Prioritization of the Physical Resilience Criteria for Affordable Housing Locating Based on An Analytic Hierarchy Process (AHP)

Abstract

Natural hazards cause numerous problems occurred mostly in residential areas. Affordable housing is one of the types of housing that is planned for low- and middle-income groups. Optimum location of affordable housing is one of the most important criteria for this type of housing. Due to the high vulnerability of its residents, it is necessary to evaluate the site resilience. This chapter is aimed to identify and prioritize the criteria of physical resilience that are effective in selecting a resilient location for the affordable housing construction. Documentary materials are used to explain the literature and to determine the effective factors on physical resilience. Then the criteria were prioritized using AHP method by 22 experts. The important criteria obtained from the research include Infrastructure & Services (IS), Region Context (RC), Natural Environment (NE) and Surrounding Uses (SU). This research can be the basis of a strategic document for the discussion of the affordable housing resilience.

1. Introduction

The location of housing and its connectivity to jobs, services, and amenities is central to reducing socio-spatial inequalities. Resilience is one of the most basic issues in today’s world due to the occurrence of natural or anthropogenic events. The housing resilience process should have the necessary capability to predict accidents and prevent the burden of life and financial losses on citizens. In an ecosystem, resilience is a measure of the ecosystem’s ability to absorb changes for its survival. Based on Holling’s definition, resilience is determining the persistence of relations within a system and measuring the ability of this system to absorb changes created in various situations in order to resist various effects and factors. Based on the growth of urbanization and the increasing vulnerability of cities to disasters, significant changes have been observed in the attitude toward risks, as the dominant view has changed from focusing only on reducing vulnerability to increasing resilience against events. Risks around the world have always provided a great challenge in sustainable development, and as a result, some paths to achieve this development by reducing vulnerability patterns are essential and of great importance, and should find a suitable position in urban policies to create suitable conditions to reduce the effective and efficient risk at different levels. Thus, urban areas are considered sensitive areas due to the acceptance of large populations, which has increased the level of vulnerability due to the type of human interaction. Human being considers themselves a part of the place and based on their experiences of signs, meanings, and functions, he imagines a role for the location in his mind [1]. The identification and evaluation of such risks can be considered a good guide in the design of new urban areas and their control to manage urban areas by authorities.

Due to its climatic and geological characteristics and especially Iran’s location on the Alpine-Himalaya earthquake belt, Iran is considered one of the most vulnerable countries around the world; so that the crisis risk index of the United Nations Development Program [2] indicates that, Iran has the highest vulnerability to earthquakes among the countries of the world after Armenia, and 31 of 40 types of natural disasters have taken place in Iran. Natural disasters have always been a great challenge for urban societies, and human settlements and infrastructures have always been endangered. According to statistics, accidents have increased over time and the urban communities’ vulnerability to accidents (namely in developing countries) is increasing. Now, most of the world’s population lives in cities. Major migrations from rural areas to cities and the formation of informal settlements, exposure of the population to unsuitable weather conditions, and other natural disasters are increasing and are great challenges for many cities. Under this condition, resilience, which can mean bouncing back from difficult events, becomes meaningful. In Iran, a country with a high probability of natural disasters and cities with heterogeneous and old textures, resilience is of great importance. One of the most important aspects of urban resilience is physical resilience.

The present study is aimed to measure the components of physical resilience in urban contexts for identifying resilient areas against natural disasters in order to build affordable housing. Affordable housing is a type of urban housing that is planned and built for groups with low- and middle-income socioeconomic levels with different policies. The optimal location of affordable housing is one of the most important planning criteria to build this type of housing [3]. Due to the high vulnerability of groups living in affordable housing, it is required to evaluate the resilience of its construction site in order to prevent the severity of the effect of natural and unnatural damages on this group in the future. On the other hand, presenting affordable housing is important to have a resilient city, and it is necessary to consider some criteria for it [4]. Studies have shown that the appropriate locating of social housing leads to city sustainability [5]. This research attempts to establish a relationship between affordable housing and physical resilience. This chapter is aimed to identify and prioritize the criteria of physical resilience that are effective in selecting a resilient location for the construction of affordable housing. Based on this goal, two questions of research are proposed:

• What are the criteria for resilient locating of affordable housing?

• How is the prioritization of these criteria?

This chapter has five main sections, first, the literature on resilience and resilience in the built environment is reviewed. The second part is related to the research method, in which the AHP model, study area, construction of questionnaire, and weighting of alternatives are done. In the third part, the results are stated, and in the fourth part, the discussion about the prioritization of the criteria and elements is discussed, and the limitations and suggestions of the research are stated. The last part is the conclusion.

2. Literature review

2.1 Resilience

The concept of resilience began in the 1960s and 1970s in the field of ecology. Then it was expanded to different fields of study and resilience became an interdisciplinary concept. The literature identifies two main approaches to resilience. The first approach is “equilibrium” related to the ability of an organism to resist shock and return to its original state, and the second approach is “evolutionary” or “transformational” related to the ability of an organism to continuously adapt to continuous changes in its environment [6]. The emergence of resilience as a driver of urban policy led to a shift toward an integrated and multidisciplinary planning system and quickly became an important urban policy discourse [7]. A city’s ability to absorb disturbances while maintaining its functions and structures is a simple definition of resilience [8].

Resilience studies began in the late 1990s in response to environmental threats by adjusting social and institutional frameworks associated with planning, with a primary focus on physical and infrastructural improvements to prevent disruptions [9].

Resilience, which comes from the Latin root resi-lire meaning the return of spring, was first used by physical scientists. In the 1960s, with the rise of systems thinking, resilience entered the field of ecology, where multiple meanings of the concept have since emerged, each rooted in different worldviews and scientific traditions. The publication of an article in 1973 by a Canadian theoretical ecologist, Crawford Stanley Howling, advanced the concept of resilience, but although the concept of resilience has recently been added to the discourse of planners, it is by no means a new concept. Resilience researchers share a common understanding of resilience as a process involving change over time that produces a desirable outcome for one or more systems or parts of a system. For example, the dynamic interplay between resilience (change) and sustainability has been widely discussed for the first time by C.S. in a field of scientific studies that focuses on interactions between natural environments and human activities as social-ecological systems.

Holling [10] states that resilience is the “persistence of relationships within a system and a measure of the ability of these systems to absorb changes of state variables, driving variables, and parameters, and still persist.”(p. 17) This idea has been extended by many researchers interested in international development studies and social-ecological systems. As Bousquet et al. [11] explain that resilience is “the capacity to cope with change and continue to develop,” (p. 40) whether this development occurs for the survival of fisheries, forests, freshwater ecosystems, or communities dependent on these natural ecologies.

In other sciences, such as physical sciences, the same concept of stability and change is commonly used. For example, in architecture, the term resilience is synonymous with “the process of creating sustainable and successful places that promote well-being, by understanding people’s needs for the places they live and work” [12]. The subject of resilience is also used in psychological sciences. Extensive studies have been conducted on promotional and protective processes. When human biological, psychological, social, economic, and political systems are stressed, the concept of resilience operates.

As a developmental psychologist, Masten [13] is known for evolving the concept of resilience to adopt a more systemic approach. He defines resilience as the capacity of a dynamic system to successfully adapt to disturbances that threaten system performance, viability, or development. This definition can be used for various systems at different interactive levels, both living and non-living, such as microorganisms, children, families, security systems, economy, forests, or global climate. Masten’s definition has much in common with unrelated fields such as disaster resilience, where the focus is on “the ability to prepare and plan for, absorb, recover from, or adapt more successfully to actual or potential adverse events” [14].

Despite the distinction of all these definitions in the function of systems or different parts of systems, they have many similarities. First, resilience is associated with abnormal and stressful perturbations in one or more interdependent systems. Instability is an issue that threatens the system’s capacity to maintain its performance. Second, all resilient systems involve processes to create opportunities for continuity, resilience, recovery, adaptation, or change.

Resilience is context-specific, as is the evolving public health thinking that currently emphasizes “precision public health” by identifying high-risk hotspots and then targeting interventions to their unique contexts. In this way, instead of generalization mechanisms, it seeks to maintain public welfare [15].

The third quality of resilience focuses on the need for sensitivity to the local context, acknowledging the different levels of power of each system (or part of a system) and its capacity to affect the individual or collective well-being of a system (or systems). Overall, this expression of power that leads to trade-offs is always a matter of debate as all the different parts of a system compete for the resources they need to deal with internal and external stressors.

Resilience is demonstrated only when a system functions in a way that is positively valued by its constituents or concurrent systems. In fact, it can be argued that a family that adopts criminal behavior as a way of managing social marginalization or economic adaptation to modernization in order to maintain its livelihood may be considered resilient from the perspective of those who benefit from these patterns [16].

Although the three definitions of resilience (i.e., exposure to an unusual disturbance, contextual specificity of protective processes, and negotiated outcomes) may seem abstract, in practice, resilience is a response to a disturbance that alters patterns of adaptation. Creates that favor some sectors. More than others, resilience has been the basis for a vast amount of study in many different disciplines. For example, Annarelli and Nonino [17] used Hollings’ work on social-ecological systems to examine the resilience of supply chains. These include other environmental systems (for example, disruptive weather and political conflicts can be disruptive to supply chains) and the contemporary methods used by management (for example, labor strikes and poor financial decisions can affect the planned production of goods and services). Although the only desirable outcome of supply chain resilience may seem to be sustainable production (recovery), it must be said that a return to business as usual can be a very limited understanding of resilience.

2.2 Resilience in the built environment

The literature on resilience in the built environment can be expressed in three main paradigms: first, disciplines related to architecture, urban design, and planning. Second, combining ecosystem sciences with architecture and urban design. And third, resilience is embodied in architecture and built form. The first resilience paradigm is used as a model developed by architectural engineers, urban design, and planning.

The second resilience paradigm was shared as a theme between the disciplines of architecture and ecology. The third paradigm is also used as general knowledge individually and collectively through trial and error, learning, and memory. In the first paradigm, especially in areas with a high earthquake or hurricane risk, resilience thinking is used by combining contemporary practices of built environments with scientific approaches such as material physics and engineering resilience [18].

Hassler and Kohler [19] stated that the urban context is a complex socio-technical system with different time constants, actors, and institutional regimes that includes different scales such as buildings, neighborhoods, cities, and regions. They also used the term-built environment to refer to an artifact in an overlapping zone between culture and nature, with causality in both directions, referring to the relationship between the built and unbuilt parts of the environment. Pickett et al. [20] state that “resilient cities” are a metaphor for the integration of ecological, socio-economic, and planning realms. While metaphors have explanatory power for interdisciplinary discussions and can stimulate creativity around shared concepts and perspectives, metaphors are slippery figures of speech.

Resilience as an inclusive and open metaphor links the new non-equilibrium paradigm of ecosystem science with the dynamics of architecture, design, and urban planning, acknowledging that ecosystems are either externally regulated or have multiple or unstable state(s) or may have a dynamic state and possible disorder.

Belsky et al. [21] state that the trade-off that households make to reduce housing costs, such as transportation, access to public services, health and safety, is accounted for an ideal affordability assessment. Rowley [22] shows that in reality, housing affordability involves quality and location trade-offs. Monetary costs and socio-economic costs, which are hidden by traditional measures of affordability, are imposed on households by such trade-offs. It is clear that it is difficult and perhaps impossible to address all the concerns related to housing affordability, such as physical quality, location, access to services, and fit, in a simple measure, and they need to examine additional supplementary indicators [23].

3. Materials and methods

3.1 Development of the AHP model

The present study is based on the descriptive-analytical method. The documentary (library) method was used to explain the literature and records of the research subject and to determine the effective factors on physical resilience. Then, physical resilience indices were extracted for the location of affordable housing, based on theoretical justification. In this study, the combination of two important and highly applied mathematical models, i.e., fuzzy logic and hierarchical analysis process, has been used in order to rank indices. This ranking was performed using the AHP method with Expert choice v.11 software.

The AHP method was first presented by Saaty [24]. AHP is a multi-criteria decision-making method based on statistical data and a hierarchical structure. Normally, this method is designed to rank limited alternatives that have limited features. This method is used to eliminate probable errors for certain decision criteria. According to Saaty [25], the three main stages in the AHP approach include problem analysis, comparative analysis, and preference synthesis.

The components that best define the features of a resilient location for the construction of affordable housing are presented in a three-layer hierarchy of the AHP model (Figure 1), in which the top layer is the relevant goal, the second layer is the criteria, and the third layer is components.

Figure 1.

AHP model used in the process of prioritizing criteria for resilient location for affordable housing.

The second layer consists of five physical resilience criteria, which include Surrounding Uses, Region Context, Natural Environment, Infrastructure & Services, and Open & Public Spaces. The elements of each measure of resilience are also the last layer.

This model was developed according to the literature review and expert approval. In this way, first, the resilience criteria were collected and categorized, then in order to coordinate with the issue of affordable housing, it was given to 10 architecture and urban planning experts (including university professors and doctoral students) for judgment. The criteria that all the experts approved were chosen as the final criteria of resilience in locating affordable housing. Since this kind of housing is built for society’s low- and middle-income groups, its site should be chosen in such a way that it has physical resilience in critical conditions. So, it would be cost-effective and does not impose high costs on its residents in times of profound changes. On the other hand, it will be easier for these vulnerable residents to be stable and adapt to post-crisis conditions.

The criteria of physical resilience and the relevant components are obtained by evaluating the background and categorized in Table 1. According to Lanagarneshin et al. [29], the physical-environmental indices of resilience include green and open space, appropriateness of uses, characteristics of the land (ground), building resistance, access, and density. Pashapour and Pourakrami [30] consider the physical dimensions of urban resilience as uses and characteristics of the surrounding context, access to urban facilities, rescue centers, parks, and open spaces. Delshad et al. [26] state that physical resilience against earthquakes can be measured with some criteria such as physical resistance, road network, infrastructural facilities and services, and the condition of open space. In their research, Farhadi et al. [27] introduced the physical measures affecting resilience by the uses surrounding the fabric, urban infrastructure including roads, crisis centers, and water supply, and access to open space. The dimensions of physical resilience against natural disasters have been presented by Ghasemi and Gharaee [28], resilience of place (feature of the land, distance from the river, etc.), resilience in the mental image (security …), legal resilience (observing safety principles in constructions), structural resilience (building frame, roof lightness, etc.) and functional resilience (building density, width of roads, etc.). According to Desouza & Flanery [33], it is important to consider the characteristics of the fabric and access to roads and urban transportation in the design, planning, and management of resilient cities. Rezaie et al. [32] considered criteria in four structural-physical, socio-economic-cultural, spatial-functional, and structural-natural dimensions for analyzing the resilience of urban land use in Tehran. These criteria include the condition of buildings, the condition of relief and services, access network, employment centers, active population, population density, open and green space, worn texture, access to commercial uses, health and urban facilities and equipment, land bed and surface water. Abdullah et al. [46] evaluated the physical resilience in Tehran (Iran) with the indicators of population and building density, roads, worn-out texture, green and open spaces, health centers, crisis headquarters centers, and natural bed characteristics. Chen et al. [34] evaluated some indices such as topology, rate of green space, proximity to the river, building age, availability of medical facilities, and public services in the resilience of affordable housing. Regarding location resilience, Lyon [38] referred to the importance of infrastructural measures and public services during a crisis. In his research, Adger [35, 42] considers access to facilities such as roads, medical centers, and retail as important factors in resilience. In research on resilience in coastal areas, Orencio & Fujii [39] mentioned access to neighborhood facilities and road transportation as important in physical resilience. Pokhrel [40] evaluated green space in the resilience of the urban environment. He believed that access to roads for transportation is very important, especially during the crisis. Zhang et al. [41] consider urban resilience against climate change as dependent upon infrastructure criteria such as public services, transportation, and health use, access to infrastructure equipment, and crisis management. In their review research, Assarkhaniki et al. [37] considered the physical measures of resilience including access to road infrastructure, medical and educational centers, as well as urban infrastructure equipment and services during a crisis.

Reference	Elements	Criteria
[26, 27, 28, 29, 30]	Congruity of surrounding uses	Surrounding Uses
[27, 31, 32, 33]	Buildings age (New, middle, worn, old)	Region Context
[26, 28, 29, 30, 31, 33]	Building density
[29, 30, 31, 32, 34]	Proximity to parks & green spaces	Natural Environment
[28, 32, 34]	Proximity to superficial water (rivers, …)
[28, 29, 32, 34]	Topography, Slope & Soil endurance
[26, 27, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41]	Efficient roads & public transportation (accessibility routes)	Infrastructure & Services
[30, 31, 32, 34, 35, 37, 41, 42]	Access to health care use
[32, 35, 42]	Access to commercial use and retails
[37]	Access to educational use
[27, 30, 31, 38]	Rescue and security facilities (Emergency, Police, Firefighting), The number of crisis headquarters centers
[26, 27, 28, 32, 37, 38, 41]	Pipelines, urban equipment, access to and supply of water sources
[26, 27, 28, 29, 30, 32]	Access to open space	Open & Public Spaces
[43, 44, 45]	Access to public space

Table 1.

Physical resilience criteria and the relevant elements.

A brief description and definition of each criterion and elements are given in Table 2.

Description	Elements	Description	Criteria
Coordination of surrounding uses with the site	Congruity of surrounding uses	Parcel of land with different use around athe site	Surrounding Uses
Quality of the building based on the construction time	Buildings age (New, middle, worn, old)	Surrounding building conditions in the area	Region Context
Ratio of building structures per acre	Building density
Number of parks & green spaces in the vicinity of the site	Proximity to parks & green spaces	Non-human-made surroundings and conditions	Natural Environment
Number of rivers or other superficial water in the vicinity of the site	Proximity to superficial water (rivers, …)
The chosen land (site) physical conditions	Topography, Slope & Soil endurance
Efficient connectivity to city areas with appropriate roads and transportation	Efficient roads & public transportation (accessibility routes)	City infrastructures and facilities that are accessible for the site	Infrastructure & Services
Site proximity to health care use (clinic, hospital, …)	Access to health care use
Site proximity to commercial use and retails (mall, grocery, …)	Access to commercial use and retails
Site proximity to schools, universities…,	Access to educational use
Site proximity to Rescue and security facilities and crisis headquarters centers	Rescue and security facilities (Emergency, Police, Firefighting), The number of crisis headquarters centers
Site accessibility to some equipment	Pipelines, urban equipment, access to and supply of water sources
Site proximity to open spaces among outside buildings	Access to open space	Any urban ground space with unrestricted access	Open & Public Spaces
Site proximity places of public use (park, square, …)	Access to public space

Table 2.

Description of criteria/elements.

^a

Affordable housing site.

3.2 Reliability and validity

Before the conduction of the survey on the developers, validation, assessment, and rationality of the questionnaire was carried out. This was achieved with the aid of practitioners and studies lecturers; they evaluated the questionnaire in order to put off the anomaly of expression and make sure relevant terms are used primarily based on the peculiarity of physical resilience. The questionnaire became finalized based totally on the form of comments. Information reliability testing revealed a Cronbach alpha rate of 0.79 for the 24 identified elements. This is a little greater than the boundary of 0.70. The collected records are remarkably dependable for further statistical evaluation.

3.3 Study area and local decision-makers

The prioritizing process of the resilience components of affordable housing was performed in Mazandaran province (Figure 2). The familiarity and experience of these specialists with Mazandaran and the resilience resources in its cities was the main reason for selecting them. These members from the academic environment and local government (with specialized responsibilities in this field) were selected as decision-makers during the prioritization of resilience components due to their experience, skills, knowledge, and activities related to the topic. The questionnaire was distributed among 22 experts (See Appendix 1 and 2). Experts’ profiles are shown in Table 3.

Figure 2.

Map of the study area, Mazandaran province, Iran.

Variable	Type		Distribution
Role	Academic	Ph.D. Candidate	5 (22.7%)
		Ph.D. (University Prof.)	10 (45.5%)
		Post-doc	1 (4.5%)
	Local government		6 (27.3%)
Age	30–40		6 (27.3%)
	41–50		9 (40.9%)
	Up to 51		7 (31.8%)
Gender	Male		13 (59%)
	Female		9 (41%)
Years of experience	5–10		7 (32%)
	Up to 10		15 (68%)

Table 3.

Profiles of the participants in the analytic hierarchy process (AHP) study.

Lam and Zhao [47] argued that AHP survey is an unusual approach for research associated with a particular trouble; subsequently the adoption of a massive sample is not always imperative. Tavares et al. [48] argued that the peculiarity of AHP makes judgment from one professional be deemed ok. On the contrary, Cheng and Li [49] advised that the adoption of a big sample size for an AHP examine can also result in inconsistent judgment, as many professionals may additionally provide arbitrary consequences. The peculiarity of AHP in housing research and construction studies might be tied to its functionality to cope with small pattern sizes. Research [50, 51, 52] has followed respondents starting from four to nine even as others used a pattern size of 20 to 30 [53, 54]. As most of the people of the research followed a small sample size, it is imperative that to allow beneficial decisions, regular outputs and models, the adoption of a small pattern size is most desirable. Therefore 22 developers from the overall survey with over 6 years’ experience in sustainable housing were selected to take part within the AHP survey.

3.4 Weights of alternatives in a consistent matrix

The paired comparisons are a key step in AHP to prioritize the weights of locating factors. Thus, based on different factors, the alternatives are scored. This process simultaneously focuses on two factors and their relations with each other. The relative importance of each factor is measured via a numerical measurement scale [55]. According to the AHP model, the identification of important criteria and components of resilience in affordable housing locating was performed using paired comparisons and ratio-scale measurement, which is explained as n(n-1)/2, where n denotes the components in a prioritization judgment [56]. In this research, 10 comparisons in a matrix are defined for 5 criteria, while the comparison of criteria components formed 90 questions. Each output of a paired comparison shows the decision-maker’s preferences for one alternative over the others based on a set of scales (Table 4) that include scales from 1 to 9 [24, 56].

Scale	Judgment of preference	Description
1	Equally important	Two factors contribute equally to the objective
3	Moderately important	Experience and judgment slightly favor one over the other
5	Strongly important	Experience and judgment strongly favor one over the other
7	very strongly important	Experience and judgment very strongly favor one over the other, as demonstrated in practice
9	Extremely important	The evidence favoring one over the other is of the highest possible validity
2.4. 6, 8	Intermediate preferences between adjacent scales	When compromise is needed

Table 4.

Rating scale for judging preferences used for the pair wise comparison of various physical resilience criteria in affordable housing locating.

When alternative i was considered extremely important compared with alternative j, the calculation matrix score was based on aij = 9 and aji = 1/9. The distribution of these scores in a square matrix resulted in a reciprocal matrix [57], represented as:

$$A=\left[a_{\mathit{ij}}\right]=\left\{\begin{array}{ccc}1& a_{\mathit{ij}}\dots & a_{1n}\\ 1/a_{\mathit{ij}}& 1\dots & a_{2n}\\ ⋮& ⋮& ⋮\\ 1/a_{1n}& 1/a_{2n}\dots & 1\end{array}\right\}$$E1

where A = [aij] is a representation of the intensity of the decision-maker’s preference for one over another compared alternative aij and for all comparisons i,j = 1,2,…n. Decision-makers facilitated the comparisons of alternative criteria or elements in rounds till the ratings had been taken into consideration strong. Stability was reached while a certain consensus on a sum of rankings became done [39].

Consistency test: This test is conducted to check the judgment consistency. This test guarantees that best steady matrixes are covered in similarly evaluation. The formulation utilized in calculating the best eigenvalue and vector is:

$${\lambda }_{\mathit{max}}=\sum _{j=1}^m\frac{\mathit{Aw}}{\mathit{Mw}1}\left(i=1,2,\dots ,m\right)$$E2

Where λmax represents matrix the highest eigenvalue, A denotes the pairwise matrix; w stands for the matrix of weights of elements, and wi stands for the element’s weights. The consistent level of the judgment was determined using the Consistency Ratio (CR) which was computed by the formula:

$$\mathrm{CR}=\frac{\mathit{CI}}{\mathit{RI}}=\frac{1}{\mathit{RI}}\left(\frac{{\lambda }_{\mathit{max}}-m}{m-1}\right)$$E3

Here, CI uses an integrity index. CR is the consistency ratio. RI represents the random index and m represents the amount of CSF in the matrix.

Weight calculation:

CSF weights were determined by estimating the eigenvector matrix and a measure of the consistency of judgment is obtained by computing the maximum eigenvalue. In the AHP study, we calculated CSF weights at each stratum level to establish priority among elements. This was acquired through:

$$n_i=\prod _{j=1}^m\mathit{aij}\left(i=1,2,\dots ,m\right)$$E4

Where ni represents the multiplication of the relative importance for each row of CSFs; aij represents the relative importance of the CSFs “i” were compared with CSFs “j” and m represents the number of CSFs in the matrix. Vector wi was calculated by:

$$w_i=\sqrt[m]{{\overline{n}}_i(i=\left(1,2,\dots ,m\right)}$$E5

Where wi represents the m^th power of ni:

$$w_i=\frac{w_i}{{\sum }_{i=1}^m{w}_i}\left(i=\overline{1},\underset{¯}{2,}\dots ,m\right)$$E6

The weights of the CSFs were calculated by normalization of the vector: where wi stands for weights of CSFs and criteria.

3.5 Consensus building

To acquire consensus on ratings in a paired comparison of variables in the AHP model, the Delphi method became selected as a powerful technique in a multilateral decision-making procedure. But the technique needed a robust facilitator that would coordinate the distinct views of the decision-makers toward a single objective. Regardless of comparable experiences, social status (e.g., education), and engagement level with the issue of resilience among respondents, the results confirmed differences in perspectives about each variable.

The Delphi method was of great importance during the comparison of the variables and the level of each one. Decision-makers tended to consider variables as having similar goals, which made comparisons difficult. The facilitator’s role was to interpret the differences between the variables and to organize the respondents’ views. Thus, the group managed to discover a common perspective for the superiority of each variable in paired comparisons.

The use of a quantitative base scale (Table 2) helped the respondents in scoring each pairwise comparison, especially when the number of variables of each criterion was above two. To make scoring easier, the variables were placed in the table in front of each other and the scores (1 to 9 on each side) were between them.

The agreement on the final scores was obtained from a pairwise comparison of criteria and components using Delphi technique. Final scores were calculated based on the geometric mean of all scores given by the decision-makers for each pairwise comparison. When consensus was achieved, a summary of the final scores for each pairwise comparison was entered into a matrix or decision table.

4. Results

4.1 Selected criteria and elements

The comparison matrix at the criterion level was consistent with a value of 0.08 (Table 5). Based on the weights of alternatives at this level, Infrastructure & Services (IS) and Surrounding Uses (SU) were ranked as the highest and lowest criteria, respectively. The highest ranked criteria, i.e., Infrastructure & Services (IS), Region Context (RC), and Natural Environment (NE), were selected by the sum of their weights and accounted for 85% of the overall weights of the criteria being compared. Their attribute elements were then subjected to further comparison, and high-ranking elements were subsequently selected.

Codes	Criteria	Weight	Rank
SU	Surrounding Uses	.052	5
RC	Region Context	.184	2
NE	Natural Environment	.102	3
IS	Infrastructure & Services	.564	1
OPS	Open & Public Spaces	.098	4

Table 5.

Normalized Weights and ranks of various criteria of a resilient location of affordable housing.

For Infrastructure & Services (IS), the elements that characterized resilient location for affordable housing were IS1, IS2, IS3, IS4, IS5, and IS6 which accounted for 75% of the overall alternatives (Table 6). Among its elements, IS5 accounted for 30% of the most important attributes that describe the resilient location. The matrices of comparisons for these attribute elements fell within a CR value of 0.10 and 0.09, respectively.

Criteria	Elements of resilient location of affordable housing		Weights	Rank
SU	SU1	Congruity of surrounding uses	.021	11
RC	RC1	Buildings age	.025	10
	RC2	Building density	.076	5
NE	NE1	Parks & green spaces	.006	14
	NE2	Proximity to rivers	.042	6
	NE3	Topography & Slope & Soil endurance	.28	9
IS	IS1	Efficient roads & public transportation	.164	3
	IS2	Access to health care use	.182	2
	IS3	Access to commercial use and retails	.033	8
	IS4	Access to educational use	.018	12
	IS5	Rescue and security facilities, the number of crisis headquarters centers	.233	1
	IS6	Pipelines, urban equipment, access to and supply of water sources	.123	4
OPS	OPS1	Access to open space	.040	7
	OPS2	Access to public space	.007	13

Table 6.

Normalized Weights and ranks of various elements that characterized the selected criteria to produce a resilient location of affordable housing.

Subsequent procedures for selecting and evaluating attribute elements were conducted for Region Context (RC), and Natural Environment (NE). For Region Context (RC), the elements RC1, and RC2 were selected as elements that describe the resilient location of affordable housing, in which, RC2 is a more important element (Table 6). For Natural Environment (NE), the elements NE1, NE2, and NE3 were selected to represent elements that described the resilient location of affordable housing, in which, NE3 is the most important element.

5. Discussion

5.1 Priority criteria and elements

Infrastructure & Services (IS) was the most important criterion for finding a physically resilient location for setting the affordable housing because the existence of some infrastructure is crucial to the resilience of residential projects.

Among the variables of service and infrastructure, rescue and security facilities, access to health care use, efficient roads & public transportation, and urban equipment were the most important, respectively. Urban—water infrastructure, sewage, energy, communication and transportation systems—are of great importance in emergency response and rapid recovery of the community and its economy. Critical systems should be designed so they are not destroyed by natural risks. The transportation infrastructure network and the structural reliability of the network components (roads and bridges) are the most important measures of physical resilience [26, 58, 59, 60]. Proximity to suitable rescue uses includes crisis management centers and health uses. The logical location of the main components of the city and the logical relationships between them help to create a resilient region. On the other hand, the damage to infrastructural facilities such as water, electricity, and gas networks can greatly increase the damages caused by earthquakes in the city [26]. Some of the utilities in the city play a great role in the city’s vulnerability to natural disasters. These uses are known as special uses including schools, universities, hospitals, rescue centers, urban management centers, factories, and fuel tanks [30].

Region Context (RC) represents the physical condition of context that has surrounded an affordable housing project. The degree of security of discrete context against natural disasters is higher than the degree of security of continuous context. The more regular the segmentation pattern and the less obtuse angles, the less the degree of vulnerability. Section area, section length, and width proportions in relation to land use and ownership type will be effective in the vulnerability factor or context efficiency [61]. If there are worn-out contexts in the area, strengthening, restoring, restoration, and renovating these old contexts seem necessary. Due to its direct relationship with population density, the density of living collections indicates the number of financial losses and life losses in the earthquake and the increase of the crisis. The relationship between population density and earthquake impacts is complex. Based on the inductive and reasoning method, it is obvious that population density is not effective on the intensity of destruction, but the importance of densities is related to the occurrence of destruction [62]. As the building gets older, the resilience is reduced.

Natural Environment (NE) describes natural resources in the vicinity of affordable housing project sites which affects the resilience of the location. It reflects the degree of vulnerability to flooding, waterlogging, and proximity to the river in the affordable housing area. The topography is characterized by the difference between the highest topography and the lowest topography within the community. Topography and land slope are important factors in guiding surface water in case of danger [34].

Open & Public Spaces (OPS) and Surrounding Uses (SR), are respectively the least important criteria at the time of finding a resilient location for affordable housing construction. Access to suitable open spaces to escape from dangerous factors and access to safe places, the possibility of quick and safe escape and shelter, facilitating relief and rescue operations after the earthquake, speeding up cleaning operations are essential. Therefore, it is the degree and quality of open spaces that can act as the additional element of destroyed buildings and infrastructures in the event of an earthquake crisis, therefore, open spaces play a crucial role in the physical resilience of space against earthquakes [26, 27, 32]. If the ratio of green space is high, the regulation ability of rainwater infiltration is also good [34]. Moreover, green spaces are important components of the urban landscape and improve the physical, psychological stress relief center and improve social harmony through social interaction and recreation. Further, these green spaces help to protect urban biodiversity to protect urban landscape through mitigation and adaptation of adverse impacts of climate change, through heat reduction and cooling effects. In the same way, the green space also helps to maintain the hydrology around the city, provide emergency shelter, and many more [40].

5.2 Limitations of the proposed criteria and future research

The result of this research demonstrates that the AHP model can provide a framework to assist decision-makers in analyzing various location factors, evaluating location site alternatives, and making final location selections based on resilience. One of the limitations of the research is the sampling of decision-makers. Due to choosing the north of Iran as the study area, experts from this region of the country were selected to respond to the AHP questionnaire. It is required to perform a survey in other geographical locations with larger and different groups of experts.

In this research, only the discovery and prioritization of resilience criteria were discussed. Thus, it is necessary to evaluate these prioritized criteria in the real environment to select a suitable site for the construction of affordable housing or to evaluate the resilience of existing affordable housing projects in future research. Social criteria are also the factors affecting the resilience of affordable housing. Hence, it is necessary to examine the criteria of social resilience and their relationship with the physical criteria of resilience in selecting an affordable housing site. Future research extensions could also investigate the impact of changing input parameters such as measurements and the importance of location factors. Further studies of sensitivity analyses on the effects of changes in decision-maker preferences are needed, as changes in decision-maker preferences can affect the attractiveness of a particular place.

6. Conclusions

The issue of housing is one of the most important parts of development in a society, which has a great impact on the health and view of the society, with its great economic, social, environmental, and physical dimensions. Today, despite many advances, problems in the housing sector are one of the challenging issues of developing countries, such as internal migrations, problems of land supply, inadequate resources, weak economic management, lack of comprehensive housing planning, and other inefficiencies which exist in the economic infrastructure of these countries, on the one hand, and the rapid increase of the urban population, on the other hand, has turned to present shelter in these countries into an unsolved problem. Above all, the low quality of urban housing in the cities has led to the vulnerability of housing and their lack of resilience against all kinds of accidents and based on the available statistics, there are many casualties of life and loss of citizens due to the low quality of buildings and lack of resilience. Evaluating housing indices is one of the various recognized tools and methods of housing characteristics, which can be used to identify the effective procedures of housing. Based on the low percentage of durable houses in Iran, the need to evaluate resilience in physical indices is intensified, especially in times of crisis. Due to the strong role of cities in the loss of lives and financial aspects of citizens, urban crisis management theories with emphasis on making the city resilient and especially the resilience of urban houses have turned into an important strategy for cities in less than a decade, because the housing sector is of great importance as one of the great topics in this strategy.

In this chapter, by extracting the physical components of resilience and measuring the opinions of experts, the prioritization of the components and indices of physical resilience in urban areas for the location of affordable housing was considered. In order to respond to the research questions, the components affecting physical resilience are services and infrastructures, the context of the region, the natural environment, open and public spaces, and the surrounding uses, respectively. In the services and infrastructure components, the highest impact factor is related to access to rescue and security facilities, the number of crisis headquarters centers and smart infrastructures, and access to health facilities. In terms of the effect of physical indicators on the resilience of urban areas, research results are consistent with research results [26, 27, 30, 32, 58, 59, 60, 61]. The important point of this research compared to previous research is that it has focused on identifying the most resilient urban land to build affordable housing by identifying and prioritizing the physical components of resilience in those areas with the neighboring context which can be the basis of a strategic document for the location of affordable housing lands at the macro level. Creating resilience needs cooperation and communication between organizations and stakeholders, adapting the management institution to the ecological scale of the resource, and preventing section-based analysis. It is rarely possible to find and even build a city that completely has resilience components and indices, but what is important is the will of these cities and their urban management and their step-by-step movement toward prepared cities and getting closer to resilient cities. In order to achieve this purpose, the campaign to construct resilient cities is presenting guidance and helps city managers evaluate the current situation of cities based on the approved standards of prepared and resilient cities, and also it attempts to parallel the growth and development of cities and moving them on the path of resilient cities.

Acknowledgments

This research work has been supported by a research grant from the University of Mazandaran.

Conflict of interest

“The authors declare no conflict of interest.”

A.

Dear respondent: Thank you for taking the time to complete this questionnaire. The following questionnaire has been prepared for “locating affordable housing with approach of physical resilience.” Please complete it. Thank you for your sincere cooperation.

Age: …

Gender: Male □ Female □

Field of study: Architectural Engineering □ Urban Engineering □

Education level: Ph.D. Candidate □ Ph.D. □ Post-doc □

Role: …

* Description: In this questionnaire, please, as an expert, determine which criterion and to what extent do you think is more important for locating low-income housing. Criteria and sub-criteria in this study are:

1. Surrounding Uses (Congruity of surrounding use).

2. Region Context (Buildings age (New, middle, worn, old); Building density).

3. Natural Environment (Proximity to parks & green spaces; Proximity to superficial water (rivers, …), Topography; Slope & Soil endurance).

4. Infrastructure & Services (Efficient roads & public transportation (accessibility routes); Access to health care use; Access to commercial use and retails; Access to educational use; Rescue and security facilities (Emergency, Police, Firefighting); The number of crisis headquarters centers; Pipelines, urban equipment, access to and supply of water sources).

5. Open & Public Spaces (Access to open space; Access to public space).

* Please compare these criteria to find out which one is more important than the other and how important it is. Please rank between 1 and 9.

Dear respondent: Thank you for taking the time to complete this questionnaire. The following questionnaire has been prepared for “locating affordable housing with approach of physical resilience.” Please complete it. Thank you for your sincere cooperation.

Age: …

Gender: Male □ Female □.

Field of study: Architectural Engineering □ Urban Engineering □.

Education level: Ph.D. Candidate □ Ph.D. □ Post-doc □.

Role: …

* Description: In the comparison of criterion j with criterion i, if the importance of both criteria is the same, mark the number 1. If the criterion on the right was more important, the number on the right should be chosen as much as it is more important. But if the number on the left is more important, mark the number on the left. Be careful to only mark the number of one side (the side of the item that is more important).

Sub-criteria (elements)	Priorities																	Sub-criteria (elements)
Buildings age (New, middle, worn, old)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Building density	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Proximity to parks & green spaces	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Proximity to superficial water (rivers, …)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Topography, Slope & Soil endurance	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Efficient roads & public transportation (accessibility routes)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Congruity of surrounding uses
Building density	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age (New, middle, worn, old)
Proximity to parks & green spaces	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Proximity to superficial water (rivers, …)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Topography, Slope & Soil endurance	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Efficient roads & public transportation (accessibility routes)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Buildings age
Proximity to parks & green spaces	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Proximity to superficial water (rivers, …)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Topography, Slope & Soil endurance	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Efficient roads & public transportation (accessibility routes)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Building density
Proximity to superficial water (rivers, …)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Topography, Slope & Soil endurance	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Efficient roads & public transportation (accessibility routes)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to parks & green spaces
Topography, Slope & Soil endurance	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Efficient roads & public transportation (accessibility routes)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Proximity to superficial water (rivers, …)
Efficient roads & public transportation (accessibility routes)	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Topography, Slope & Soil endurance
Access to health care use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Efficient roads & public transportation (accessibility routes)
Access to commercial use and retails	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to health care use
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to health care use
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to health care use
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to health care use
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to health care use
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to health care use
Access to educational use	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to commercial use and retails
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to commercial use and retails
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to commercial use and retails
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to commercial use and retails
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to commercial use and retails
Rescue and security facilities, the number of crisis headquarters centers	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to educational use
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to educational use
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to educational use
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to educational use
Pipelines, urban equipment, access to and supply of water sources	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Rescue and security facilities (Emergency, Police, Firefighting), The number of crisis headquarters centers
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Rescue and security facilities, The number of crisis headquarters centers
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Rescue and security, The number of crisis headquarters centers
Access to open space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Pipelines, urban equipment, access to and supply of water sources
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Pipelines, urban equipment, access to and supply of water sources
Access to public space	9	8	7	6	5	4	3	2	1	2	3	4	5	6	7	8	9	Access to open space