Criteria and Practices for Resilience at the Neighbourhood Level

ARCHITECTURAL SCIENCES AND SUSTAINABLE APPROACHES: URBAN RESILIENCE Editors Prof. Dr. Ömer ATABEYOĞLU Prof. Dr. Ertan DÜZGÜNEŞ October 15, 2025 Copyright © 2025 by İKSAD publishing house All rights reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means, including photocopying, recording or other electronic or mechanical methods, without the prior written permission of the publisher, except in the case of brief quotations embodied in critical reviews and certain other noncommercial uses permitted by copyright law. Institution of Economic Development and Social Researches (The Licence Number of Publicator: 2014/31220) TÜRKİYE TR: +90 342 606 06 75 USA: +1 631 685 0 853 E mail: [email protected] www.iksadyayinevi.com It is responsibility of the author to abide by the publishing ethics rules. Iksad Publications – 2025© Architectural Sciences and Sustainable Approaches: Urban Resilience ISBN: 978-625-378-337-2 Cover Design: Prof. Dr. Ertan DÜZGÜNEŞ October 15, 2025 Ankara / Türkiye Size = 16x24 cm PREFACE Dear Professors and Colleagues, We are pleased bring to life that Architectural Sciences and Sustainable Approaches: Urban Resilience, which was published as an e-book by IKSAD Publishing House with the editors Prof. Dr. Ömer ATABEYOĞLU and Prof. Dr. Ertan DÜZGÜNEŞ. This book project, entitled “Architectural Sciences and Sustainable Approaches: Urban Resilience,” aims to address sustainability-oriented approaches to urban resilience from theoretical, methodological, and practical perspectives. The volume seeks to establish a multi-layered platform of discussion, ranging from the scale of individual buildings to the entirety of the urban fabric. Within this framework, it welcomes contributions from scholars and researchers working in architecture, urban design, landscape architecture, urban and regional planning, environmental engineering, and related disciplines. With the valuable contributions of our chapter authors working in the professional disciplines of landscape architecture, architecture, city and regional planning, urban design and sustainability, we have completed Architectural Sciences and Sustainable Approaches: Urban Resilience book study has been completed with 24 book chapters. We would like to thank you, our esteemed authors, for their contributions to the preparation of the book. We would also like to thank the editorial board and IKSAD Publishing House. We wish to continue this process we have started in the coming years. In addition, we would like to express our sincere appreciation to Prof. Dr. Atila GÜL, the book coordinator of IKSAD Publishing House, for his guidance and support throughout the publication process. We hope that our book ‘Architectural Sciences and Sustainable Approaches: Urban Resilience’ will be helpful to the readers. Best regards. 15.10.2025 EDITORS Prof. Dr. Ömer ATABEYOĞLU Prof. Dr. Ertan DÜZGÜNEŞ EDITORS Prof. Dr. Ömer ATABEYOĞLU Prof. Dr. Ertan DÜZGÜNEŞ AUTHORS The authors were listed in alphabetical order Alper ÇABUK Ayça GÜLTEN Ayşe ÖZYETGİN ALTUN Ayşe Özge ŞİMŞEK SOYSAL Ayşegül TANRIVERDİ KAYA Demet EROL Deniz DEMİRARSLAN Ebru Vesile ÖCALIR Eda ŞENTÜRK Elif Kübra ÖZTÜRK Emine BAYDAN Esra KESKİN Feran AŞUR Feyza Sena ŞENOCAK Filiz KARAKUŞ Furkan AKDEMİR Gencay ÇUBUK Gülşah BİLGE ÖZTÜRK Halil DUYMUŞ Hamza ALTAŞ Hande AKARCA İnci OLGUN Kemal Mert ÇUBUKÇU Kumru ÇILGIN Mehmet Akif IRMAK Mehmet Emin DAŞ Mehtap ÖZENEN KAVLAK Merve ALICI AKA Mesut GÜZEL Muhammed Akif AÇIKGÖZ Muhammed Emir GÖRAL Murat YEŞİL Olcay Türkan YURDUGÜZEL Özge DÜZGÜN EREKİNCİ Pervin YEŞİL Rabia Nurefsan ACIKGOZ Sedef ŞENDOĞDU Seher Simay KUŞOĞLU Serim DİNÇ Sevilay YILDIZ Sinem SEYHAN Şevval ERGİNDOĞAN Şuheda ALTUNOK Temuçin Göktürk SEYHAN Tuba Nur OLĞUN Tuna BATUHAN Ufuk Teoman AKSOY Yusuf Eminoğlu REVIEWER LIST The authors were listed in alphabetical order Aslıhan TIRNAKÇI Nevşehir Hacı Bektaş Veli University Atila GÜL Süleyman Demirel University Ayşe Kalaycı ÖNAÇ İzmir Katip Çelebi University Bige ŞİMŞEK İLHAN İstanbul Medipol University Burcu YILMAZEL Eskişehir Technical University Eda KOÇAK Siirt University Ekrem BAHADIR Ankara Yıldırım Beyazıt University Elif KUTAY KARAÇOR İstanbul Technical University Hakan ARSLAN Ondokuz Mayıs University Hilal TURGUT Karadeniz Technical University Meliha AKLIBAŞINDA Nevşehir Hacı Bektaş Veli University Murat AKTEN Süleyman Demirel University Nihan Sümeyye GÜNDOĞDU Atlas University Okan Murat DEDE Amasya University Ömer Lütfü ÇORBACI Recep Tayyip Erdoğan University Selcen Nur Erikci Çelik Beykoz University Sibel AKTEN Isparta Unıversıty Of Applıed Scıences Sinem ÖZDEDE Pamukkale University Şeyma ŞENGÜR Ordu University Turgut KALAY Kütahya Dumlupınar University Tendü Hilal GÖKTUĞ Aydın Adnan Menderes University 492 1. Introduction In today’s context, where multidimensional urban risks such as climate change, disasters, and social inequalities are increasing, the idea of resilient cities is viewed as a complex system that includes not only physical infrastructure but also social, economic, and governance elements (Meerow, Newell & Stults, 2016; Sharifi, 2016). Resilience refers to a system's ability to withstand, adapt to, and recover from external shocks (Cutter, Ash & Emrich, 2014). In this setting, resilient cities are not just urban systems that “respond” to disasters and crises, but also those that can develop proactive, transformative, and inclusive solutions (Vale, 2014). The neighbourhood level is a vital scale in spatial planning for creating resilient cities. Neighbourhoods are units where local communities interact directly, where social capital is concentrated, and where daily practices are maintained. Physically, neighbourhoods include various spatial elements such as the road network layout, distribution of open and green spaces, building density, types of buildings, quality of public spaces, and infrastructure systems. Assessing these components collectively at the neighbourhood level is essential for the success of both pre-disaster risk reduction and post-disaster recovery. For example, the proportion of permeable surfaces plays a key role in managing rainwater and reducing the urban heat island effect, while green corridors and parks support ecological balance and foster social interaction (Mueller et al., 2023; Henning Larsen Architects, 2024). Moreover, morphological factors such as street widths, building heights, and development patterns should be evaluated in terms of emergency 493 response capacity, accessibility, and the availability of safe gathering areas. In this regard, neighbourhoods are multidimensional spaces that influence both physical and social resilience. Therefore, urban design practices implemented at the neighbourhood scale in resilience planning should be considered not only as technical solutions but also as spatial strategies integrated with communities (Sajjad et al., 2021; Bixler et al., 2022). However, the practical application of resilience strategies at the sociospatial level is most clearly tested in neighborhoods (Bixler et al., 2022; Sajjad et al., 2021). In urban design, neighborhoods especially offer strategic opportunities for open space systems, microclimate control, disaster shelter solutions, and community-driven planning practices (Henning Larsen Architects, 2024; Mueller et al., 2023). This study aims to compile the criteria identified in the literature for resilient neighborhood design. By analyzing disasters caused by climate change and natural hazards, the research demonstrates how theoretical debates are reflected in practical applications through a review of literature and real-world projects. 2. Material and Methods In academic research, a scoping review is a systematic yet flexible form of literature review conducted to broadly map the existing body of knowledge on a particular topic, identify key themes, conceptual frameworks, and knowledge gaps (Arksey & O’Malley, 2005; Munn et al., 2018). Compared to systematic reviews, scoping reviews offer a broader scope for exploration and conceptual categorisation (Peters et al., 2020). 494 In this study, the topic of resilient neighbourhood design is addressed from a multidisciplinary perspective. In particular, resilience practices and urban design approaches developed at the neighbourhood scale in the face of multidimensional urban risks, such as climate change and natural disasters have been examined in light of literature and best practice examples. This study aims to identify key principles, priority strategies, and implementation scales related to resilient neighborhood design by analyzing current case studies and academic debates. It clarifies the scope of the subject within its conceptual diversity and highlights the common features and different approaches of models developed in various regions. Using this scoping method, broad trends in the literature concerning both the theoretical framework and implementation strategies for resilient neighborhood design are uncovered. In this study, a comprehensive literature review was conducted to identify existing indicators for measuring and evaluating neighborhood-level resilience to disasters. A search using the keywords "resilience," "neighborhood," "disaster," and "indicators" in the Web of Science (WOS) and Scopus indexes yielded a total of 40 articles. Additionally, this research was conducted from 2020 to 2025. Similarly, to identify indicators for climate resilience at the neighborhood level, the keyword "climate" was searched together with "resilience," "neighborhood," and "indicators" in the Web of Science (WOS) and Scopus indexes. In total, 37 documents in Scopus and 53 in WOS were listed. These identified studies were examined, and publications that fell outside the scope of the research in terms of subject matter and scale or were duplicative were 495 eliminated. Publications found in both searches are only included in one research field; for example, publications about flooding are only included under the disaster topic. The keywords used in the searches and the number of publications selected from the indexes are shown in Table 1. Table 1. WoS and SCOPUS literature search results from 2020 to 2025 Article SCOPUS WoS Indicators for neighbourhood disaster resilience 10 6 Indicators for neighbourhood climate change 5 12 Disaster-resilient neighbourhood implementation 18 9 2.1. Data Extraction and Coding Process The following information was systematically extracted from the selected articles: • Year of study and geographical context • Resilience dimensions used (social, physical, economic, environmental, governance, technological) • Proposed or tested indicators • Analysis methods used (e.g., survey, statistical analysis, case study, modeling, etc.) These data were thematically coded, and common indicators were categorized in a table. The coding process was conducted independently by two researchers, and the results were compared to ensure consistency. 2.2. Analysis Method The study used a qualitative content analysis approach, not a quantitative meta-analysis. The findings were interpreted within a thematic framework, including the areas where indicators are concentrated, which indicators are prominent in specific regions, and where gaps exist. 496 3. Findings and Discussion This section initially presents a conceptual framework grounded in interdisciplinary studies of disaster risk reduction and climate resilience, forming a basis for resilient neighbourhood design. It also describes practical applications across urban and architectural fields, highlighting adaptive strategies, risk-informed planning, and design innovations aimed at improving neighbourhood-level resilience. 3.1. Indicators for Neighbourhood Disaster Resilience Disasters not only cause severe damage to physical infrastructure but also have complex and profound effects on social, economic, and administrative systems. In this context, the ability of communities to prepare for, mitigate, adapt to, and recover from disasters is called resilience (Meerow et al., 2016). Resilience provides a comprehensive approach to disaster risk management, covering not only physical recovery but also aspects like social capital, economic strength, institutional cooperation, and environmental sustainability (Cutter et al., 2014; Twigg, 2009). Recent research emphasises the importance of indicator-based approaches in assessing resilience. Indicator sets ensure that spatial planning and disaster risk reduction strategies are based on measurable and comparable data (Cutter et al., 2010; Joerin & Shaw, 2011). The neighbourhood scale is particularly significant because it is where local characteristics and community capacity can be observed in the most detailed way (Sharifi, 2016; Vale, 2014). This scale is vital for decision-making regarding predisaster preparedness as well as post-disaster response and recovery efforts. 497 In this study, a comprehensive literature review was conducted to identify existing indicators for measuring and evaluating neighbourhood-level resilience to disasters. The 16 articles were systematically analysed in terms of the dimensions and indicators used in measuring resilience to disasters at the neighbourhood level. The findings, which evaluate approaches from different disciplines within a holistic framework, are presented in Table 2. Table 2. Indicators for neighbourhood disaster resilience Article Dimension Identified Indicators Barroca et al., 2023 Social Social ties, level of participation Governance Local governance capacity, inter-institutional cooperation Physical Building density, infrastructure condition Economic Income level, economic resilience Bixler et al., 2021 Social Social networks, mutual trust, and information sharing Institutional Resource sharing, support mechanisms Buck et al., 2023 Social Micro-scale measures, level of organization Institutional Meso-scale neighborhood organizations, governance structures Physical Macro-scale infrastructure investments, physical planning Saijad et al., 2021 Information/ Data Real-time disaster data, historical records Institutional Governance structures, collaboration networks Process Learning and feedback loops, social learning Adrobo et al., 2023 Physical Building age, building type, and infrastructure condition Social Population density, dependent population, and education level Economic Income, ownership status, job security Meshkini et al.,2021 Physical Land-use diversity, green spaces, accessibility Social Social resilience, mixed-use advantages Pazhunan & Amirzade h (2023). Social Social ties, participation Economic Income level, livelihoods Physical Building condition, infrastructure Institutional Inter-institutional coordination, local governance Environmental Natural environmental conditions 498 Chakrabor ty et al., 2024 Social Elderly ratio, low income, single-parent households, ethnic minority ratio, and education level Physical Spatial overlap with seismic risk zones Li et al., 2021 Social Community organization, social indicators Economic Income sources, economic security Physical Infrastructure condition, building quality Environmental Green space, environmental quality Institutional Local government capacity, decision-making mechanisms Zebardas t, 2022 Social Capital Trust, participation, relationships Infrastructure Access and quality Economic Security Livelihoods, income stability Governance Participation in local decision-making Environmental Awareness Environmental sensitivity, sustainability behaviors Alam & Haque (2022). Physical Building density, building type, number of floors, building quality Social Population density, dependent population ratio, and education level Economic Income level, ownership status (tenant/homeowner) Environmental Soil type, green space ratio Bixler et al., 2022 Social/Process Trust among stakeholders, transparency of communication, sensitivity to local context, diversity of information, and continuous learning Institutional Institutional resilience and management of resource constraints Sogabe & Maki (2021). Social/ Demography Population change, age distribution, proportion of returning young population Economic Employment types, recovery of small businesses, and public investments Spatial Housing policies, socio-spatial segregation, and port functions Amirzad eh & Barakpo ur (2021). Institutional Multi-level governance, institutional capacity, and coordination Local Knowledge Local knowledge and learning systems, information sharing Community Participation of women/young/and elderly, social networks, organizations Nature-Based Water management, diversification of livelihoods Moradi et al., 2021 PhysicalEnvironmental Building age, building type, road width, plot layout, and infrastructure condition Socio-Cultural Public awareness, level of participation, and health infrastructure 499 Economic Income level, economic infrastructure Key Criteria Resistance, adaptation capacity, redundancy, recovery SinghPeterson et al., 2025 Social Social capital, local participation Economic Economic resources Infrastructure Infrastructure services General Spatial variability indicators, neighborhood-level analysis An examination of Table 2 reveals that the most prominent indicators are physical, social, economic, corporate-governance and scale-related indicators. Social, physical, economic, and institutional indicators are the primary ones. Environmental and governance factors are also significant but serve as supporting elements. Among physical indicators, Building density, infrastructure, land use diversity, and green spaces are the most emphasized factors for both earthquake and flood resilience. Social indicators, including social networks, community trust, participation, and social capital, are key elements that enhance resilience in nearly all studies. Economic indicators focus on livelihood diversity, income stability, and economic infrastructure, and are seen as directly linked to post-disaster recovery capacity. The importance of institutional and governance aspects, such as multi-level governance, information sharing, and local government capacity, is vital in addressing slow-moving hazards and complex urban systems. When analyzing the studies by scale, most are conducted directly at neighborhood or similar sub-local levels (e.g., Mymensingh, Lyon City, Shanghai, Shiraz). Character of Indicators: • Physical: Concrete spatial factors such as building density, building type, road width, and infrastructure are at the forefront. 500 • Social: Emphasises local participation, social networks, and community connections. • Economic: The variety of economic resources and ownership structures at the neighbourhood level is vital for post-disaster recovery. • Institutional/Governance: Local governance capacity and interinstitutional coordination are critical to neighbourhood-based planning. The benefits of neighbourhood-level studies are thought to be enhanced spatial awareness in disaster management, offering a solid foundation for prioritisation and targeted actions. The indicators summarized in Table 2 reveal common themes from various disciplines used to measure disaster resilience at the neighborhood level. However, simply listing these indicators is not enough; a critical and contextual evaluation is also essential. Studies conducted over the past five years have identified three distinct trends in disaster resilience indicators. Initially, physical infrastructure indicators remain dominant, but they are not sufficient alone. While indicators such as building density, road width, infrastructure quality, and green space availability are prominent because they can be measured quickly (Li et al., 2021; Alam & Haque, 2022), the literature warns about the risk of neglecting the social aspect. Then, social and governance indicators are gaining importance. Participation levels, social trust, the strength of social networks, and the representation of vulnerable groups (elderly, migrants, low-income communities) are seen as critical for sustainable resilience (Bixler et al., 2022; Chakraborty et al., 2024). In terms of governance, multi-level 501 coordination, transparent information sharing, and local government capacity have been prominent indicators, particularly in managing slowdeveloping risks (Amirzadeh & Barakpour, 2021). The third theme, technological and environmental indicators, adds a new dimension to the topic. Recent studies demonstrate that IoT-based early warning systems, big data analysis, and AI-supported decision-making mechanisms can be used at the neighborhood scale (Yang et al., 2025; OECD, 2025). Furthermore, nature-based solutions (permeable surfaces, ecosystem services, greenways) not only provide ecological benefits but also strengthen social interaction and support social capital (Mueller et al., 2023). Differences in geographical contexts also shape the choice of indicators. While Asian examples focus on engineering-based infrastructure solutions, European literature emphasizes nature-based approaches and participatory governance. In the US, technology integration and multiactor governance are combined (Boston Climate Ready, Barcelona Eixos Verds, China's Sponge City program). This shows that indicators must be adaptable to specific settings but also standardized to support international comparison (Sharifi, 2016; Wang & Liu, 2023). Consequently, indicators used to measure disaster resilience at the neighborhood level are not limited to physical parameters; they offer a multidimensional framework encompassing social justice, economic diversity, governance capacity, environmental sustainability, and technological innovation. This multidimensional approach necessitates the development of context-specific yet comparable hybrid indicator sets in the future. 508 patterns, which is analyzed within the disaster resilience framework adopted in this research. The primary concern in all of these research areas is collecting statistical data, since all aspects of climate issues are entirely site-specific and unique. Therefore, indicators also vary depending on geographical location, local population, urban density, industrial plants, agricultural activities, and other factors. This fact also highlights the advantages of neighbourhood-level studies. In this research area, although the main dimensions resemble those found in disaster resilience publications (Priya & Senthil, et al., 2025; Suárez, et al., 2024; Cole, et al., 2024), such as the Institutional Dimension of Climate Resilience and Indicators (Naji & Gwilliam, 2022), and the Vulnerability of urban areas to climate change (Cangüzel & Coşkun Hepcan, 2024), these studies have their own distinctive approaches toward indicators and resilience dimensions. One recent study highlights a specific concern, as it employs a framework to examine the phenomenon of "climate gentrification," which involves the demographic and socioeconomic upgrading of neighborhoods linked to SLR, potentially displacing lower socioeconomic groups by the higher classes (Wang & Liu, 2023). Nonetheless, the most common indicators mentioned in these studies include increasing green and blue surfaces, creating greener patches, and developing more permeable and less reflective surfaces. Additionally, the most frequently cited indicators encompass community participation, spatial awareness, and spatial justice within the social dimension. Indicators for measuring disaster and climate resilience at the neighborhood level are organized and analyzed within a thematic 509 framework. The findings show that resilience indicators mainly focus on social, physical, economic, governance, and environmental aspects. Additionally, technological and process-oriented dimensions have become increasingly important in recent years. Analyzed studies indicate that the most frequently used indicators for disaster resilience are building density, infrastructure quality, green space availability, social networks, social trust, income level, and governance capacity. These indicators play a critical role in both pre-disaster preparedness and post-disaster recovery processes. Social capital and local participation, in particular, stand out as determining factors, alongside physical infrastructure (Cutter et al., 2014; Bixler et al., 2022). Studies reveal that physical indicators are frequently preferred due to their measurability and direct applicability, while social and governance indicators are often considered secondary. This situation leads to a prioritization of “technically focused” solutions in practice, whereas community participation and local knowledge systems are indispensable for the sustainability of resilience. Climate change adaptation indicators are more diverse. Studies focus on physical-environmental measures such as reducing the heat island effect, increasing green and blue infrastructure, promoting permeable surfaces, and protecting ecosystem services. Furthermore, climate justice, protection of vulnerable groups, equity, and spatial justice have gained prominence as key social indicators in recent years (Suárez et al., 2024; OECD, 2025). While studies in Europe and North America highlight nature-based solutions and participatory governance models, examples in Asia (e.g., the 510 Sponge City program in China) emphasize infrastructure and water management solutions more. This difference shows that indicators are sensitive to context and that a single set of criteria will not be enough. Comparative analysis of studies reveals three key trends: 1. While physical indicators (building density, infrastructure status, green space ratio) still dominate, these indicators alone are not sufficient. 2. Social indicators (participation, social networks, trust) and governance indicators (multi-level governance, institutional capacity) are becoming increasingly important. 3. Technology integration (IoT-based early warning systems, realtime climate data monitoring, AI-supported decision-making mechanisms) adds a new dimension to resilience indicators. Existing literature shows that neighborhood-scale resilience studies mainly rely on conceptual frameworks but lack standardized measurement methods (Sharifi, 2016; Wang & Liu, 2023). This makes it difficult to compare data from different regions. Additionally, many studies only examine the effects of local context and social inequalities on indicators. Therefore, future research should develop context-sensitive yet comparable indicator sets, increase interdisciplinary collaborations, and test the applicability of indicators in the field. The findings reveal that neighborhood resilience involves more than just physical infrastructure; it is a complex concept that encompasses social capital, economic diversity, governance capability, and environmental solutions. The most common indicators identified in the research (such as social participation, building density, infrastructure quality, and green spaces) are also the easiest to incorporate into policy and planning. 511 Furthermore, the variety of models developed in different locations highlights the need for indicator sets that are both sensitive to context and adaptable. In this context, the findings align closely with the recommendations in the study's conclusion: standardizing indicators, ensuring transparency of data sources, conducting long-term monitoring studies, and fostering greater interdisciplinary collaboration. Additionally, approaches that leverage smart technologies and emphasize community participation seem to play a crucial role in strengthening neighborhood resilience in the future. 3.3. Examples of Resilient Neighbourhood Implementations In the review, which focused on “resilient neighbourhood practices and disasters” (including geological disasters and climate change), it was observed that projects developed within the context of climate change gained prominence. Regarding climate change, the spatial arrangements of cities have emphasised solutions centred on floodwater or rainwater management, energy management, disaster-related technologies, as well as smart urbanism and architectural practices. The practices are classified as those covering the entire city and architectural scale practices that provide detail at the trim neighbourhood group level. In this section, the practices examined are presented in two categories: urban-scale and architectural-scale topics. 3.3.1. Urban design scale The sponge city concept, which involves urban and regional-scale water management strategies to address climate change, is gaining prominence. Sponge City practices, a China-based initiative launched as a pilot programme in 2013 for floodwater management, represent a significant 512 topic in climate change governance. In response to China’s ongoing population growth and the rising risk of water inundation caused by global climate change, sponge city measures have been implemented at the neighbourhood level. In this context, two examples are provided from the Chinese cities of Xiamen and Wuhan. The project in Xiamen was actively implemented in 2014. The LID (LowImpact Development) projects, which began in Xiamen in 2014, were primarily completed between 2015 and 2017, featuring green roofs, rain gardens, water channels, and storage systems (Figure 1). In the 6.2-hectare pilot area, design solutions were developed, including 1,401 m² of green roofs, 5,325 m² of bioretention areas (rain gardens), 1,880 m² of vegetated swales, and a 15 m³ rainwater storage tank (Xiang et al., 2017). These solutions made significant contributions in reducing the impact of heavy rainfall, decreasing the volume of water discharged to the sewer system, and lowering carbon emissions. Its resistance to Typhoon Nepartak in 2016 has been a strong indicator of the system’s effective operation (New Security Beat, 2017). In the case of Wuhan, efforts under the sponge city strategy began in 2015, and a comprehensive system was implemented, consisting of two main demonstration areas and 288 sub-projects (GrowGreen, 2021). Similarly, in the Wuhan example, rain gardens, green roofs, permeable asphalt, onsite infiltration ditches, and water storage systems were utilized (Reason to be Cheerful, 2020). In this project, too, the development of resilience against climate change was demonstrated by the fact that despite a daily rainfall of 472 mm in 2020, the city did not experience significant inundation, and the number of 513 flood-prone locations decreased by more than 50% (GrowGreen, 2021; Reason to be Cheerful, 2020). Figure 1. A: Tianjin Wetland Park, B: Qnuli Rainwater Park, C: Haikou Meishe River before the project, D: Haikou Meishe River after the project (Edited with images from Arkitera, 2023). Increasing the amount of green space at the urban scale is one of the key practices in resilient neighbourhood design for temperature management. An important example in this regard is the Eixos Verds plan implemented in Barcelona. Eixos Verds refers to the network of green streets with high vegetation cover that connect neighbourhoods in the city of Barcelona (URBAG, 2023) (Figure 2). A total of over 750 km of potential green routes has been planned. Among the objectives of the practice, also referred to as a green corridor, are strengthening socio-ecological connectivity, supporting habitat, improving the microclimate, managing 514 rainwater, and increasing the amount of recreational space (URBAG, 2021). In the project, which was carried out through co-creation workshop processes, the top priorities include multifunctionality, reducing heat stress, and supporting biodiversity (URBAG, 2023). The planning process for Eixos Verds is based on the Superblock pilot studies conducted in Barcelona between 2013 and 2016. This design approach has been demonstrated to provide advantages in terms of climate management and accessibility (Anguelovski et al., 2023). These pilot applications demonstrated the effects of transformation on promoting equity (Anguelovski et al., 2023). In 2021, the Superblock pilot projects were expanded across the entire city and developed into Eixos Verds (URBAG, 2021; Anguelovski et al., 2023). In the Eixample district, one in every three streets has been designated as a green corridor (López-Bueno et al., 2023). Streets such as Consell de Cent, Carrer de Bolívia, and Carrer de Cristóbal de Moura have incorporated vegetation, water features, and social spaces. As of 2023, 2.8 km of the main corridor of the plan, which is still under implementation, has been completed, and expansion continues into surrounding neighbourhoods such as Sant Martí (Barcelona City Council, 2022). According to Mueller et al. (2023), the corridor can increase the green area ratio by 3.6% and reduce temperatures by 0.05–0.42 °C. The project, which increases access to green space for children and low-income groups, is estimated to have positive mental health effects for 31,353 people and a 13% reduction in medication use (Mueller et al., 2023; Opbroek, 2024). According to the analysis by the Barcelona Institute for Global Health 515 (ISGlobal) (2023), which evaluates the potential health impacts of the Eixos Verds plan, the green corridor intervention covering one out of every three streets may contribute to the reduction of preterm birth risks annually (ISGlobal, 2023; Mueller et al., 2023). Figure 2. A: Eixos Verds plan (taken from URBAG, 2021). B: Distribution of the green corridor at neighbourhood level in the Example case (edited with images from Anguelovski et al., 2023). Another key factor guiding citywide implementations is the use of technological solutions. Innovative urban solutions are employed across the city to address various types of disasters. While smart city technologies aim to improve urban efficiency through data-driven management and infrastructure solutions, resilient neighbourhood design emphasises physical, social, and infrastructural resilience to climate change and disaster risks. The city of Boston integrates these two approaches, setting an example with pioneering applications in both technological and ecological fields. Launched in 2016 by the Boston Planning and Development Agency, the Climate Ready Boston program is a comprehensive plan for climate adaptation throughout the entire city. It includes risk analyses for the 47mile-long coastline, adaptation strategies against heat stress, and flood 516 projections. Resilient infrastructure solutions have been developed particularly in coastal residential areas of neighbourhoods such as East Boston, Charlestown, South Boston, and Roxbury (City of Boston, 2023; Boston Planning & Development Agency, 2022). In the East Boston area, nature-based solutions such as elevated park areas, deployable floodwalls, and flood defence systems integrated with natural landscapes have been implemented. These solutions are supported by sensors and early warning systems, creating a 'smart + resilient' structure at the neighbourhood level. The projects were shaped through community participation, and pilot implementations began in 2021 (ASLA, 2022). The Waterfront Innovation District transformation project, launched in 2010, aims to convert the industrial waterfront area of South Boston into a centre for knowledge, clean technology, and innovation. The project features smart transportation systems, energy efficiency measures, IoTbased infrastructure solutions, and sustainable building standards. The area has been designed as a “living lab,” meaning a real-life testing ground for innovation (City of Boston, 2023; Boston Planning & Development Agency, 2022). Resilient solutions such as elevated building foundations, permeable surfaces, bioswales for stormwater management, and smart energy infrastructure enhance the area's resilience to climate change. Additionally, the Climate Resiliency Infrastructure Contribution model allows for financial contributions from the private sector to public infrastructure projects (Kim, 2024). The Boston cases demonstrate that strong integration between technology and resilience is possible. Both projects use early warning systems, data 517 analytics, nature-based design solutions, participatory planning approaches, and multi-stakeholder governance models. Thanks to this integration, both infrastructural resilience and social inclusion are prioritised (City of Boston, 2023; Boston Planning, 2023). By integrating smart city technologies with resilient neighbourhood design at both neighbourhood and district scales, Boston presents a model urban framework. This structure highlights the importance of a multidimensional approach to urban planning in the age of the climate crisis. 3.3.2. Architectural design scale The example of Moakley Park in Boston, Massachusetts, illustrates a significant approach to managing potential coastal flooding caused by sea level rise (Figure 3A). According to Whiteside (2022), Moakley Park, originally established in 1916 for multi-purpose recreational use, has been incorporated into various climate adaptation strategies since 2018. These measures, mainly aimed at preventing sea level rise along the coast and managing stormwater, are expected to provide notable benefits both in the short and long term. A boundary was outlined along the coastline to indicate the potential sea level rise, and landscape features such as barriers, vegetation, and similar elements were developed between this boundary and the waterfront to hold back water (Figure 3 B). The design of these interventions, created through community collaboration for disaster risk reduction, highlights Moakley Park’s role in strengthening community resilience (Boston Parks and Recreation Department, 2025). 524 Data-driven technological infrastructure and smart systems contribute significantly to early warning, crisis management, and resource efficiency. Diversity in spatial scale requires the integration of architectural details with urban strategies. In this context, resilient neighbourhood design necessitates a holistic approach that encompasses not only physical infrastructure but also social, economic, and governance dimensions. For future practices, it is crucial to promote interdisciplinary collaboration, data-informed decision-making, and community-centred models. 4. Conclusion and Suggestions This study provides a thorough interdisciplinary analysis of indicators used to evaluate disaster and climate change resilience at the neighborhood level. The findings reveal that resilience extends beyond physical infrastructure to include a multidimensional framework comprising social capital, economic diversity, governance capacity, environmental sustainability, and technological innovation (Cutter et al., 2014; Sharifi, 2016; Bixler et al., 2022). However, social capital, community involvement, building density, infrastructure quality, and governance capacity are key indicators; these elements are also essential for both pre-disaster preparedness and postdisaster recovery at the neighborhood level. Meanwhile, nature-based solutions, climate justice strategies, and emerging technological innovations have become prominent trends in recent years. Indicators are grouped as seen in Table 4. The first key observation is that social and physical indicators are the most reported (e.g., population density, social capital, building density, infrastructure status) and dominate 525 other indicators. In the context of disaster resilience, the most frequently cited indicators include building density, infrastructure quality, green space availability, social networks, community trust, income level, and governance capacity (Li et al., 2021; Alam & Haque, 2022; Zebardast, 2022). Table 4. Key common indicators Dimension Key Common Indicators Social - Social capital (trust, community ties, social networks) - Level of participation (involvement in decision-making and solidarity activities) - Population density, proportion of elderly/dependent population - Education level and awareness - Social equality, social justice, and inclusiveness Economic - Income level and income stability - Diversification of livelihoods and economic security - Types of employment, recovery of small businesses - Poverty rate, economic infrastructure, and resilience Physical / Infrastructure - Building density, building type, building quality - Infrastructure condition (roads, water, energy, etc.) - Land use diversity and spatial integration - Green spaces and accessibility - Urban morphology, open space ratio, and urban heat island effect Institutional / Governance - Local governance capacity and multi-level governance - Inter-institutional cooperation and coordination - Resource sharing and support mechanisms - Transparency, information sharing, learning and feedback loops Environmental / Ecological - Natural environmental conditions, ecosystem services - Green and blue infrastructure (parks, forests, wetlands, water management) - Biodiversity and ecological resilience - Reduction of heat island effect, microclimate regulation capacity Process / Technological - Long-term monitoring and use of longitudinal data - Use of real-time disaster and risk data - Learning and innovation capacity - Technological integration (IoT sensors, AI-supported decision support systems) 526 These indicators play a critical role in both pre-disaster preparedness and post-disaster recovery. However, due to their measurability, physical indicators tend to be prioritized, while social and governance indicators are often considered secondary (Buck et al., 2023; Chakraborty et al., 2024). This leads to a dominance of technically focused solutions, whereas community participation, local knowledge systems, and institutional collaboration are essential for sustainable resilience (Amirzadeh & Barakpour, 2021; Sogabe & Maki, 2021). Climate change resilience, on the other hand, is addressed through more diverse and context-specific indicators. Physical-environmental measures such as reducing the urban heat island effect, increasing green and blue infrastructure, promoting permeable surfaces, and protecting ecosystem services are emphasized (Priya & Senthil, 2025; Yang et al., 2025). Additionally, social indicators such as climate justice, protection of vulnerable groups, equity, and spatial justice have gained prominence in recent years (Suárez et al., 2024; OECD, 2025). For these reasons, the second key observation is the growing emphasis on institutional and governance indicators such as multi-level governance and coordination mechanisms as well as the promotion of sustainability-oriented behaviors. The third key observation emerging from this study is the critical importance of spatial scale, particularly the role of neighbourhoods as foundational units in resilience planning. Neighbourhoods are not only social constructs but also spatial entities composed of diverse physical, infrastructural, and environmental components. These include residential fabric, open and green spaces, transportation networks, public service infrastructure, and social amenities. Such multidimensional characteristics 527 directly influence a neighbourhood’s capacity to withstand and recover from disasters (Cutter et al., 2014; Sajjad et al., 2021; Sharifi, 2016). This perspective is reinforced by implementation examples such as the Sponge City projects in Xiamen and Wuhan, which demonstrate how neighbourhood-level interventions like rain gardens, green roofs, and permeable surfaces can effectively reduce flood risks and enhance climate resilience (Xiang et al., 2017; GrowGreen, 2021). Similarly, the Eixos Verds plan in Barcelona illustrates how spatial scale can be leveraged to integrate ecological, social, and health-related indicators. By transforming one in every three streets into green corridors, the city has not only improved microclimatic conditions but also enhanced access to green spaces for vulnerable populations, contributing to public health and social equity (Mueller et al., 2023; ISGlobal, 2023). From a design perspective, addressing the physical features of neighborhoods through integrated urban planning allows for the coordination of infrastructure systems, expansion of green spaces, creation of multifunctional areas, and development of flexible solutions to disaster risks. Projects such as Moakley Park in Boston and the Climate-Resilient Block in Copenhagen demonstrate how architectural-scale interventions can support stormwater management, energy efficiency, and biodiversity preservation while encouraging community engagement (Henning Larsen Architects, 2024; Boston Parks and Recreation Department, 2025). These examples affirm that the spatial scale of neighbourhoods is not merely a technical consideration but a strategic dimension in resilience planning. It allows for the contextualization of indicators, the mobilization of local knowledge, and the implementation of tailored solutions that 528 reflect the unique needs and capacities of communities. As emphasized in recent literature, neighbourhood-level approaches enhance spatial awareness, support participatory governance, and provide a robust foundation for prioritizing and targeting resilience actions (Sharifi, 2016; Wang & Liu, 2023; Amirzadeh & Barakpour, 2021). In this context, the third key observation of the study is the growing recognition that neighbourhoods, as spatially and socially integrated units, offer a unique opportunity to operationalize resilience strategies in a way that is both locally grounded and scalable. The fourth key observation of this study is the growing role of technological integration in enhancing neighbourhood resilience. Recent literature highlights that trend technologies based early warning systems, real-time climate data monitoring, and AI-supported decision-making mechanisms are increasingly being adopted as part of resilience indicator frameworks (Yang et al., 2025; Naji & Gwilliam, 2022). These tools not only improve the accuracy and responsiveness of disaster risk management but also enable predictive modelling and scenario planning at the neighbourhood scale. Technological indicators are no longer peripheral; they are becoming central to resilience strategies. For example, Yang et al. (2025) emphasize the use of multi-scale mechanisms—ranging from street-level sensors to urban-scale landscape connectivity—supported by cloud analytics and smart infrastructure. Similarly, OECD (2025) and Mueller et al. (2023) highlight the importance of digital tools in monitoring green-blue infrastructure and assessing the effectiveness of nature-based solutions. 529 This trend is clearly reflected in implementation examples such as Boston’s Climate Ready Boston and the Waterfront Innovation District. These projects integrate smart city technologies with neighbourhood-scale resilience strategies, combining sensor-based flood monitoring, IoTenabled infrastructure, and data-driven planning to address climate-related risks (City of Boston, 2023; ASLA, 2022). In East Boston, for instance, deployable floodwalls and elevated parks are supported by early warning systems, while the Innovation District functions as a “living lab” for testing smart energy and transportation solutions (Boston Planning & Development Agency, 2022; Kim, 2024). These examples demonstrate that technological integration is not limited to infrastructure efficiency but also enhances community engagement, governance transparency, and adaptive capacity. Projects are increasingly designed through participatory processes, where digital platforms facilitate stakeholder collaboration and feedback loops (Amirzadeh & Barakpour, 2021; Bixler et al., 2022). In this context, the fourth key observation is that technological indicators and applications are transforming how resilience is understood and put into action. They provide scalable, data-driven, and context-aware solutions that enhance physical, social, and institutional aspects of resilience. As cities confront increasingly complex and slow-onset hazards, integrating smart technologies into neighborhood planning becomes a crucial pathway for developing future-ready urban environments. The findings confirm that disaster resilience at the neighborhood level is fundamentally multidimensional. While physical indicators such as building density and infrastructure quality are well-known metrics, they 530 should be considered alongside social networks, participation levels, and economic resources (Cutter et al., 2014). Additionally, governance indicators like institutional capacity and coordination have become critical factors in the success of resilience strategies (Sharifi, 2016). The scoping review also highlights several gaps: Few studies provide detailed data or utilize standardized measurement frameworks. The variation of indicators across different contexts emphasizes the need for context-specific indicator sets that reflect local vulnerabilities and capacities. In conclusion, to effectively achieve the vision of a resilient city, decision-making must occur at the neighborhood level. The neighborhood scale serves not only as a foundation for physical design but also as a means to address social factors such as governance, inequality, accessibility, and social cohesion. Therefore, urban planning and design strategies should be reorganized with an emphasis on developing resilient neighborhoods. General Conclusions 1. While physical indicators are still dominant, they are not sufficient on their own; they need to be considered in conjunction with social and governance indicators. 2. Local participation and community networks are as critical to the sustainability of resilience as infrastructure investments. 3. Climate justice and spatial equity are increasingly important, particularly in climate change adaptation policies. 4. Resilience indicators should be context-sensitive yet comparable; this ensures that local needs are met and international comparisons remain possible. 531 Recommendations Develop standardized yet flexible indicator sets. These sets should adapt to various geographic and socio-economic contexts while maintaining comparability. Conduct historical process studies to track resilience over time. Methodological transparency should be improved. Future studies must clearly specify data sources, measurement scales, and validation methods. Long-term monitoring needs to be established. Indicators of neighborhood resilience should demonstrate changes over time, not just cross-sectional data. Interdisciplinary collaboration needs to be strengthened. Architecture, urban planning, sociology, economics, environmental sciences, and information technology should work together to develop more inclusive models. Policy and practice should be seamlessly integrated. The indicators highlighted in the study should be directly incorporated into municipalities' urban planning strategies and disaster management policies. Encourage community participation. Resilience efforts at the neighborhood level should include residents' knowledge and experience, supported by participatory governance models. Smart technologies and nature-based solutions should be used together. Resilience can be enhanced by integrating early warning systems, data analytics, and artificial intelligence with green infrastructure and water management solutions. 532 This study has limitations in that it only searched the WoS and Scopus databases, excluding local reports. Direct comparisons were challenging because of the diverse methods used in the analyzed studies. 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Sustainable Cities and Society, 86, Article 104127. https://doi.org/10.1016/j.scs.2022.104127. 543 Dr. Hande AKARCA E-mail: [email protected] Educational Status License: Architecture / Istanbul Technical University Degree: Built Resource Studies / Oxford Brookes University Doctorate: Architectural Design Problems / Mimar Sinan Fine Arts U. Professional experiences: Asst. Prof. / Duzce University, Participation & Sustainability in Architectural Design and Conservation Assoc. Prof. Dr. Ayşegül KAYA TANRIVERDİ E-mail:[email protected] Educational Status License:Architecture/Middle East Technical University Degree:Landscape Architecture/ Ataturk University Doctorate:Landscape Architecture/Duzce University Professional experiences: Assoc. Prof./ Duzce University, Urban Morphology Dr. Ayşe ÖZYETGİN ALTUN E-mail:[email protected] Educational Status License: Urban and Regional Planning / Mimar Sinan Fine Arts University Degree: Urban Design / Istanbul Technical University Doctorate: Urbanizm / Mimar Sinan Fine Arts University Professional experiences: Asst. Prof / Kırklareli University, Urban Resilience, Urban Conservation