
The city with a special concern for affordable housing, mixed-use programs, and a healthy community. How does urban design recognize the particular need for affordable housing, to ensure a vibrant mix of society and multi-functional mixed-use programs?
Land use development patterns are the key to sustainability. A mixed-use (and mixed-income) city delivers more social sustainability and social inclusion, and helps to repopulate the city centre. Demographic changes, such as age, are a major issue for urban design. It is advantageous for any project to maximize the diversity of its users. Different sectors in the city can take on different roles over a 24 hours cycle; for example, the CBD is used for more than just office work. In general we want connected, compact communities, for a livable city, applying mixed-use concepts and strategies for housing affordability, and offering different typologies for different housing needs. To this end we need affordable and livable housing together with new flexible typologies for inner-city living. These mixed-use neighbourhoods (of housing types, prices and ownership forms) have to avoid gentrification and provide affordable housing with districts inclusive for the poor and the rich, young and old, and workers of all walks of life, and also provide secure tenure (ensuring ‘aging in place’). Housing typologies need to deal with demographic changes. We have to understand migration and diversity as both an opportunity and a challenge. Mixed land uses are particularly important as it helps reduce traffic. Master plans should require all private developments to contain 40 to 50 per cent of public (social) housing, and have it integrated with private housing. Higher densities should centre on green TODs. Essentially, these changes will aim to introduce more sustainable lifestyle choices, with jobs, retail, housing and a city campus being close by with IT and tele-working from home significantly helping to reduce the amount of travel (motto: `Don’t commute to compute’). By integrating a diverse range of economic and cultural activities, we avoid mono-functional projects, which generate a higher demand for mobility. Green businesses would be supported through the use of ethical investments to generate funding. The question is: how specific or adaptable should buildings be to their use?
Principle 11 Local food and short supply chains
The city for local food supply, with high food security and urban agriculture.
Which strategies can be applied to grow food locally in gardens, on roof tops and on small spaces in the city?
The various aspects of this principle include: local food production; regional supply; an emphasis on urban farming and agriculture, including `eat local’ and `slow food’ initiatives. The sustainable city makes provision for adequate land for food production in the city, a return to the community and to the allotment gardens of past days, where roof gardens become an urban market garden. It is essential that we bridge the urban-rural disconnect and move cities towards models that deal in natural eco-systems and healthy food systems. The people of the eco-city would garden and farm locally, sharing food, creating compost with kitchen scraps and garden clippings and growing `community’ vegetables. Buying and consuming locally will be necessary to cut down on petrol-based transport. Such things as re-using paper bags and glass containers, paper recycling and the cost of food processing will need reconsideration. We will need to reduce our consumption of meat and other animal products, especially shipped-in beef, as the meat cycle is very intensive in terms of energy and water consumption and herds create methane and demand great quantities of electricity. Perhaps as much as 50 per cent of our food will need to be organically produced, without the use of fertilizers or pesticides made from oil, and grown in local allotments.
Principle 12 Cultural heritages, identity and sense of place
The city of public health and cultural identity: a safe and healthy city, which is secure and just. How to maintain and enhance a city’s or region’s identity, unique character and valued urban heritage, avoiding interchangeable design that makes all cities look the same?
All sustainable cities aim for air quality, health and pollution reduction, to foster resilient communities, to have strong public space networks and modern community facilities. This is the nature of sustainable cities. However, each city has its own distinct environment, whether it be by the sea, a river, in a dessert, a mountain; whether its climate is tropical, arid, temperate, etc, each situation is unique. The design of the city will take all these factors into consideration, including materials, history and population desires. The essence of place is the up-swelling of grassroots strategies, the protection of its built heritage and the maintenance of a distinct cultural identity, e.g. by promoting locally owned businesses, supporting creativity and cultural development. New ideas require affordable and flexible studio space in historic buildings and warehouses. Cities will grow according to the details and unique qualities of localities, demographic qualities of the populace and the creativity of the authorities and citizens. The aim of a city is to support the health, the activities and the safety of its residents. It is, therefore, incumbent on city councils to protect the city by developing a master plan that balances heritage with conservation and development; fostering distinctive places with a strong sense of place, where densities are high enough to support basic public transit and walk-to retail services.
Principle 13 Improved urban governance, leadership and best practice
The city applying best practice for urban governance and sustainable procurement methods. Which networks and skills can be activated and utilized through engaging the local community and key stakeholders, to ensure sustainable outcomes?
Good urban governance is extremely important if we want to transform existing cities into sustainable compact communities. It has to provide efficient public transport, good public space and affordable housing, high standards of urban management, and without political support change will not happen. City councils need strong management and political support for their urban visions to be realized. They need strong support for a strategic direction in order to manage sustainability through coherent combined management and governance approaches, which include evolutionary and adaptive policies linked to a balanced process of review, and to public authorities overcoming their own unsustainable consumption practices and changing their methods of urban decision-making. A city that leads and designs holistically, that implements change harmoniously, and where decision-making and responsibility is shared with the empowered citizenry, is a city that is on the road to sustainable practices. In balancing community needs with development, public consultation exercises and grassroots participation are essential to ensuring people-sensitive urban design and to encouraging community participation. Citizens need to participate in community actions aimed at governments and big corporations, by writing letters and attending city-council hearings. Empowering and enabling people to be actively involved in shaping their community and urban environment is one of the hallmarks of a democracy. Cities are a collective responsibility. As far as bureaucratic urban governance and best practice is concerned, authorities could consider many of the following: updating building code and regulations; creating a database of best practice and worldwide policies for eco-cities; revising contracts for construction projects and integrated public management; raising public awareness; improving planning participation and policy-making; creating sustainable subdivisions, implementing anti-sprawl land-use and growth boundary policies; legislating for controls in density and supporting high-quality densification; arriving at a political decision to adopt the
Principle 14 Education, research and knowledge
The city with education and training for all in sustainable urban development.
How to best raise awareness and change behaviour?
The various aspects of this principle include: technical training and up-skilling, research, exchange of experiences, knowledge dissemination through research publications about ecological city theory and sustainable design. Primary and secondary teaching programs need to be developed for students in such subjects as waste recycling, water efficiency and sustainable behaviour. Changes in attitude and personal lifestyles will be necessary. The city is a hub of institutions, such as galleries and libraries and museums, where knowledge can be shared. We must provide sufficient access to educational opportunities and training for the citizenry, thus increasing their chances of finding green jobs. Universities can act as `think tanks’ for the transformation of their cities. We also need to redefine the education of architects, urban designers, planners and landscape architects. Research centres for sustainable urban development policies and best practice in eco-city planning could be founded, where assessment tools to measure environmental performance are developed and local building capacity is studied.
Principle 15 Strategies for cities in developing countries
Particular sustainability strategies for cities in developing countries, harmonizing the impacts of rapid urbanization and globalization. What are the specific strategies and measurements we need to apply for basic low-cost solutions appropriate to cities in the developing world?
Developing and emerging countries have their own needs and require particular strategies, appropriate technology transfers and funding mechanisms. Cities in the developing world cannot have the same strategies and debates as cities in the developed world. Similarly, particular strategies for emerging economies and fast-growing cities are required, as is the problem of informal settlements and urban slums and slum upgrading programs. Low-cost building and mass housing typologies for rapid urbanization are required in cooperation with poverty reduction programs. It is essential that we train local people to empower communities, creating new jobs and diversifying job structures, so as not to focus on only one segment of the economy (e.g. tourism). Achieving more sustainable growth for Asian metropolitan cities is a necessity. Combating climate change, which was mainly caused through the emissions by industrialized nations and which is having its worst effect in poorer countries in Africa, Asia and Latin America, with a focus on Small Island States, is a priority.
The presented principles are about holistic strategies and integrated approaches: The most successful solutions are now the highly effective combination of passive design principles with some well considered
Before electrical heating, cooling and illumination became common, architects used a combination of passive design principles to ensure that interiors were well lit and ventilated through passive means, without any use of mechanical equipment. However, since the early 1950s most architects and engineers have simply employed air-conditioning systems for cooling, as energy from fossil fuels was cheap and plentiful, and air-conditioning systems allowed for deep-plan buildings, internalized shopping mall complexes and other highly inefficient air-conditioning dependent building typologies.
The biggest energy consumers in buildings are technical installations for cooling interiors and lighting. The extensive use of glass surfaces in the facades of buildings (especially in hot, tropical or subtropical climates) and materials that easily store the heat in summer
The outlined 15 principles of Green Urbanism aim to guide urban designers and decision-makers. Diagram: courtesy the author, 2008.
frequently lead to solar overheating, which has led to the widespread use of mechanical systems (air-conditioning systems) (Aynsley, 2006). Buildings in the tropics are a particular challenge due to the high humidity and temperatures. However, the tropics are home to almost two-thirds of the world’s population, so practical and achievable solutions are of particular relevance. With more careful building design, energy-hungry air-conditioning systems could be avoided in almost any climate. Instead of the use of mechanical air-conditioning systems, substantial improvements in comfort can be achieved by the informed choice of materials appropriate to basic passive energy principles and the optimization of natural ventilation (cross-ventilation, night-flush cooling, mixed-mode systems), summer shading and winter solar heat gain. Solar and wind energy can provide heating, cooling and electric power.
On the other hand, buildings from a pre-air-conditioning era frequently display a convincing application of passive design principles, such as their optimized orientation, the use of evaporative cooling, strategic use of thermal mass, trompe walls, ingenious sun-shading devices for the western facade, solar chimneys, courtyards allowing for cross-ventilation of hot air at the highest point in the room, and natural cross-ventilation adjustable to the changing directions of a breeze. Sub-slab labyrinths for fresh air intake, activating the thermal mass, have recently seen a comeback in many projects. Such underground air chambers, called thermal labyrinths, are frequently used to ventilate rooms, with air cooled naturally by travelling a long distance underground through channels in the earth. Energy savings from the use of thermal labyrinths can be significant (Daniels, 1995, 2000). In addition, the use of local materials with less embodied energy (combined with local workforce and locally available technical know-how) has recently led to regional ‘styles’ in architecture.
Successful buildings of the future will increasingly rely on the critical examination of, and learning from, buildings of the past (Vale and Vale, 1991, 2000; Hyde, 2000). There is so much we can learn from such studies, e.g. which passive design principles have delivered the most
The average German household produces around 43.5 tonnes of greenhouse gas emissions per year. Diagram: courtesy Umweltbundesamt, Germany, 2009.
energy savings? How has adequate active and passive thermal storage mass been provided? There is a good reason why passive design principles have traditionally been preferred to (and are now once again being chosen over) active systems. ‘We need solutions for buildings that can do more with less technology’, argues engineer Gerhard Hausladen, adding: ‘The optimization of the building layout and detailing of the facade system are essential for an integrated approach to the design of low-energy consuming buildings and cities’ (Hausladen et al., 2005; 41). Just optimizing buildings through the application of passive design principles can deliver energy savings of up to 80 per cent (Hausladen et al., 2005).
A building’s location and its surroundings play a key role in regulating its indoor temperature, the illumination of space and the capacity to minimize energy use. For example, trees and landscaping can provide shade or block wind, while neighbouring buildings can overshadow a building and thus increase the need for illumination during daytime. This is why the designer needs to understand the site conditions and the effective application of passive design principles fully (Hall and Pfeiffer, 2000; Gauzin-Mueller, 2002; Treberspurg, 2008).
For buildings to have the minimum adverse impact on the natural and built environment, energy-efficient building design needs to balance a whole range of requirements from various inter-linked issues, including (but not limited to):
design strategies based on a deep understanding of site and context
strategies for energy efficiency (operational and embodied)
strategies for water efficiency
material efficiency: focusing on material flows and embodied energy (life cycle)
overall material and waste streams during construction, operation and demolition
integrating passive design principles, such as optimizing the building’s shape and orientation, employing natural ventilation, use of daylight, thermal mass, sun shading, solar gains, the use of courtyard typologies, etc.
reducing overall greenhouse gas emissions from construction, operation and demolition
integrating community well-being and sundry social dimensions
health and quality of indoor environment (occupants’ comfort).
The need to minimize non-renewable resource consumption and reduce waste poses significant challenges for the building designer as well as construction companies, and for building operators during the period of building use. It is obvious that some of the earliest design decisions have a significant impact on energy efficiency and opportunities to use passive solar power or natural ventilation, such as decisions on: building orientation, placement on site, compactness and geometry, typology, material choices, facade openings, etc.
While recognizing that using more electricity from non-fossil fuels (such as solar and wind power) will help to address climate change, the building designer is likely to focus primarily on cutting energy consumption (Keeler and Burke, 2009). Reducing energy consumption with energy-efficient building design strategies is vital because it helps to preserve finite resources, lowers costs for businesses and consumers and can often be accomplished relatively quickly (again, the
Buildings using passive design principles are usually naturally ventilated (or use mixed-mode systems, which is a combination of natural ventilation and additional mechanical cooling during summer months) and are well day-lit to minimize the need for active systems of climate control and artificial lighting (Daniels and Hindrichs, 2007). Green roofs help to cut energy consumption by providing insulation to the building and by acting as filtration for the rainwater capture system, and at the same time increasing the city’s biodiversity.
Studying the built heritage plays an important role in the shift towards a low-carbon society. It offers a large resource of knowledge about design principles and how architects have operated for hundreds of years within the challenges of hot, arid or tropical climates. This knowledge has not been sufficiently discussed, taught and researched. In the light of globalization, it is increasingly necessary for the existing authentic built heritage to be a significant contributor to local identity, helping to define the unique character of a location, supporting local people to achieve social outcomes and as a memory of a place. The diversity and rich complexity of tangible and intangible heritage is a constant inspiration that deserves to be better maintained and protected.
Research in pre-air-conditioning built heritage is particularly relevant for the future of the Asia-Pacific region, where we can find rapid urbanization, sometimes combined with too much reliance on outdated models of urban growth and building designs, thus further increasing energy demands. This can include an unusually high dependency on mechanical (air-conditioning) systems, thereby creating large CO2 emissions and high operating costs in both residential and commercial building stock. In current discussions about sustainability and climate change, we can observe a re-appreciation and evaluation of the built heritage in harmony with its climatic conditions and geographic location. The Asia-Pacific region’s humid tropical climate poses a particularly difficult problem. It has temperatures often around 30 degrees Celsius during the daytime and around 25 degrees Celsius at night, and has a high relative humidity of about 90 per cent. This is typical for Singapore, Hong Kong, Bangkok, Jakarta, Manila and other large tropical cities suffering from the Urban Heat Island (UHI) effect. Such conditions leave little scope for night-flush cooling, and refreshing breezes (air flow) are often lacking for long periods (Aynsley, 2006). Serious climate engineering strategies are needed, and the de-humidification of the air as part of a cooling process is a preferable option. There are some particularly exciting developments in the innovative area of ‘solar cooling’. So far, around 400 installations worldwide already use such innovative solar cooling technology (Kohlenbach, 2010).
The UHI effect has been particularly difficult for large cities located in tropical regions. Hong Kong, for instance, has a very high population density and is always praised for its efficient public transport systems (Owens, 1986; Newman and Kenworthy, 1989). But the city has an extremely high dependency on air-conditioning and the lack of natural air ventilation in the city has emerged as a serious planning issue. Most buildings are not insulated and lack any external sun shading of their facades.
Brooks and Hyde have pointed out how a site’s micro-climate can be modified through careful site planning, leading to improved thermal comfort of outdoor spaces, increased capacity for natural ventilation and sun control in buildings, and therefore reduced cooling loads (Brooks, 1988; Hyde, 2000). Traditionally, in cities in Asia and the Middle East, there has always existed a large repertoire of climatically adaptive and culturally sensitive urban form, which is found in the traditional use of courtyard typologies and low-rise housing, even in high-density districts, with narrow, shaded laneways. In addition, there is a variety of passive cooling techniques that can be utilized for particular climate types, such as shaded spaces with courtyards and atria for effective cross-ventilation, open circulation with breezeways and verandahs, roof ventilation, solar chimneys and similar techniques.
The main principles of material and energy-efficient design include:
optimal orientation, appropriate window size and sun control (effective shading)
compact building form (building geometry with less facade surface)
building mass modified to increase natural air flow through site (catching breezes)
cross-ventilation and day lighting, with effective external sun shading (e.g. a louver system for sun control, using vertical shading louvers at the eastern and western facades; these have the advantage of retaining the outside view and are more effective than horizontal louvers)
passive solar heating for winter months
evaporative cooling systems
strategic selection of materials for use of thermal mass (e.g. choice of lightweight or heavy construction materials, with exposed, ‘activated’ concrete surface)
rooftop vegetation, gardens and water surfaces for improved micro-climate and reduced heat load
night-flush cooling through openings, activating thermal mass (using night purge)
sub-slab labyrinths, bringing in outside air through underground, cool air channels beneath the slab
white (not dark) facade and roof colouring
optimal sun shading devices, with wide roof overhangs to shade windows
landscaping for westerly facade protection
high insulation of external walls and roofs.
These strategies are often combined to make them work together as a system; for instance, by linking high thermal capacity (thermal mass) for heat sink effects with passive solar heating, or with cross-ventilation for night-flush cooling (summer cooling). The use of lightweight exterior facade construction elements with low thermal capacity can help to avoid the accumulation, storage and re-radiation of heat.
Deep building plans, beyond a maximum of 15 metres in depth, have disadvantages, as these can significantly reduce the effectiveness of day lighting and natural ventilation, leading to greater dependency on air-conditioning systems, thereby negatively impacting on the occupants’ health, thermal comfort, productivity and overall working conditions. Therefore, four of the most applicable and widely used passive design strategies are:
avoiding large glazing that receives direct sunlight and is without shading (design of high quality external shading)
reducing the surface-to-volume ratio as much as possible through compact building massing
using window sizing strategically in the design of the building (depending on orientation)
maximizing day lighting and natural cross-ventilation through slim building plans.
A widely recognized green urbanism model district is \'Hammarby Sjöstad\', an inner-city district of the Swedish capital city of Stockholm. It occupies an area of about 200 hectares, which, according to the masterplan, will comprise 11,000 apartments, for about 20,000 residents, and an additional 200,000 sqm area of commercial space by the year 2018. The project, which was started in the mid 1990s, expands the inner city centre towards to the waterfront, having water as a central focus for the development. It is the conversion of an old industrial and harbour area (brownfield site) into a modern, sustainable neighbourhood.
Hammarby Sjöstad has a strong emphasis on design principles of ecology and environmental sustainability. The development links the city centre with the new urban district by using same street dimensions, block lengths, building heights, density and mix of uses as can be found in the city centre, delivering a high quality neighbourhood. One could say that the new district has a traditional Swedish structure, which it has combined with a modern architectural language that responds to the specific waterside context. The design promotes sustainability and follows modern architectural principles, such as maximising light and views of the water and green spaces. It follows standard dimensions of street width (18 m), block sizes (70x100 m), density, and land use. Public transport and the creation of new road and tram infrastructure make the area easily accessible.
The scale of the development varies from four to five storeys along the canal and 6 to 8 storeys along the inner area. The spine of the new district is a 37.5 m wide boulevard, which connects key transport nodes and public focal points, creating a natural focus for activity and retail. The ground floors of nearly all the buildings along this boulevard have been designed as flexible spaces, suitable for commerce, leisure or community use. Many residents work in the neighbourhood which allows them to walk to work.
The residential districts adjacent to the main spine follow a grid structure with a semi-open block form, which delivers maximum daylight and long views, as well as providing open access to the courtyards of residential blocks. Most apartments have balconies overlooking the streets and waterfront. An inter-connected network of varied parks, green spaces and walkways runs through the district as well as pedestrian paths, quays and linear parks across the waterfront, offering access to the residents towards the boat moorings in the summer. Community provisions include a modern church building, two public schools, one private school, one pre-school and nursery, a health centre, a library, a sports centre, a football pitch and basketball court and other amenities.
Example of Green Urbanism in practice: The green district Hammarby Sjöstad in Stockholm, built 1995-2008 on land formerly used by the port (to be fully completed in 2018). It is widely accepted as a best practice model for sustainable urban development, having included in its urban development innovative principles of water and waste management and reduction of car dependency. Image: courtesy City of Stockholm, Sweden, 2008.
Stockholm’s green district Hammarby Sjöstad includes on-site energy generation with solar cells and green roofs, as well as principles for sensitive urban water management. Image: courtesy City of Stockholm, Sweden, 2008. See also:
It is important to note, that a couple of innovative engineering solutions will not deliver a vibrant city. All the technology in the world cannot achieve sustainability and vitality by
Moving from a non sustainable linear metabolism towards a more sustainable, circular metabolism, requires the looping and re-use of materials and products. Less required input and less waste generation are the characteristics of such a healthier city structure. Diagram: courtesy the author, 2010 (after: H. Girardet, 1999).
itself. The problem of urban design is far more complex. Designing a city requires holistic, multi-dimensional approaches, and each time the adaptation of strategies to a unique context: the integration and combination of qualitative and quantitative knowledge.
There is now a growing interest in understanding the complex interactions and feedbacks between urbanization, material consumption, energy and water efficiency and the depletion of our resources. The question how far urban form and population density impact on resource consumption is important but still not fully understood.
Much of Green Urbanism is common sense urbanism. In the future,
Convolutional Neural Networks (CNNs) are specially designed to handle data that consists of multiple arrays/matrixes such as an image composed of three matrixes in RGB channels [1]. The key idea behind CNNs is the convolution operation, which is to use multiple small kernels/filters to extract local features by sliding over the same input. Each kernel can output a feature map and all the feature maps are concatenated together, this is also known as a convolutional layer and it is the core component in a CNN. Note that these concatenated maps can be further processed by the next layer. To reduce the computational cost, the pooling operation such as maximum pooling is usually applied on these feature maps. A typical CNN is usually structured as a series of layers, including multiple convolutional layers and a few of fully connected layers. For example, the famous LeNet [2] consists of two convolutional layers and three fully connected layers, and the pooling operation is used after each convolutional layer.
In addition to building a neural network, a loss function is essential to measure the model performance. Therefore, the process of training a CNN model is transformed into an optimization problem, which normally seeks to minimize the value of the loss function over the training data. Specifically, a gradient-descent based algorithm is usually adopted to iteratively optimize the parameters in a CNN.
Figure 1 shows the high-level abstraction of CNNs in this survey. Specifically, we firstly introduce two types of convolution operations in Section 2. Then four methods are summarized for constructing convolutional layers in CNNs in Section 3. In Section 4, we group the current CNN architectures into three types: encoder, encoder-decoder and GANs. Next, we discuss two main types of loss functions in Section 5. In Section 6, we give the advanced applications based on the three types of CNN structures. Finally in Section 7, we conclude this research and give future trends.
High-level abstraction of convolutional neural networks in this survey.
The main reason why CNNs are so successful on a variety of problems is that kernels (also known as filters) with fixed numbers of parameters are adopted to handle spacial data such as images. In particular the weight sharing mechanism can help reduce the number of parameters for low computational cost while remaining the spacial invariance properties. In general, there are mainly two types of convolution operations, including basic convolution and transposed convolution.
As shown on the left in Figure 2, convolution operation essentially is a linear model for the local spacial input. Specifically, it only performs the sum of element-wise dot products between the local input and the kernels (usually including a bias), and output a value after an activation function. Each kernel slides overall spacial locations in the input with a fixed step. The result is that we can get an 1-channel feature map. Note that there are generally many kernels in one convolutional layer, and all of the output feature maps are concatenated together, e.g., if the number of kernels used in this convolutional layer is
While the kernel size of
Normally the size of output feature maps generated from the basic convolution is smaller than the input space (i.e., the dimension of input
Similarly, we can still use dilated kernels in transposed convolution. The main reason why we need transposed convolution is that it is the fundamental idea to construct a decoder network, which is used to map a latent space into an output image, such as the decoders in U-Net [6] and GANs. Specifically, the transposed convolution is widely used in tasks such as model visualization [7], image segmentation [6], image classification [8] and image super-resolution [9].
The core components in CNNs are convolutional layers. In the last section, we have demonstrated two types of convolution operations and they are the main idea to construct convolutional layers. In this part, we summarize the main methods in deep learning for building convolutional layers, including basic convolutional layers, convolutional layers with shortcut connection, convolutional layers with mixed kernels and convolutional capsule layers.
Recall that there are normally
where
While there are many variants related to the activation function, the typical ones which are widely adopted are ReLU
Note that after convolution operation, the width and height of the output feature map
where
It is true that deep neural networks normally can learn better representation from the data than shallow neural networks. However, stacking more layers in a CNN can lead to the problems of vanishing or exploding gradients, which make the networks hard to optimize. A simple and effective way to address this problem is to use shortcut connections, which can help directly transform the information from the previous layer to the current layer in a network.
Note that
So far we have demonstrated that we normally use many convolutional kernels with the same size in one convolutional layer such as
where pool(I) denotes the pooling operation such as max-pooling. Therefore, the size of the output feature map is
However, if we directly add different sizes of kernels in one convolutional layer, the computational cost involved will increase sharply. In the inception module [13, 14], a
In general, pooling operation is essential to reduce the size of output feature maps so that we can obtain high-level abstractions from input by stacking multiple convolutional layers in a CNN. However, the cost is that some information in the feature maps has been abandoned such as conducting max-pooling.
In 2017 [15], Hinton et al. proposed an alluring version of convolutional architectures, which is known as capsule networks, followed by the updated versions in 2018 [16] and 2019 [17]. The convolutional capsule layers in capsule networks are very similar to the traditional convolutional layers. The main difference is that each capsule (i.e., an element in convolutional feature maps) has a weight matrix
Although numerous variants of CNN architectures for solving different tasks are proposed from the deep learning community every year, their essential components and over-all structures are very similar. We group the recent classic network structures into three main types, including encoder, encoder-decoder and GANs.
In 1990, LeCun et al. proposed a seminal network called LeNet [2], which help establish the modern CNN structure. Since then, many new methods and compositions are proposed to handle the difficulties encountered in training deep networks for challenging tasks such as objective detection and recognition in computer vision. Some representative works in recent years are AlexNet [18], ZFNet [7], VGGNet [19], GoogleNet [13], ResNet [11], Inception [14]. As mentioned earlier, new methods for constructing convolutional layers in these networks are proposed, e.g., shortcut connection [11] and mixed kernels [14, 20].
In general, the above-mentioned networks can all be regarded as encoders, in which each input such as an image is encoded into a high-level feature representation, as shown on the left in Figure 4. And this encoded representation can be further used for, such as image classification, object detection etc. In some literatures, an encoder is also called as a feature extractor. Specifically, the basic convolutional layers are the main components for constructing an encoder network, by stacking multiple layers, each layer in the network can learn high-level abstractions from previous layers [1]. More formally, an encoder network can be written as
where
In some specific tasks such as image segmentation [20], our goal is to map an input image to a segmented output image rather than an abstraction. An encoder-decoder structure is specifically designed for solving this type of task. There are many possible ways to implement an encoder-decoder structure, and many variants have also been proposed to improve the drawbacks in the last few years. A naive version of encoder-decoder network which was introduced in [20] can be denoted as
where
As shown in the middle in Figure 4, an encoder-decoder network is still one complete network and we can train it with an end-to-end method. Note that there are generally many convolutional layers in each coder network, which results that it can be challenging to train a deep encoder-decoder network directly. Recall that the shortcut connection is often adopted to address the problems in deep CNNs. Naturally, we can add connections between the encoder and the decoder. An influential network based on this idea is U-Net [6], which is widely applied in many challenging domains such as medical image segmentation. The above two equations can also be rewritten as a composition of two functions.
Specifically, in unsupervised learning, an encoder-decoder network is also well known as autoencoder. And there are many variants of autoencoders proposed in recent years, some famous ones including variational autoencoder [21], denoising variational autoencoder [22] and conditional variational autoencoder [23, 24].
Since generative adversarial networks were firstly proposed by Goodfellow et al. [25] in 2014, this type of architectures for playing two-player minimax game has been most extensively studied. Partly because it is an unsupervised learning method and we can obtain a fancy generator network which can help generate fake examples from a latent space (i.e., a vector with some random noise). On the right in Figure 4 shows the basic structure of GANs, in which a generator network can map some input noise into a fake example and make it look as real as possible and a discriminator network always tries to identify the fake sample from its input. By iteratively training the two players, they can both improve their methods. More formally, we can have
where
As shown in Table 1, numerous variants of GANs architectures can be found in the recently published literatures and we broadly summarize these representative networks according to their published time. Note that the fundamental methods behind these architectures are very similar.
Name | Year | Summary |
---|---|---|
GANs [25] | 2014 | The original version of GANs, where |
Conditional GANs [26] | 2014 | Labels are included in |
Laplacian Pyramid GANs [27] | 2015 | CNNs with the laplacian pyramid method. |
Deep Convolutional GANs [28] | 2015 | Transposed convolutional layers are used to construct |
Bidirectional GANs [29] | 2016 | An extra encoder was adopted based on the traditional GANs. |
Semi-supervised GANs [30] | 2016 | The |
InfoGANs [31] | 2016 | An extra classifier was added into the GANs. |
Energy-based GANs [32] | 2016 | The |
Auxiliary Classifier GANs [33] | 2017 | An auxiliary classifier was used in the |
Progressive GANs [34] | 2017 | Progressive steps are adopted to explain the networks. |
BigGANs [35] | 2018 | A large GANs with self-attention module and hinge loss. |
Self-attention GANs [36] | 2019 | The self-attention mechanism is proposed to build |
Label-noise Robust GANs [37] | 2019 | A noise transition model is included in |
AutoGANs [38] | 2019 | The neural architecture search algorithm is used to obtain |
Your Local GANs [39] | 2020 | A new local sparse attention layer was proposed. |
MSG-GANs [40] | 2020 | There are connections from |
Representative architectures of GANs in recent years.
Before introducing the loss functions, we need to understand that the ultimate goal to train a neural network
where
Note that there are numerous variants of loss functions used in the deep learning literature. However, the fundamental theories behind them are very similar. We group them into two categories, namely Divergence Loss Functions and Margin Loss Functions. And we also introduce six typical and classic loss functions that are commonly used for training neural networks.
Divergence loss functions denote a family of loss functions based on computing the divergences between the predicted results and true labels, mainly including Kullback-Leibler Divergence, Log Loss, Mean Squared Error.
Before introducing the Kullback–Leibler divergence, we need to understand that the fundamental goal of deep learning is to learn a data distribution
where
Specifically,
where
Log loss is widely used in the current deep neural networks due to its simplicity and power. The binary log loss function is defined as
where
When the learning task is multi-class classification, each sample label is normally encoded with the one-hot-encoding format, which can be denoted as
where
We may wonder why the log loss is a reasonable choice. Informally, let
And our goal is to minimize the divergence between
Probably the mean squared error is one of the most familiar loss functions as it is really like the least square loss function. It directly calculates the difference between the predicted result and the true label, which is denoted as
One example which can help us deeply understand the mean squared error is that minimize the mean squared loss of a linear regression model is equivalent to maximum likelihood. In other words, this is a method to optimize the parameters of our model so that the distribution learned by our model is most probable under the observed training data. Therefore, the fundamental goal is still the same as above, which is to make the model distribution and the data distribution as close as possible.
Margin loss functions represent a family of margin maximizing loss functions. The typical functions include Hinge Loss, Contrastive Loss and Triplet Loss. Unlike the divergence loss functions, margin loss functions calculate the relative distances between outputs and they are more flexible in terms of training data.
Hinge loss is well known to train Support Vector Machine classifiers. Specifically, there are two main types of hinge losses. The first type is for each sample with only one correct label, it is denoted as
where
However, in real tasks such as attribute classification, each samples can have multiple correct labels. e.g., a photo posted on Facebook may include a set of hashtags. Therefore, the second type for multiple labels is
where
Contrastive loss is specially designed for measuring the similarity of a pair of training samples. Considering two pairs of samples
where
where
Triplet loss looks similar to the contrastive loss, but it is a measure of the difference between the matched pair and the unmatched pair. Considering three samples
Note that minimize the loss function is equivalent to minimizing the distances of matched pairs and maximizing the distances of unmatched pairs.
One of the most exciting areas in deep learning is that we can apply neural networks to a numerous number of applications that cannot be solved well or be handled by the traditional machine learning method. In this section, we summarize the typical advances that CNNs has achieved based on the three types of CNN structures.
A basic task in machine learning is classification, which is the problem of identifying to which of a list of labels a new sample belongs, such as the well-known CIFAR-10 dataset, in which there are 10 categories of images and the goal is to train a model for correctly classifying an unseen image based on observing the training dataset. In particular, CNNs have made many breakthroughs on large scale image datasets such as the ImageNet challenge [18]. As mentioned in Section 4.1, the classic encoders such as AlexNet [18], ZFNet [7], VGGNet [19], GoogleNet [13], ResNet [11], Inception [14] are regarded as the milestones in the past few years. The successes of these encoders are all based on supervised learning, which means that manual labelling is essential for the dataset such as the ImageNet dataset [42]. Specifically, a labeled dataset is normally divided into training and test dataset (may also include a validation dataset), and our goal is to achieve good performance on the test dataset after training a neural network with the training dataset, and the pre-trained model can be further used for classifying new images that are from the same data distribution space.
Classification can also be treated as a fundamental problem in machine learning, the successes of these encoders on image classification also help establish the foundation for many other applications. Specifically, we can utilize an encoder to extract high-level representation from the low-level input image, and the obtained representation can be further used for many other applications.
In addition to image classification, object detection is also very important in computer vision. Image classification gives us the answer to what a given image is, and object detection is about telling us the specific positions of objects in an image. Specifically, the goal is to train an encoder to output a suitable bounding box and associated class probabilities for each object in a given image. Two typical methods are widely used in the current computer vision, including YOLO [43] and SSD [44]. The core idea of YOLO is that object detection is treated as an regression problem, which means that each image is divided into multiple grids and each grid cell outputs a pre-defined number of bounding boxes, the corresponding confidence for each box and class probabilities [43]. Since the first version of YOLO was proposed, the updated versions have also been proposed. SSD is a more simple method, which utilizes a set of default boxes with different aspect ratios, and each box outputs the shape offsets and the class confidences [44].
The multiple levels of representations learned in the multiple layers of CNNs can also be used for solving the task of human-body pose estimation. Specifically, there are mainly two types of approaches, including regression of body joint coordinates and heat-map for each body part. In 2014, a framework called DeepPose [45] was introduced to learn pose estimation by a deep CNN, in which estimating human-body pose is equivalent to regressing the body joint coordinates. There are also some extension works based on this method, such as a process called iterative error feedback [46], which encompasses both the input and output spaces of CNN for enhancing the performance. In 2014, Tompson et al. [47] propose a hybrid architecture which consists of a CNN and a Markov Random Field, in particular the output of the CNN for an input image is a heat-map. Some recent works based on the heat-map method such as [48], in which a multi-context attention mechanism was proposed to incorporate with CNNs.
The operation of image restoration is to recover a damaged or corrupt image for the clean image such as image denoising and super-resolution. Therefore, a natural way to implement this idea is to utilize a pre-trained encoder-decoder network, where the encoder can map a noise image into a high-level representation, and the decoder can transform the representation into an original image. For example, Mao et al. [49] apply a deep convolutional encoder-decoder network for image restoration, in particular the shortcut connection method is adopted between the encoder and decoder, which has been demonstrated in Section 3.2. And the transposed convolution is used for constructing the decoder network, as mentioned in Section 2.2. Similar work in [50] has also been introduced for image restoration, in which a residual method is used in the network (i.e., in Section 3.2).
The task of image segmentation is to map an input image into a segmented output image. The encoder-decoder networks have been developed dramatically in recent years and achieve a significant impact on computer vision. Specifically, there are mainly two types of tasks including semantic segmentation and instance segmentation. In 2015, Long et al. [20] firstly showed that an end-to-end fully CNN can achieve state-of-art in image segmentation tasks. Similar work has also been introduced in [6] in 2015, in which a U-Net architecture is proposed for medical image segmentation, and the main advance in this architecture is that the shortcut connection method is also used between the encoder and decoder network. Since then, a series of papers based on these two methods have been published. In particular nowadays the U-Net based architectures are widely used for the medical image diagnosis.
One of the exciting applications achieved by CNNs is image captioning, which is to describe the content of an input image with natural language. The basic idea is as follows: Firstly, a pre-trained CNN encoder is used to extract some high-level features from an input image. Secondly, these features are typically fed into an recurrent neural network for generating a sentence. For example, Li et al. [51] proposed a fully convolutional localization network for extracting representation from images and the decoder for generating captions is LSTM. Recently, attention mechanism has been widely used for sequence processing and achieved significant improvements such as machine translation, Huang et al. [52] introduce an encoder-decoder framework, where an attention module is used in the encoder and decoder respectively. Specifically, the encoder is a CNN based network.
Note that speech signals exhibit spectral variations and correlations, CNNs are very suitable to reduce them. Therefore, CNNs can also be utilized for the task of speech processing, such as speech recognition. Sainath1 et al. [53] applied deep CNNs for large vocabulary speech tasks. In [54, 55, 56], the CNNs are used for speech recognition. And the fundamental methods are very similar, both of them use the CNNs to extract features from the raw input, and then these features are fed into an decoder for the specific learning tasks.
The most typical application of GANs is to generate fake examples. Recall that there normally are two dependent networks in GANs, including
Generating fake samples can be regarded as data augmentation, which means that these fake data can be further used to train models. Note that deep learning is also well known as a data-driven approach. In particular most of the advances that deep neural networks achieved are based on supervised learning. Specifically, the current successful neural network models usually consist of millions of parameters. And annotated data is essential to optimize these parameters for guaranteeing the model accuracy when conducting supervised learning. However, manually labeling data is time-consuming and expensive, especially in some specific domains such as medicine. Even more severe is that it can be hard to collect enough data due to the privacy concerns. There are numerous works to utilize GANs for enhancing model performance. E.g., in [57], a semi-supervised framework based on GANs is applied to semantic segmentation in order to address the lack of annotations. [58] is a work of utilizing synthetic medical images for enhancing the performance of liver lesion classification.
Despite the successes of GANs, generating high-resolution, diverse samples is still a challenging task. In [35], they introduce the progressive GANs which can generate high-resolution human faces. Another impressive work to generate realistic photographs is BigGANs [36].
Another interesting application derived from GANs is image translation. While there are many specific applications, we summarize them into three categories, including translation of image to image, translation of text to image and translation of image to super-resolution.
Image editing is regarded as a fundamental problem in computer vision. The emergence of GANs has also brought new chances for this task. In the past few years, GANs have been developed for image editing, such as image inpainting and image matting.
In this research, we have conducted a hierarchically-structured survey of the main components in CNNs from the low level to the high level, namely, convolution operations, convolutional layers, architecture design, loss functions. In addition to introducing the recent advances of these aspects in CNNs, we have also discussed the advanced applications based on the three types of architectures including encoder, encoder-decoder and GANs, from which we can see that CNNs have made numerous breakthroughs and achieved state-of-the-art in computer vision, natural language processing and speech recognition, especially these fantastic results based on GANs.
From the above analyses, we can summarize that the current development tendencies in CNNs mainly focus on designing new architectures and loss functions. Because these two aspects are the core parts when applying CNNs into various types of tasks. On the other hand, the fundamental ideas behind these various applications are very similar, as summarized above.
However, there are still many disadvantages in the current deep learning. The first problem is the requirement of large-scale datasets, in particular constructing a labeled dataset is very time-consuming and expensive such as in the medical domain. Therefore, we need to pay much more attention to semi-supervised learning and unsupervised learning. The second disadvantage is the high computational cost related to training deep CNNs, as the current standard CNN structures become deeper and deeper and they usually consists of millions of parameters. The third issue is that applying CNNs into tasks is not an easy job and it usually requires professional skills and experiences, because training a network involves a lot of hyper-parameters to tune, such as the number of kernels in each layer, the size of kernels, the total number of layers, learning rate etc.
Future work should focus on deep learning theory as the solid theory for supporting the current neural models is lacking. Unlike other machine learning algorithms such as support vector machines that have obvious mathematical logic, it is usually very hard to totally understand why a deep network can achieve such an excellent performance on a task. Therefore, based on the current developments of deep learning, we give three trends on which we need to work in the future: Neural Topologies such as the graph neural networks, Uncertainty Estimation such as Bayesian neural networks and Privacy Preservation.
This work is supported by China Scholarship Council and Data61 from CSIRO, Australia.
The authors declare no conflict of interest.
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Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. 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