Revisiting Urban Resilience: A Review on Resilience of Spatial Structure in Urban Refugee Neighborhoods Facing Demographic Changes

Providing a durable and sustainable approach based on urban resilience is essential for solving many spatial challenges in neighborhoods with sudden refugee influxes. As refugees settle in different locations in host cities, many of these neighborhoods have high urbanization, poor infrastructure, and over-population and their conditions impact their urban stability, livability, and quality of life. Hence, this study will review the urban resilience literature focusing on a set of resilient spatial elements of a neighborhood to support the design and planning of refugee settings. First, the theories of urban resilience are reviewed to identify the characteristics of resilience and classify the reviewed literature by different focused categories of spatial resilience. Second, the resiliency of spatial structure are explored focusing on the links between resilient characteristics and urban form attributes at the neighborhood scale. The review summarizes a set of resilient spatial measurements that use urban form indicators of resilient characteristics facilitated by geospatial technologies. Further, a framework of resilient spatial structure for refugee neighborhoods is proposed using existing urban resilience frameworks. The proposed framework includes factors of urban form attributes at the neighborhood scales (e.g., blocks, plots, and building scale), resilience in refugee contexts, and urban resilience mechanisms. The study is not limited to providing an operative resilience knowledge. It provides spatial strategies for humanitarian organizations and inter-governmental agencies to improve the vulnerable spatial structures of refugee settings and to broaden opportunities for the assessment, profiling, communication, monitoring, and planning of resilient refugee neighborhoods.

Introduction

The world faces complex humanitarian emergencies including warfare (Shaluf, 2007). The crisis of warfare threatens safety, wellbeing, health, and security of communities and individuals (Coalition, 2013). The main features and consequences of warfare are decades of displacements and millions of Forced Migrants (Newman and Van Selm, 2003). This mass displacement of Forced Migrants causes permanent or semi-permanent changes of residence due to the continued existence of the crisis.

While not an international legal concept, Forced Migration includes refugees, internally displaced people (IDPs), asylum seekers, and others (Castles, 2003). Refugees flee their origin country and cross international borders, and cannot return home often due to wars, persecution, and violence (Kennedy, 2008). Currently, there are many refugee settlements in the world but more specifically in developing countries (McAdam, 2018). They settle in scattered refugee camps or urban neighborhoods in cities of host countries and transform these locations physically, socially, and economically. In fact, according to some sources, about 60% of refugees are classified as urban refugees who live in urban areas of host cities (Park, 2016). Therefore, refugees create sudden and rapid stress on urbanization with unexpected economic activities, uncertain political issues, and new social fabrics.

The relationships between refugee communities, host cities, and inter-governmental organizations are complex. In general, refugees are described as invisible, hidden, and marginalized. Refugees as a disadvantaged community suffer from economic frustrations and exclusion (Valtonen, 2004; Blocher and Gulati, 2016). Unfortunately, children and women make more than 50% of refugees (DATA, 2019), who face health problems, psychological disturbances (Fazel and Stein, 2003), and identity issues (Smith, 2013). A critical challenge is identifying the conditions of refugee settings for proper considerations in the official management of these settings (Sajjad et al., 2020). Often, refugee neighborhoods face spatial challenges such as a lack of urban services, accessibility, and spaces for social activities due to a sudden increase in population (Blank, 2019; Tsavdaroglou, 2020). Therefore, there is an urgent need to study refugee situations to understand their everyday experiences, struggles, and aspirations.

To fill-in the gap, this study focuses on examining the spatial conditions of refugee neighborhoods in host countries. It aims to help build some knowledge on how urban resilience can contribute to the improvement of these neighborhoods. Traditional refugee protection procedures and solutions include quick and short-term responses focused on basic needs. These procedures and solutions show the discontinuation between the reality of refugee living and official policies and practices. In contrast, urban resilience is a more long-term solution that prepares the urban system for any future disturbances. So far, the resilient approach has been inadequately explored concerning refugee settings and their spatial structure in relation to the specific stress of demographic changes. Therefore, this research will develop and apply tools and techniques to improve urban resiliency using spatial structures. Moreover, the qualities of resilient urban system should help decision-makers understand the importance of spatial resilience while preparing for refugee influxes, and help international organizations think beyond the current protection strategies to develop urban resilience.

In this article, the literature is reviewed exploring urban resilience and resilient urban form. It contains an overview of urban resiliency types, approaches, characteristics, solutions, and measurements focusing on urban form. It also contains the social aspect of urban resilience. Additionally, it reviews the conceptual frameworks pertaining to urban form resilience associated with refugee neighborhoods.

Resilient Urban form of Refugee Neighborhoods

The main reason for the vulnerability of the refugee context is sudden refugee influxes that shape cities as these cities continue to accept uncertain numbers of these influxes at unexpected intervals as long as the reasons for the crisis continue to exist (Kirbyshire et al., 2017). Thus, the refugee setting is one of non-equilibrium urban formation (Sullivan and Homewood, 2003) where pressure and demands on urban systems and components including housing and urban services exist. Therefore, this study considers the resilient urban form of refugee neighborhoods in the following three research domains: Urban Resilience or Resilient Urban Form, Urban Forms of Refugees, and Resilience of Refugee (Figure 1).

FIGURE 1

Figure 1. The three research domains.

The study focuses on the resilient urban form because an adequate response to population influx challenges is important to prepare the urban system, sub-system, and components (Kirbyshire et al., 2017). In this regard, the literature on urban refugees in cities shows their neighborhoods with low accommodation standards, informal processes, and poorly designed overcrowded housing (Alhusban et al., 2019). The literature also shows poor public transportation, less accessibility to amenities, and a lack of open spaces (Alhusban et al., 2019). Moreover, refugees influence their urban form settings with physical and spatial characteristics of their previous neighborhoods for a better sense of place (Mazumdar et al., 2000). Therefore, refugee waves change and transform the social context in an incoherent manner and the physical context with informality and unknown architectural styles.

In the domain of “resilience of refugee,” resilience expands to empower refugees by including specific resilience strategies accounting for behaviors, resources, components, and conditions to work in refugee settings (Netto et al., 2021). The resiliency approach provides an opportunity for a more suitable solution for all residents while preparing the urban system, sub-system, and components for population influx challenges (Kirbyshire et al., 2017). More particularly, a community resilience approach enhances the relationship of the people-place relationship as part of the integrated approach of refugees in their urban contexts and building their social capital (Berkes and Ross, 2013; Tippens, 2020). Eventually, the main objective for the resilience of refugees is a reduction of risks using urban resilience in their geographic places.

This study develops a conceptual framework that is based on the literature review of the three domains. The flow diagram in Figure 2 helps understand the three domains of the framework. The framework shows the resilient urban form domain as three temporal phases: pre-, during-, and post-disaster or disturbance. Resiliency has different functions in these temporal phases related to maintenance and resistance, recovery, adaptation, and transformation. In the resilience of refugee domain, the refugee contexts can employ resilience concept in many physical, community, individual, economic, and policy aspects. The aspects involve different agents and their institutions including refugee and citizen population besides host governments and humanitarian organizations. Meanwhile, the urban form of refugee domain consists different refugee settings namely: refugee camps, urban refugee neighborhoods, and refugee resettlement areas. However, the article will focus on engaging resilience in physical structures due to refugee influxes and consequent demographic changes. The article will also focus on urban forms attributes and will provide a resilient assessment tool by using metric-based methods for different morphological scales. Generally, the framework highlights the contribution of this research to the study of resilient morphological components combining qualitative and quantitative approaches. Accordingly, the review materials were collected through different research databases, such as google scholar and Scopus. For measurable resilient characteristics of urban forms, the review considered the following set of physical factors:

1) geometry (layout, height, numbers),

2) pattern distribution (density, relationship),

3) typology (type of routes, spaces), and

4) functioning (land use, transit).

FIGURE 2

Figure 2. The conceptual framework.

The review expanded on the operational definitions of resilient characteristics and included measurements to quantify the resilient urban form of refugee neighborhoods. The measurements test the resilient urban form using numeric and visual representations of resilient characteristics through descriptive analysis. The measurements are metric-based assessment of resilience that indicate different urban form attributes within the spatial scales of neighborhoods (Sajjad et al., 2021). The spatial resilience supports community resilience in neighborhoods especially for the refugee population, therefore this enhances the overall urban resilience. However, this study focuses on the resilient urban form of refugee neighborhoods only recognizing that economic, social, and environmental indicators of urban resilience are also important in the refugee context.

Urban Resilience (or, Resilient Urban Form)

Nowadays, resilience is a promising concept in different areas of research including ecology, psychology, sociology, and urban design and planning. In terms of urban systems, resilience has been expanded from the details of our built environment to the major and comprehensive functions of urban systems. The concept started before the 19th century as a design principle in traditional construction to improve the resiliency of buildings (Hassler and Kohler, 2014). The timeline of resiliency research demonstrates a developmental pattern with different phases: generation, emergence, synthesis, and now operationalization (Beigi, 2015).

Urban resilience was introduced to integrate resilience with urban development (Chelleri, 2012; Yamagata and Maruyama, 2016). It refers to urban systems that maintain stability in multiple states. It also refers to adaptive concepts with many applications in cities (Hassler and Kohler, 2014; Beigi, 2015). Currently, urban systems in most cities are far from a state of equilibrium under a pressure from many factors and due to the complexity of their own processes (Batty, 2012). The geography of rapid population influx is one of the factors that can affect spatial structure, economy, livelihood, social pattern, and services in cities (Kirbyshire et al., 2017). Accordingly, there is a necessity to rethink these systems, so they are resilient and are capable to absorb, recover, adapt and transform in response to these changes. Urban resilience is a solution to prepare the urban system for any further disturbances as well as to respond to the ongoing shock of refugee waves and to adapt to any previous ones. In this regard, it is important to know the challenges faced by cities, more particularly spatial challenges, due to drastic demographic changes resulting from refugee influxes and to know how to structure an appropriate analysis to study these complex spatial challenges.

In general, urban resilience enhances the quality of life while focusing on the urban systems of a city (Ribeiro and Gonçalves, 2019). Yet, the conceptual frameworks of urban resilience differ by their considerations. Some of the existing frameworks consider all the city systems to be responsive to any stressor or shocks, such as the City Resilience Framework (Index, 2014). This framework is divided into every category of urban systems with different indeterminate qualities and goals. In contrast, the conceptual framework of Rockefeller Foundation has 4 different dimensions of the city-systems of urban resilience: leadership and strategy (knowledge); health and wellbeing (people); infrastructure and ecosystems (place); and economy & society (organization) (Reiner and McElvaney, 2017).

In term of resilience of refugee, there is some value in highlighting climate change in a resilience framework (Tyler and Moench, 2012). Therefore, some urban resilience frameworks use a multidisciplinary approach focusing on climate change adaptation (Kim and Lim, 2016). The resilience framework provided by Woolf et al. (2016) also considers informal settings with aspects of external resources, qualities, assets, and capacities (Woolf et al., 2016). Others adapted a city resilience framework focusing on issues related to rapid influxes such as shelter, health, services, economic development, employment, social and political inclusion, and cohesion (Kirbyshire et al., 2017). Recently, a framework was developed to include the mechanisms of urban systems by the types of disturbances (Ribeiro and Gonçalves, 2019). The model focuses on five dimensions: natural, economic, social, physical, and institutional, and integrates redundancy, robustness, connectivity, independence, efficiency, resources, diversity, adaptation, innovation, inclusion, and integration. These are some of the urban resilience characteristics discussed in this article. Nevertheless, a comprehensive conceptual framework of resilient urban form has remained elusive because of the complexity of urban systems and the existence of multiple processes and operations (Davidson, 2010).

Urban resilience tries to ensure equity of resources and services, recognizing the needs of different communities, besides equitable participation in policies and procedures (Meerow et al., 2019). Thus, it is quite common that the resiliency of refugees addresses shelter, healthcare, infrastructure, basic services, employment, economic development, political and social inclusion, and the risk of violence (Kirbyshire et al., 2017). Based on the different needs and complexities of refugee settings, the resilience maturity model (RMM) provides a tool to help multi-level of governance to build resilient city planning (Hernantes et al., 2019). RMM is developed by a collective of experts from different European countries with a sequence of five stages of start, moderate, advance, robust, and vertebrate for stakeholders (NGOs, internal government and refugee themselves), leadership and governance (international and national policies), infrastructure and resources, preparedness (officials and refugees), and cooperation (residents and refugees) (Resilience, 2020). Accordingly, RMM can be applied to obtain tangible resilience of refugee with developed strategies and community engagements.

Table 1 presents a list of the literature on different areas of urban resilience. Table 2 includes a summary of a few relevant publications in different fields. It includes the definitions of resilience, the resilient characteristics, the identification of a focus, and the types of resilient urban form considered in these studies. Table 3 lists various measurements for defining resilient urban form. Finally, Table 4 includes the link between various neighborhood attributes and resilient characteristics as discussed in the literature. Based on the findings presented in these tables, it may be suggested that the literature allows us to learn about urban resilience background and provides enough materials for a proper multi-scale conceptual framework for building resilience in specific spatial settings with abilities to respond to an ongoing shock or a disturbance.

TABLE 1

Table 1. A list of the literature on urban resilience classified by subject area.

TABLE 2

Table 2. A summary of the literature on urban resilience, identified based on relevance to this article.

TABLE 3

Table 3. Quantitative measurements of resilient characteristics.

TABLE 4

Table 4. A link between main urban-form attributes of a neighborhood and resilient characteristics at different hierarchal scales.

In 2016, urban resilience had as many as 25 definitions (Meerow et al., 2019). As noted above, Table 2 includes some of these definitions. In these definitions, a frequently cited function of urban resilience includes the capacity of urban systems to adapt to a shock or stressor (Adger et al., 2002; VLAD, 2020). The other functions of urban resilience have included absorption, recovery, and transformation of specific urban components and strategies in disturbed contexts (Hassler and Kohler, 2014). In general, resilient urban form starts with pre-disaster planning and preparation to decrease any specific decline of a system (Sustainable network) (Sharifi, 2019a), and to enhance the absorption (limit disturbance impacts), redundancy (alterations and reorganization), and flexibility (adjustable system) when disaster is accruing. In after-disaster stage, the characteristics of resilience are recovery, solving the problem (respondent), and adaptation (Sharifi, 2019a). The definitions also include identifications of whether resiliency is a quality, a process, or a result (Southwick et al., 2014).

However, the overall objective of urban resilience is to enhance quality of life (QOL) for all populations (Sharifi and Yamagata, 2018; Ribeiro and Gonçalves, 2019). Accordingly, the resilience of urban form is dependent on the specific needs and priorities of populations within specific geographical areas (Sharifi and Yamagata, 2018). All resilient urban form must seek answers to the following five questions (Meerow et al., 2016):

• Who? Who is included or excluded in urban system? This refers to the fact that different population groups have different concerns and priorities related to resilient urban forms (Sharifi and Yamagata, 2018).

• What? The prioritization in urban resilience considers contextual aspects while thinking of different population groups and their interactions (León and March, 2016; Sharifi, 2019a).

• When? The focus here is on timeline to obtain the goal of resiliency. The temporal scales are essential to study the resilience of urban form (Sharifi and Yamagata, 2018). Each resilient urban form of pre-disaster, during-disaster, and after-disaster phase has definite resilient characteristics.

• Where? This refers to the fact that the resilience of urban form can be expanded to various dimensions and directions in the complex urban systems and can enhance the urban resilience of cities (Kim and Lim, 2016).

• Why? The “why” question defines characteristics, resilience level of interventions, and the main purpose of this intervention (Sharifi and Yamagata, 2018).

While urban forms of cities are dynamic and complex with human and environment sub-systems, complex adaptive theory approaches the complexity of all urban systems besides interconnecting the theoretical basis of resilient characteristics (Dianat et al., 2022). The CAS theory emphasizes the interconnections of heterogeneous components (Carvalhaes et al., 2021). On the other hand, disaster resilience indices (DRI) are a less challenging approach to taking a temporal snapshot of vulnerability (Figure 3). DRI uses CAS as a theoretical background of resilience complexity and focuses on discussing specific dimension and identifying the dimension of resilience indicators (Carvalhaes et al., 2021). DRI first identifies resilient characteristics and resilient metrics; then provides the required improvements for implementable solutions (Carvalhaes et al., 2021). Also, DRI is essential to support the resilient quality of adaptation which is a process that enables the system to maintain its identity, to be able to cope with trends and shocks, and reduce vulnerability to disturbance. Moreover, this approach focuses on the component of spatial distribution of vulnerability in its conceptual framework for resilient city and resilient community (Jabareen, 2013). Therefore, resilient urban forms have spatial aspects of a multi-level hierarchical structure that is essential in the resilience of cities and that has the required characteristics of resilient urbanism (León and March, 2016; Sharifi, 2019b). In the built environment, time, actors, and scale are most important in resilient urban form (Hassler and Kohler, 2014); therefore, as a simple approach, the complexity of urban form is introduced in a hierarchical manner of scales (Sharifi, 2019b).

FIGURE 3

Figure 3. The assessment tool of resilient urban form of refugee neighborhoods.

Hierarchy is one simple way to approach the complex urban form. This approach includes macro, mesoscale, micro scales (Sharifi, 2019a). Macroscale clarifies the regional and metropolitan levels as well as the whole city level that has city's size, types of development, distribution patterns, and connectivity. Mesoscale includes elements of neighborhood scale and the community level. Finally, microscale of the building level has the structures and designs of buildings (Sharifi and Yamagata, 2018; Sharifi, 2019a). These three geographical scales help us understand spatial distributions and elements relations, thus defining the related characteristics of resilient urban form.

In this hierarchy, neighborhoods have the primary spaces of social production and perception (Wheeler, 2013). Neighborhoods consist of physical structures with spaces arranged to facilitate social interaction among residents (Brower, 2020). Their urban spaces have different morphological elements: plot, street edge, street, block, sanctuary space, and district (Feliciotti et al., 2016; Sharifi, 2019a). An approach to resiliency at the neighborhood scale must consider these elements focusing on the following resilient characteristics: diversity, connectivity, redundancy, modularity, and efficiency (Feliciotti et al., 2016). Ultimately, implementing resilience in neighborhood structure will help obtain interconnected resiliency in other urban systems to produce socio-economic and environmental benefits.

Next, the article will describe some of the resilience characteristics using quantitative measurements (Salat et al., 2010). It will focus on topology, programmatic satisfaction, and the quality of urban forms at the neighborhood scale (Table 3). It is hoped that the measurable parameters of resilient characteristics will allow a comparison of resiliency across different neighborhoods of different urban fabrics. The description will also include computation tools such as GIS, Space Syntax, and CityZoom to help quantify the resilient characteristics and to help develop a urban resilience knowledge system in refugee neighborhoods using various layers of information for better decision-making (Cariolet et al., 2019).

Connectivity

Connectivity is the ability to easily communicate within and across the systems (Feliciotti et al., 2016). Connectivity shows the interaction strength between urban elements (Salat et al., 2010; Boeing, 2018; Samuelsson et al., 2019). This characteristic helps urban form to facilitate reorganization (Nyström and Folke, 2001), besides improving communication, human travel patterns, and accessibility. The idea of connectivity as the strength of systems components has a complicated relationship with resiliency (Samuelsson et al., 2019). Connectivity at the urban scale includes street networks and their properties such as intersection types and density (Boeing, 2018). Connectivity in resilience has two sides: higher connectivity helps to absorb and recover, and lower connectivity reduces the diffusion of disturbance and preserve memory by limiting fragmentation (Marcus and Colding, 2014; Feliciotti et al., 2016).

Urban form literature has several methods to quantify connectivity for street networks and their properties. The method of a theoretical grid applies a series of intersected straight or curved lines that have ideal connections traced from the existing network. This method emphasizes the hierarchy of streets. In this regard, the connectivity of existing street networks decreases by with higher degree of deviation from the quality of gridedness (Boeing, 2021). The street segment changes have some removals (amalgamation phenomenon) that decrease the connectivity and other additives (fragmentation phenomenon) that enhance the connectivity (Vialard, 2012). Meanwhile, incisions are alterations of block boundaries that enhance connectivity. For example, Alice Vialard applied the theoretical grid and analyzed the street changes in her study of the two cities of Savannah and Atlanta. Atlanta has four additives of street segments, and 35% of the blocks have incisions. While Savannah has only two additives, and 42 removed streets, including 32% of blocks are affected by the amalgamation phenomenon. The percentages of street changes show Atlanta has better connectivity. Hence, connectivity measurement depends on the type and location of amalgamated or fragmented blocks besides any incisions. The method quantifies the properties of each area (the number and location of amalgamated or fragmented units) rather than the street network itself.

Metric reach measurement is a helpful tool to describe a connected street network. For instance, applying a metric reach ratio between implemented grid and the existing network the difference in connectivity can be calculated (Peponis et al., 2008). A ratio value close to 0.00 means more changes, in contrast, the a ratio value of 1.00 means the street segments are stable with better connectivity. The example of Savannah and Atlanta shows that the Savannah network decreased by the ratio of metric reach, and the Atlanta network increased specifically by the block's incisions (Vialard, 2012). Yet, the method uses more layers to measure connectivity to amenities and public transit. It indicates how the network follows a geometric order and expresses the degree of street homogeneity, hierarchy, centrality, orientation (Vialard, 2012). The main objective of this method is to determine the performance, accessibility, and functionality of the street network.

Integration also measures the connectivity by determining the accessibility of streets within a street network. The measurement identifies social interaction potential and human travel pattern which shows copresence of social capital within the any neighborhoods (Marcus and Legeby, 2012). Integration is good indicators to measure connectivity in the case of refugee communities, and can be used to characterize street network and pedestrian routes.

Other methods to measure connectivity are the number and types of street intersections. Table 3 includes the formulas of different methods. These formulas measure the intersection properties such as Intersections Density of the ratio between the number of network intersections and the square area (Equation 4) (Dill, 2004). The number of intersections indicates how the blocks are connected and how subtle and coarse the network is (Boeing, 2018). Another measurement is Connected Node Ratio (CNR). It is a ratio between the number of intersections and the number of both intersections and cul-de-sac (Equation 5) (Dill, 2004). CNR value toward 1.00 with fewer cul-de-sac has better connectivity. Moreover, the Link Node Ratio measures the number of links to the number of nodes (Equation 6) and a higher value means a more connected network. Nevertheless, intersection types have other spatial characteristics than connectivity. For instance, a four-way intersection is more connected but less safe while cul-de-sac is considered a friendly type. In a resilient urban, there is a need for balance between connectivity, safety, and friendly types (Samuelsson et al., 2019).

Lastly, pedestrian and cycling routes are important urban form attributes that enhance connectivity. They are essential for better neighborhoods with more social traveling patterns. Eventually, better connectivity of such traveling networks increases neighborhood resiliency. In this regard, there are two measurements to quantify the connectivity of pedestrian and cycling routes. Pedestrian Route Directness (PRD) is a ratio between existing route distance and straight-line distance (Equation 7) (Dill, 2004). This measurement has values of 0.00 to 1.00 while 1.00 has a more direct route and is better connected. On the other hand, Effective Walking Area (EWA) is a measurement that indicates the number of parcels within 0.40 km pedestrian shed (Equation 8) (Dill, 2004). EWA shows the accessible areas within 5 min walking distance.

Diversity

Diversity allows urban forms to have coping capacity and multiple stability in use and geometry (Feliciotti et al., 2016), and to support wellbeing and spatial justice among the neighborhood's residents (Samuelsson et al., 2019). Diversity also shapes travel behaviors in urban contexts (Cervero and Kockelman, 1997; Bordoloi et al., 2013). All urban forms need diversity (Salat et al., 2010), and there is a need to identify and evaluate the quality of urban form in terms of resilient diversity (Samuelsson et al., 2019) based on geometry, pattern distribution, and function (Feliciotti et al., 2016; Jacobs, 2016; Boeing, 2018). However, diversity of developments, density, and activities determine compactness of urban form (Jabareen, 2006). In refugee contexts, diversity will focus on the compactness theme to promote quality of life in spaces of social interaction and access to services and facilities (Jabareen, 2006).

Diversity in quantitative terms is the equity between different elements, meaning, functions, and distributions. Spatial diversity is concerned with the complexity of urban fabric which is a difficult parameter to define and measure. However, many theories provide a measurement of diversity among similar objects, different scales, or spatial distributions (Salat et al., 2010). The most popular is Shannon entropy (Equation 9) to measure land-use diversity. The entropy defines the complexity of the distribution of specific categories among others and ideally quantifies diversity in relation to even distribution. In addition, mixed land use provides better commute and human travel that affect the social and economic aspects (Torrens and Alberti, 2000; Van and Senior, 2000). It is essential for risk management, sustainable urban form, and future resilience.

There are several ways to define the diversity of networks, resources, and sizes, some of which are specified in Table 3. For instance, Simpson Diversity Index (Equation 10) indicates the richness of urban fabric (Salat et al., 2010). This index was developed to include different categories of urban forms. The measurement has a value between 0 and 1, where 1 has better diversity.

Salingaros's index (Equation 11) defines the diversity of distribution among different scales, such as the distribution of different scales of routes (Salat et al., 2010). Therefore, Salingaros's distribution works for the right proportion of objects of different sizes and scales.

The method of the theoretical grid also shows the changes of blocks diversity in shape and size. Therefore, more amalgamated or fragmented blocks indicate better diversity in the numbers and sizes of blocks. The method of theoretical grid measures both connectivity of street network by its closeness to gridedness, while changes of segments from theoretical grid give more diverse blocks in their sizes and shapes. Thus, there is a need to balance connectivity and diversity characteristics to meet the desirable resiliency.

A study of Stockholm city in Sweden investigates human experiences of connectivity and diversity for quantifying resilience (Samuelsson et al., 2019). This empirical investigation of Stockholm measured the spatial diversity by different indicators such as the proportion of working spaces, residential areas, roads, and natural elements. The study used public participatory GIS (PPGIS) to show spatial diversity of users' experiences. The results were compared with Pielou's diversity (evenness) (Equation 12) for the same indicators. The results showed that higher diversity occurs in intermediate connectivity based on the correlation between connectivity and diversity (Samuelsson et al., 2019).

Redundancy

The existence of spare capacity in urban form against threats is redundancy (Tyler and Moench, 2012; Anderies, 2014). Multiple components of same, similar, or backup functions often contribute to redundancy (Feliciotti et al., 2016). Put differently, redundant urban form contains alternative urban elements that reinforce each other so that urban form is able to reorganize or self-organize the space and people if and when needed (Feliciotti et al., 2016). In general, redundancy improves overall resilience. For example, a redundant network improves connectivity and accessibility (Sharifi, 2019a). A resilient urban form contains redundancy at all morphological scales (Vialard, 2012). A careful subdivision of urban blocks and districts with a degree of mixture in different ranges will lead to a more redundant urban form (Feliciotti et al., 2016).

A quantitative measurement of redundancy calculates the spatial distributions of spaces that allow an opportunity to reorganize, such as sanctuary spaces (Feliciotti et al., 2016). A spatialized version of Simpson's diversity index (Equation 13) is to know the distribution of these spaces at the district scale. A value close to 1.00 will have more equal spatial distribution of sanctuary spaces and will have an equal redundancy capacity in their specific areas. Open spaces or greenery spaces have many positive outcomes added to image of neighborhoods, quality of life of communities, sustainable lifestyle, and enhancements of the ecological life (Jabareen, 2006).

Balance index (Equation 14) is another equation that determines the balance between built area and unbuilt area (open spaces) to urban density (Villagra et al., 2014). In this regard, the resilient urban form will be enhanced in any neighborhood with equally distributed sanctuary spaces because of the improvement in both characteristics of diversity and redundancy. In urban block and plot scales, the redundant capacity is not limited to sanctuary spaces, it exists in street edges within urban block and plot scales. Street edges is redundant based on frontage spaces. Redundancy increases in fragmented and smaller size blocks (Vialard, 2012). This is measured by the frontage index for plot or block which is a ratio between frontage street length and plot or block perimeter length (Bobkova et al., 2021).

Modularity

The modules are self-standing systems or subsystems of a larger system. They consist of proper elements with independency in functionality and geometry (Feliciotti et al., 2016). Modules are not fixed urban patterns; instead, they are a homogeneous distribution of urban form that gives wholeness ensuring identity (Salingaros, 2000). They work like a nested structure within a hierarchical urban form. Modules in neighborhoods provide community capacity of absorption and recovery from disturbances (Allan et al., 2013). Modules can be emergent patterns of uses and peoples (Sharifi, 2019a). Therefore, the emergent neighborhood model has overlapped layers of varied spaces for better self-organization in any time of disturbances (Mehaffy et al., 2010; Sharifi, 2019a). The modules are important nodes with concentrated urban activity spaces with pedestrian shed of 400 meters and pedestrian flow of minimum 4 min walking (Mehaffy et al., 2010).

Modularity concerns the equal pattern distributions, such as having layers of an equal distribution of blocks in a district or plots in a block. Modularity characteristic has similar quantitative measurements of redundancy of spatial distribution. Therefore, modularity is measured by different layers in urban nuclei such as different dense activities, mixed-use corridors, green spaces, green corridors, and natural areas (Mehaffy et al., 2010). Urban nucleus places emphasis on hierarchy of community, movements, and natural elements. Moreover, the distribution of layers of activities determines the quality of sustainable transport including walking, cycling, and transportation through travel time (Jabareen, 2006).

In regard to street connectivity, the nucleus has different types:

• Centered nucleus is located at the center of neighborhood

• Edge nucleus is located at the edge of neighborhood

• Exposed nucleus is located along urban movement network

• Shielded nucleus has layers of complex uses that are shielded by main network.

However, the mixture of edge/shielded or centered/exposed nuclei represents an outcome of many layers that can support self-organization as well as self-standing subsystems that have independency in functionality and geometry (Mehaffy et al., 2010). The main objective of any study on modularity is to measure the mixture of these types to obtain emergent neighborhood model with dynamic complexity.

Efficiency

The general definition of efficiency is the ability of any system to avoid wasting resources and time while achieving the desired result. In urban form, it means maintaining the function of static urban form relative to dynamic processes (Godschalk, 2003; Kim and Lim, 2016). Nevertheless, efficiency in resilience is debatable, since it can be described as the expenses of other resilient characteristics of diversity, connectivity, redundancy, and modularity. Efficiency decreases urban resilience in simple urban forms (Feliciotti et al., 2016). However, more complex urban forms are more efficient structures with different elements at different scales (Feliciotti et al., 2016). Efficient urban forms often have a large number of small and flexible elements mixed with a few large ones that support each other (Wood and Dovey, 2015).

In this section, efficiency measurement focuses on block scale. Block scale works as an intermediate scale between streets and plots. The efficiency of the block has specifications of the size and shape of buildings or their circulation pattern (Siksna, 1997). This scale, therefore, has the space of urban community and identity at its edge (Vialard, 2012). Also, the performance of the social capital of any neighborhood occurs at this scale. Blocks in urban form determine the capacity of urban resilience and community resilience. The performance of urban blocks generally is related to their geometrical parameters and metric properties (Vialard, 2012).

Efficiency related to the resilience of a block depends on a balance between circulation patterns (fragmentation) and the footprints of buildings (amalgamation). The geometrical compatibility or incomparability of fragmentation and amalgamation depends on:

1) The size of footprint, which is related to the block threshold,

2) The shape of building/s, which defines the shape of a block,

3) The size of the building in relation to the size of block, and

4) The degree of building complexity related to block size.

Block threshold is an average distance between the perimeter to the centroid of a block. It is also called depth (Parent, 2009). The relationship between footprint and depth measures the block density. For an efficient block, the desirable depth to building footprint is 6–7 m (20′ −23′) for natural light, ventilation, and accessibility (Steadman et al., 2009).

Vacant spaces enhance block efficiency, and increase its redundancy capacity (Moudon, 1986). Thus, a correlation between building coverage (built area vs. block area) and building fragmentation (number of built-up units) identifies the most efficient block in an urban context (Vialard, 2012). For instance, this correlation will have blocks with three types of configurations (1) vacant of 0 built area and 0 fragmentation; (2) fully built with building coverage of 1; and (3) fragmented and variable coverage. In this regard, blocks with higher fragmentations and medium building coverage are more efficient (Vialard, 2012). The measure shows important relationship between block density and urban character of building fragmentations (Jabareen, 2006), and the quality of compactness (Jenks et al., 2000).

However, block configuration is not the only way to measure block efficiency. Determining compactness in urban blocks shows the degree of intensification that is the density of developments and activities (Jabareen, 2006). Compactness determines the shape of the footprint and its compatibility with the block shape. The calculation of square compactness (SqCpct) is the area to perimeter ratio (Equation 15). Further compatibility between SqCpct of block and SqCpct of footprint identifies the efficient block. In the same study of Savannah and Atlanta, the efficient block is the block of a large and complex footprint and higher SqCpct (Vialard, 2012). In general, amalgamated urban blocks can accommodate large and complex footprints. The efficient shape and size of blocks have the flexibility to accommodate different building types (Vialard, 2012).

Table 4 provides a summary of the literature describing various resilient characteristics or attributes of urban form. They are divided into the categories of geometry, pattern distribution, typology, and function. They are further divided into more measurable sub-attributes of a neighborhood's urban form. The main attributes and sub-attributes in Table 4 may have positive and negative values for the resilience of neighborhood when calculated using the following equations (Sajjad et al., 2021). However, all attributes summarized in the table have a positive value for spatial resilience:

$\begin{array}{ll}{Z}^{\prime }=\frac{x-x_{\min }}{x_{\max }-x_{\min }}\text{\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}positive\hspace{0.17em}contributed\hspace{0.17em}attribute}& (1)\end{array}$

$\begin{array}{ll}{Z}^{\prime }=\frac{x_{\max }-x}{x_{\max }-x_{\min }}\text{\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}negative\hspace{0.17em}contributed\hspace{0.17em}attribute}& (2)\end{array}$

x: is the value of specific attribute in the neighborhood

x max: is the maximum value

x min: is the minimum value

Where z' is a value standardized between 0 and 1, while 0 is less resilient and 1 is more resilient. In this regard, spatial resilience index is calculated by Cronbach's alpha as follows (Cronbach, 1951) in which an indicator is given combining all attributes of a neighborhood at a specific scale:

$\begin{array}{ll}\alpha =\frac{Nc}{v+(N-1)c}& (3)\end{array}$

N is the total number of attributes in specific scale

c is the average covariance between attributes-pairs in specific scale

v is the average variance of attributes in specific scale

Cronbach's alpha is applied to calculate the internal consistency of all attributes in all scales of the neighborhood. Table 4 has 25 attributes for the overall spatial resilience of the neighborhood. For example, street scale in a neighborhood has 6 attributes, therefore street resilience can have one overall value for all its attributes using Cronbach's alpha.

In conclusion, resilient characteristics work individually to assess the resiliency of urban forms in a neighborhood, while Cronbach's alpha value indicates the final resiliency value for urban forms at all scales. The same process can be used to operationalize the resilience sub-components of economic, social, and institutional factors of neighborhoods (Sajjad et al., 2021).

Discussion: Resilient Urban form Assessment in Refugee Neighborhoods

The five resilient characteristics of urban form resilience are connectivity, diversity, redundancy, modularity, and efficiency. In general, quantitative measurements can be used in any empirical study. They depend on the availability and accessibility of geometric and spatial data, straightforward application, the use of computation tools, and direct relationship to the specific resilient characteristics. The measurements also include the following elements of morphological scales and indicators of human behaviors and activities:

• Street layout and network elements, properties, and functions determine the connectivity of neighborhood

• District, block, and plot pattern distribution, typology, and functions determine the diversity of neighborhood

• Sanctuary spaces' distribution and typology determine the redundant capacity of neighborhood

• Block geometry and typology determining the efficiency of neighborhood

• Block–street functions, relationships, and geometry determine the modularity of neighborhood

Identifying resilient measurements is essential to contextualize the parameters for resilient urban forms of refugee neighborhoods. The parameters help define the stable physical structures that can fulfill the short and long-term needs of refugees. However, there is limited literature examining refugee contexts; few pieces of literature show their neighborhoods with complex spatial patterns of interactions, activities, and structures. The spatial structure of refugee neighborhoods varies depending on the formality and informality, demographic, and spatial experience. Concerning spatial challenges and vulnerability, urban pressures exist due to the demands and needs of sudden refugee influxes in urban services, housing, labor market, accessible transportation, sanitation, education, and health care. The disturbance of demographic changes affects residents and their quality of life (Ribeiro and Gonçalves, 2019).

Accordingly, Figure 3 and Table 5 summarize the measurements for resilient urban forms of refugee neighborhoods. The selected measurements are related to network accessibilities and mixed land uses. The set of parameters utilizes geospatial technologies of ArcGIS and space syntax to help reduce the communication gap in the interactive platform between decision-makers in refugee settings.

TABLE 5

Table 5. Contextualizing the measurements of resilient urban form in refugee neighborhoods.

Connectivity is the main factor in planning cities and their neighborhoods. There are two indicators for the connectivity of refugee settlements. The first one is personal connectivity of settlement's workers that can be measured through quantifying metric reach, and access to amenities and workplaces. On the other hand, physical and communities' infrastructure uses integration as an indicator of social capital, and effective walking area; intersection types as indicators of safety, friendly and connectivity neighborhood. Diversity has the quality of different refugee activities, choices, and uses blocks, housing, and land use. Efficiency defines the quality of urban fabric in blocks; and refugee walking experiences with their perception and image of neighborhoods; therefore, an urban block is a scale for efficiency characteristics as it focuses on neighborhood design. Redundancy helps maintain less mental distress and higher life satisfaction through recreational, open spaces, and green areas that enhances the quality of life for refugees. Moreover, the hierarchy of spaces (public, semi-public, semi-private, private) also plays a role in the redundant capacity of setbacks. Finally, modularity defines the overall quality of the spatial structure of different layers of streets, pedestrian routes, pedestrian shed, urban nucleus (centers).

The article does not have an illustrative example; therefore, it adapts the sustainability of urban forms matrix by Jabareen (2006) to conclude the assessment of resilient urban forms of different refugee neighborhoods as shown in the Table 6.

TABLE 6

Table 6. Adapted the matrix of the sustainability of urban forms by Jabareen (2006).

Conclusion

This study reviews urban resilience by focusing on assessing the resilient urban form of refugee neighborhoods. It integrates different conceptions of resilience and various knowledge domains. However, any urban resilience assessment framework must be contextual and must differ in terms of urban forms of refugees and their morphologies. Specifically, the study suggests an approach to proactively make resilient spatial structures that can adapt to and recover from the shock of displacement to ensure the security, stability, inclusion, functionality, and livability of refugee spaces.

The review summarizes important knowledge regarding resilient urban form. It gathers quantifying characteristics to enhance the resiliency concept. In addition, resilience assessment specifies different tools to utilize for improving practical resilience by official organizations working in refugee contexts.

However, the literature has been limited to measuring resiliency in cities of developed countries. Therefore, future research should consider measuring the resiliency of refugee contexts in developing countries to build theories based on the differences, changes, and transformations. Also, further studies need to examine refugee neighborhood conditions and gather refugee opinions on their urban forms. This will help to develop a model-based resilience assessment.

Author Contributions

Both authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We would like to acknowledge the Department of Architecture at the University of Kansas for the financial support and work as a platform to create this study. Additionally, acknowledging Yarmouk University is a sponsoring institution to work on the Research Topic.

References

Adger, W. N., Kelly, P. M., Winkels, A., Huy, L. Q., and Locke, C. (2002). Migration, remittances, livelihood trajectories, and social resilience. AMBIO J. Hum. Environ. 31, 358–366. doi: 10.1579/0044-7447-31.4.358

PubMed Abstract | CrossRef Full Text | Google Scholar

Alberti, M., Marzluff, J. M., Shulenberger, E., Bradley, G., Ryan, C., and Zumbrunnen, C. (2003). Integrating humans into ecology: opportunities and challenges for studying urban ecosystems. BioScience 53, 1169–1179. doi: 10.1641/0006-3568(2003)053[1169:IHIEOA]2.0.CO;2

CrossRef Full Text | Google Scholar

Alhusban, A. A., Alhusban, S. A., and Al-Betawi, Y. N. (2019). Assessing the impact of urban Syrian refugees on the urban fabric of Al Mafraq city architecturally and socially. Int. J. Disaster Resil. Built Environ. 10, 99–129. doi: 10.1108/IJDRBE-09-2018-0039

CrossRef Full Text | Google Scholar

Allan, P., Bryant, M., Wirsching, C., Garcia, D., and Teresa Rodriguez, M. (2013). The influence of urban morphology on the resilience of cities following an earthquake. J. Urban Design 18, 242–262. doi: 10.1080/13574809.2013.772881

CrossRef Full Text | Google Scholar

Anderies, J. M. (2014). Embedding built environments in social–ecological systems: resilience-based design principles. Build. Res. Inform. 42, 130–142. doi: 10.1080/09613218.2013.857455

CrossRef Full Text | Google Scholar

Apparicio, P., Landry, S., and Lewnard, J. (2017). Disentangling the effects of urban form and socio-demographic context on street tree cover: A multi-level analysis from Montréal. Landsc. Urban Plann. 157, 422–433. doi: 10.1016/j.landurbplan.2016.09.001

CrossRef Full Text | Google Scholar

Baravikova, A., and Chelleri, L. (2018). Urban Resilience Definitions and Principles: European Perspectives. Basel: Sciforum. doi: 10.3390/IFOU2018-06054

CrossRef Full Text | Google Scholar

Batty, M. (2012). Managing Complexity, Reworking Prediction. London: SAGE Publications. p. 607–608.

Google Scholar

Beigi, S. (2015). The timeline of resilience: a roadmap for cross operationalization of resilience. Ecol. Soc. 18, 5–20.

Google Scholar

Berghauser Pont, M., Stavroulaki, G., Bobkova, E., Gil, J., Marcus, L., Olsson, J., et al. (2019). The spatial distribution and frequency of street, plot and building types across five European cities. Environ. Plann. B Urban Analy. City Sci. 46, 1226–1242. doi: 10.1177/2399808319857450

CrossRef Full Text | Google Scholar

Berkes, F., and Ross, H. (2013). Community resilience: toward an integrated approach. Soc. Nat. Resour. 26, 5–20. doi: 10.1080/08941920.2012.736605

CrossRef Full Text | Google Scholar

Blank, M. (2019). “Wir Schaffen Das!”? spatial pitfalls of neighborhood-based refugee reception in germany—a case study of frankfurt-rödelheim. Soc. Sci. 8, 161.

Google Scholar

Blocher, J., and Gulati, M. (2016). Competing for refugees: a market-based solution to a humanitarian crisis. Colum. Hum. Rts. L. Rev., 48, 53. doi: 10.2139/ssrn.2674831

CrossRef Full Text | Google Scholar

Bobkova, E., Berghauser Pont, M., and Marcus, L. (2021). Towards analytical typologies of plot systems: quantitative profile of five European cities. Environ. Plann. B Urban Anal. City Sci. 48, 604–620. doi: 10.1177/2399808319880902

CrossRef Full Text | Google Scholar

Boeing, G. (2018). Measuring the complexity of urban form and design. Urban Design Int. 23, 281–292. doi: 10.1057/s41289-018-0072-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Boeing, G. (2021). Off the grid… and back again? The recent evolution of American street network planning and design. J. Am. Plann. Assoc. 87, 123–137. doi: 10.1080/01944363.2020.1819382

CrossRef Full Text | Google Scholar

Bordoloi, R., Mote, A., Sarkar, P. P., and Mallikarjuna, C. (2013). Quantification of land use diversity in the context of mixed land use. Proc. Soc. Behav. Sci. 104, 563–572. doi: 10.1016/j.sbspro.2013.11.150

CrossRef Full Text | Google Scholar

Borie, M., Pelling, M., Ziervogel, G., and Hyams, K. (2019). Mapping narratives of urban resilience in the global south. Glob. Environ. Change 54, 203–213. doi: 10.1016/j.gloenvcha.2019.01.001

CrossRef Full Text | Google Scholar

Brand, F. S., and Jax, K. (2007). Focusing the meaning (s) of resilience: resilience as a descriptive concept and a boundary object. Ecol. Soc. 12, 23. doi: 10.5751/ES-02029-120123

CrossRef Full Text | Google Scholar

Brower, S. (2020). Neighbors and Neighborhoods: Elements of Successful Community Design. Routledge.

Google Scholar

Cariolet, J.-M., Vuillet, M., and Diab, Y. (2019). Mapping urban resilience to disasters-A review. Sustain. Cities Soci. 51, 101746. doi: 10.1016/j.scs.2019.101746

CrossRef Full Text | Google Scholar

Carvalhaes, T. M., Chester, M. V., Reddy, A. T., and Allenby, B. R. (2021). An overview & synthesis of disaster resilience indices from a complexity perspective. Int. J. Disast. Risk Reduc. 57, 102165. doi: 10.1016/j.ijdrr.2021.102165

CrossRef Full Text | Google Scholar

Castles, S. (2003). Towards a sociology of forced migration and social transformation. Sociology 37, 13–34. doi: 10.1177/0038038503037001384

CrossRef Full Text | Google Scholar

Cervero, R., and Kockelman, K. (1997). Travel demand and the 3Ds: density, diversity, and design. Transp. Res. Part D Transport Environ. 2, 199–219. doi: 10.1016/S1361-9209(97)00009-6

CrossRef Full Text | Google Scholar

Chelleri, L. (2012). From the ≪Resilient City≫ to Urban Resilience. A review essay on understanding and integrating the resilience perspective for urban systems. Documents Anàlisi Geogràfica 58, 287–306. doi: 10.5565/rev/dag.175

CrossRef Full Text | Google Scholar

Coalition, H. (2013). What Is a Humanitarian Emergency? Avaialble online at: http://humanitariancoalition.ca/sites/default/files/factsheet/what_is_a_humanitarian_crisis_-_english.pdf (accessed June 13, 2014).

Google Scholar

Cote, M., and Nightingale, A. J. (2012). Resilience thinking meets social theory: situating social change in socio-ecological systems (SES) research. Progress Hum. Geogr. 36, 475–489. doi: 10.1177/0309132511425708

CrossRef Full Text | Google Scholar

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika 16, 297–334. doi: 10.1007/BF02310555

CrossRef Full Text | Google Scholar

Cumming, G. S. (2011). Spatial Resilience in Social-Ecological Systems. Springer Science & Business Media.

Google Scholar

DATA. (2019). Child Displacement. Avaialble online at: https://data.unicef.org/topic/child-migration-and-displacement/displacement/ (accessed September 2021).

Google Scholar

Davidson, D. J. (2010). The applicability of the concept of resilience to social systems: some sources of optimism and nagging doubts. Soc. Nat. Resour. 23, 1135–1149. doi: 10.1080/08941921003652940

CrossRef Full Text | Google Scholar

Davis, J., and Uffer, S. (2013). Evolving Cities: exploring the relations between urban form ‘resilience' and the governance of urban form. [Project Report]. London: London School of Economics. Available online at: https://www.lse.ac.uk/cities/publications/research-reports/Evolving-Cities

Google Scholar

Dianat, H., Wilkinson, S., Williams, P., and Khatibi, H. (2022). Choosing a holistic urban resilience assessment tool. Int. J. Disast. Risk Reduc. 71, 102789. doi: 10.1016/j.ijdrr.2022.102789

CrossRef Full Text | Google Scholar

Dill, J. (2004). “Measuring network connectivity for bicycling and walking,” in Paper Presented at the 83rd Annual Meeting of the Transportation Research Board (Washington, DC).

Google Scholar

Fazel, M., and Stein, A. (2003). Mental health of refugee children: comparative study. BMJ 327, 134. doi: 10.1136/bmj.327.7407.134

PubMed Abstract | CrossRef Full Text | Google Scholar

Feliciotti, A., Romice, O., and Porta, S. (2016). Design for change: five proxies for resilience in the urban form. Open House Int. 41, 23–30. doi: 10.1108/OHI-04-2016-B0004

CrossRef Full Text | Google Scholar

Fitzgibbons, J., and Mitchell, C. L. (2019). Just urban futures? Exploring equity in “100 Resilient Cities”. World Dev. 122, 648–659. doi: 10.1016/j.worlddev.2019.06.021

PubMed Abstract | CrossRef Full Text | Google Scholar

Godschalk, D. R. (2003). Urban hazard mitigation: creating resilient cities. Nat. Hazards Rev. 4, 136–143. doi: 10.1061/(ASCE)1527-6988(2003)4:3(136)

CrossRef Full Text | Google Scholar

Hassler, U., and Kohler, N. (2014). Resilience in the built environment. Build. Res. Inf. 42, 119–129. doi: 10.1080/09613218.2014.873593

CrossRef Full Text | Google Scholar

Hernantes, J., Maraña, P., Gimenez, R., Sarriegi, J. M., and Labaka, L. (2019). Towards resilient cities: A maturity model for operationalizing resilience. Cities. 84, 96–103. doi: 10.1016/j.cities.2018.07.010

CrossRef Full Text | Google Scholar

Index, C. R. (2014). City resilience framework. The Rockefeller Foundation and ARUP 928.

Google Scholar

Jabareen, Y. (2013). Planning the resilient city: concepts and strategies for coping with climate change and environmental risk. Cities 31, 220–229. doi: 10.1016/j.cities.2012.05.004

CrossRef Full Text | Google Scholar

Jabareen, Y. R. (2006). Sustainable urban forms: Their typologies, models, and concepts. J. Plann. Educ. Res. 26, 38–52. doi: 10.1177/0739456X05285119

CrossRef Full Text | Google Scholar

Jacobs, J. (2016). The Death and Life of Great American Cities. Vintage. doi: 10.1002/9781119084679.ch4

PubMed Abstract | CrossRef Full Text | Google Scholar

Jenks, M. J., Burgess, M. J. R., Acioly, C., Allen, A., Barter, P. A., and Brand, P. (2000). Compact Cities: Sustainable Urban forms for Developing Countries. London: Taylor and Francis.

Google Scholar

Kennedy, J. (2008). Structures for the displaced: Service and Identity in refugee Settlements. Delft: International Forum on Urbanism.

Google Scholar

Kim, D., and Lim, U. (2016). Urban resilience in climate change adaptation: a conceptual framework. Sustainability 8, 405. doi: 10.3390/su8040405

PubMed Abstract | CrossRef Full Text | Google Scholar

Kirbyshire, A., Wilkinson, E., Le Masson, V., and Batra, P. (2017). Mass Displacement and the Challenge for Urban resilience. London: Overseas Development Institute London.

Google Scholar

León, J., and March, A. (2016). An urban form response to disaster vulnerability: improving tsunami evacuation in Iquique, Chile. Environ. Plann. B Plann. Design 43, 826–847. doi: 10.1177/0265813515597229

CrossRef Full Text | Google Scholar

Lowry, J. H., and Lowry, M. B. (2014). Comparing spatial metrics that quantify urban form. Comput. Environ. Urban Syst. 44, 59–67. doi: 10.1016/j.compenvurbsys.2013.11.005

CrossRef Full Text | Google Scholar

Marcus, L., and Colding, J. (2011). “Towards a spatial morphology of urban social-ecological systems,” in Paper Presented at the 18th International Seminar on Urban Form.

Google Scholar

Marcus, L., and Colding, J. (2014). Toward an integrated theory of spatial morphology and resilient urban systems. Ecol. Soc. 19, 55. doi: 10.5751/ES-06939-190455

CrossRef Full Text | Google Scholar

Marcus, L., and Legeby, A. (2012). “The need for co-presence in urban complexity: Measuring social capital using space syntax,” in Paper Presented at the Eigth International Space Syntax Symposium.

Google Scholar

Mazumdar, S., Mazumdar, S., Docuyanan, F., and McLaughlin, C. M. (2000). Creating a sense of place: the Vietnamese-Americans and Little Saigon. J. Environ. Psychol. 20, 319–333. doi: 10.1006/jevp.2000.0170

CrossRef Full Text | Google Scholar

McAdam, J. (2018). The Global Compacts on Refugees and Migration: A New Era for International Protection? Oxford: Oxford University Press. doi: 10.1093/ijrl/eez004

CrossRef Full Text | Google Scholar

Meerow, S., Newell, J. P., and Stults, M. (2016). Defining urban resilience: a review. Landsc. Urban Plann. 147, 38–49. doi: 10.1016/j.landurbplan.2015.11.011

PubMed Abstract | CrossRef Full Text | Google Scholar

Meerow, S., Pajouhesh, P., and Miller, T. R. (2019). Social equity in urban resilience planning. Local Environ. 24, 793–808. doi: 10.1080/13549839.2019.1645103

CrossRef Full Text | Google Scholar

Mehaffy, M., Porta, S., Rofe, Y., and Salingaros, N. (2010). Urban nuclei and the geometry of streets: the ‘emergent neighborhoods' model. Urban Design Int. 15, 22–46. doi: 10.1057/udi.2009.26

CrossRef Full Text | Google Scholar

Mehaffy, M. W. (2015). Urban form and greenhouse gas emissions: Findings, strategies, and design decision support technologies. Available online at: https://repository.tudelft.nl/islandora/object/uuid%3A08008807-2699-411b-9e21-d5e733a68ba4

Google Scholar

Montgomery, J. (1998). Making a city: Urbanity, vitality and urban design. J. Urban Des. 3, 93–116.

Google Scholar

Moudon, A. V. (1986). Built for Change. Cambridge, MA: Massachusetts Institute of Technology.

Google Scholar

Netto, G., Baillie, L., Georgiou, T., Wan Teng, L., Endut, N., Strani, K., et al. (2021). Resilience, smartphone use and language among urban refugees in the Global south. J. Ethnic Migrat. Stud. 48, 542–559. doi: 10.1080/1369183X.2021.1941818

CrossRef Full Text | Google Scholar

Newman, E., and Van Selm, J. (2003). Refugees and Forced Displacement. Tokyo: International Security, Human Vulnerability, and the State, UNU Press.

Google Scholar

Nyström, M., and Folke, C. (2001). Spatial resilience of coral reefs. Ecosystems 4, 406–417. doi: 10.1007/s10021-001-0019-y

CrossRef Full Text | Google Scholar

Östh, J., Dolciotti, M., Reggiani, A., and Nijkamp, P. (2018). Social capital, resilience and accessibility in urban systems: a study on Sweden. Netw. Spatial Econ. 18, 313–336. doi: 10.1007/s11067-017-9375-9

CrossRef Full Text | Google Scholar

Parent, J. (2009). The Shape Metrics Tool. This tool was developed with the support of the Center for Land use Education and Research (CLEAR) and the University of Connecticut, Department of Natural Resources and the Environment.

Google Scholar

Park, H. (2016). The power of cities. Available online at: https://www.unhcr.org/innovation/the-power-of-cities/

Google Scholar

Peponis, J., Bafna, S., and Zhang, Z. (2008). The connectivity of streets: reach and directional distance. Enviro. Plann. B Plann. Design 35, 881–901. doi: 10.1068/b33088

CrossRef Full Text | Google Scholar

Pickett, S. T., Cadenasso, M. L., and Grove, J. M. (2004). Resilient cities: meaning, models, and metaphor for integrating the ecological, socio-economic, and planning realms. Landsc. Urban Plann. 69, 369–384. doi: 10.1016/j.landurbplan.2003.10.035

CrossRef Full Text | Google Scholar

Reiner, M., and McElvaney, L. (2017). Foundational infrastructure framework for city resilience. Sust. Resilient Infrastruct. 2, 1–7. doi: 10.1080/23789689.2017.1278994

CrossRef Full Text | Google Scholar

Resilience, S. M. (2020). Resilience maturity model.

Google Scholar

Ribeiro, P. J. G., and Gonçalves, L. A. P. J. (2019). Urban resilience: a conceptual framework. Sust. Cities Soc. 50, 101625. doi: 10.1016/j.scs.2019.101625

CrossRef Full Text | Google Scholar

Sajjad, M., and Chan, J. C. (2019). Risk assessment for the sustainability of coastal communities: A preliminary study. Sci. total Environ. 671, 339–350. doi: 10.1016/j.scitotenv.2019.03.326

PubMed Abstract | CrossRef Full Text | Google Scholar

Sajjad, M., Chan, J. C., and Chopra, S. S. (2021). Rethinking disaster resilience in high-density cities: Towards an urban resilience knowledge system. Sustain. Cities Soc. 69, 102850. doi: 10.1016/j.scs.2021.102850

CrossRef Full Text | Google Scholar

Sajjad, M., Chan, J. C., and Kanwal, S. (2020). Integrating spatial statistics tools for coastal risk management: A case-study of typhoon risk in mainland China. Ocean Coast. Manag. 184, 105018. doi: 10.1016/j.ocecoaman.2019.105018

CrossRef Full Text | Google Scholar

Salat, S., and Bourdic, L. (2014). “Spatial planning principles and assessment framework for climate adaptive & resilient cities in china,” in Paper Presented at the NDRC/MOHURD/aDb International Workshop on Urban Adaptation to Climate Change (Beijing).

Google Scholar

Salat, S., Bourdic, L., and Nowacki, C. (2010). Assessing urban complexity. Int. J. Sust. Build. Technol. Urban Dev. 1, 160–167. doi: 10.5390/SUSB.2010.1.2.160

CrossRef Full Text | Google Scholar

Salingaros, N. A. (2000). Complexity and urban coherence. J. Urban Design 5, 291–316. doi: 10.1080/713683969

CrossRef Full Text | Google Scholar

Samuelsson, K., Colding, J., and Barthel, S. (2019). Urban resilience at eye level: spatial analysis of empirically defined experiential landscapes. Landsc. Urban Plann. 187, 70–80. doi: 10.1016/j.landurbplan.2019.03.015

CrossRef Full Text | Google Scholar

Shaluf, I. M. (2007). Disaster types. Disaster Prev. Manag. Int. J. 16, 687–703. doi: 10.1108/09653560710837000

CrossRef Full Text | Google Scholar

Sharifi, A. (2016). A critical review of selected tools for assessing community resilience. Ecol. Indicat. 69, 629–647. doi: 10.1016/j.ecolind.2016.05.023

CrossRef Full Text | Google Scholar

Sharifi, A. (2019a). Urban form resilience: a meso-scale analysis. Cities 93, 238–252. doi: 10.1016/j.cities.2019.05.010

CrossRef Full Text | Google Scholar

Sharifi, A. (2019b). Resilient urban forms: A macro-scale analysis. Cities 85, 1–14. doi: 10.1016/j.cities.2018.11.023

CrossRef Full Text | Google Scholar

Sharifi, A. (2020). Urban resilience assessment: Mapping knowledge structure and trends. Sustainability 12, 5918. doi: 10.3390/su12155918

CrossRef Full Text | Google Scholar

Sharifi, A., and Yamagata, Y. (2018). “Resilient urban form: a conceptual framework,” in Resilience-Oriented Urban Planning (Cham: Springer), 167–179. doi: 10.1007/978-3-319-75798-8_9

PubMed Abstract | CrossRef Full Text | Google Scholar

Shi, Y., Zhai, G., Xu, L., Zhou, S., Lu, Y., Liu, H., and Huang, W. (2021). Assessment methods of urban system resilience: From the perspective of complex adaptive system theory. Cities 112, 103141. doi: 10.1016/j.cities.2021.103141

CrossRef Full Text | Google Scholar

Siksna, A. (1997). The effects of block size and form in North American and Australian city centres. Urban Morphol. 1, 19–33.

Google Scholar

Smith, L. R. (2013). Female refugee networks: rebuilding post-conflict identity. Int. J. Intercult. Relat. 37, 11–27. doi: 10.1016/j.ijintrel.2012.04.011

CrossRef Full Text | Google Scholar

Southwick, S. M., Bonanno, G. A., Masten, A. S., Panter-Brick, C., and Yehuda, R. (2014). Resilience definitions, theory, and challenges: interdisciplinary perspectives. Eur. J. Psychotraumatol. 5, 25338. doi: 10.3402/ejpt.v5.25338

PubMed Abstract | CrossRef Full Text | Google Scholar

Steadman, P., Evans, S., and Batty, M. (2009). Wall area, volume and plan depth in the building stock. Build. Res. Inform. 37, 455–467. doi: 10.1080/09613210903152531

CrossRef Full Text | Google Scholar

Sullivan, S., and Homewood, K. (2003). On Non-Equilibrium and Nomadism: Knowledge, Diversity and Global Modernity in Drylands (and Beyond…). Working Paper. Centre for the Study of Globalisation and Regionalisation, University of Warwick, Coventry, United Kingdom.

Google Scholar

Tippens, J. A. (2020). Urban Congolese refugees' social capital and community resilience during a period of political violence in Kenya: a qualitative study. J. Immigrant Refugee Stud. 18, 42–59. doi: 10.1080/15562948.2019.1569744

CrossRef Full Text | Google Scholar

Torrens, P. M., and Alberti, M. (2000). “Measuring Sprawl,” in Proceedings of the Association of Collegiate Schools of Planning Conference (Atlanta, GA). Available online at: https://discovery.ucl.ac.uk/id/eprint/1370/1/paper27.pdf

Google Scholar

Tsavdaroglou, C. (2020). The refugees' right to the center of the city and spatial justice: Gentrification vs commoning practices in Tarlaba-Istanbul. Urban Plann. 5, 230–240. doi: 10.17645/up.v5i3.3098

CrossRef Full Text | Google Scholar

Turkienicz, B., Gonçalves, B. B., and Grazziotin, P. (2008). CityZoom: a visualization tool for the assessment of planning regulations. Int. J. Architect. Comput. 6, 79–95. doi: 10.1260/147807708784640144

CrossRef Full Text | Google Scholar

Tyler, S., and Moench, M. (2012). A framework for urban climate resilience. Clim. Dev. 4, 311–326. doi: 10.1080/17565529.2012.745389

CrossRef Full Text | Google Scholar

Valtonen, K. (2004). From the margin to the mainstream: conceptualizing refugee settlement processes. J. Refugee Stud. 17, 70–96. doi: 10.1093/jrs/17.1.70

CrossRef Full Text | Google Scholar

Van, U.-P., and Senior, M. (2000). The contribution of mixed land uses to sustainable travel in cities. Achiev. Sust. Urban Form 139–148.

Google Scholar

Vialard, A. (2012). “Measures of the fit between street network, urban blocks and building footprints”, in Paper Presented at the Proceedings of Eighth International Space Syntax Symposium (Santiago).

Google Scholar

Villagra, P., Rojas, C., Ohno, R., Xue, M., and Gómez, K. (2014). A GIS-base exploration of the relationships between open space systems and urban form for the adaptive capacity of cities after an earthquake: the cases of two Chilean cities. Appl. Geogr. 48, 64–78. doi: 10.1016/j.apgeog.0.2014.01.010

CrossRef Full Text | Google Scholar

VLAD, L. B. (2020). Urban resilience definitions and limits of conceptual interpretation. Rev. Românǎ Geografie Politicǎ Year XXII 84–89. doi: 10.30892/rrgp.222104-337

CrossRef Full Text | Google Scholar

Wardekker, J. A., de Jong, A., Knoop, J. M., and van der Sluijs, J. P. (2010). Operationalising a resilience approach to adapting an urban delta to uncertain climate changes. Technol. Forecast. Soc. Chang. 77, 987–998.

Google Scholar

Wheeler, S. (2013). Planning for Sustainability: Creating Livable, Equitable and Ecological Communities. Routledge. doi: 10.4324/9780203134559

CrossRef Full Text | Google Scholar

Wood, S., and Dovey, K. (2015). Creative multiplicities: urban morphologies of creative clustering. J., Urban Design 20, 52–74. doi: 10.1080/13574809.2014.972346

CrossRef Full Text | Google Scholar

Woolf, S., Twigg, J., Parikh, P., Karaoglou, A., and Cheaib, T. (2016). Towards measurable resilience: a novel framework tool for the assessment of resilience levels in slums. Int. J. Disaster Risk Reduct. 19, 280–302. doi: 10.1016/j.ijdrr.2016.08.003

CrossRef Full Text | Google Scholar

Yamagata, Y., and Maruyama, H. (2016). Urban Resilience. Springer. doi: 10.1007/978-3-319-39812-9

CrossRef Full Text | Google Scholar

Yiwen, S., and Jiang, X. (2015). Understanding urban resilience: a conceptual analysis based on integrated international literature review. Urban Plann. Int. 30, 48–54. Available online at: http://en.cnki.com.cn/Article_en/CJFDTOTAL-GWCG201502009.htm

Google Scholar

Ziervogel, G., Pelling, M., Cartwright, A., Chu, E., Deshpande, T., Harris, L., et al. (2017). Inserting rights and justice into urban resilience: a focus on everyday risk. Environ. Urbaniz. 29, 123–138. doi: 10.1177/0956247816686905

CrossRef Full Text | Google Scholar