Sustainable Cities and Society最新文献

{"title":"City size promotes to park cooling services and equity","authors":"Hao Chen ,&nbsp;Guofu Yang ,&nbsp;Zhenguo Wang ,&nbsp;Ronghua Xu ,&nbsp;Bin Xu ,&nbsp;Haiyan Dong","doi":"10.1016/j.scs.2025.106887","DOIUrl":"10.1016/j.scs.2025.106887","url":null,"abstract":"<div><div>The contribution of urban parks to enhancing thermal comfort and improving urban resilience is well-established. However, the mechanisms influencing their disproportionate cooling capacity across cities remain unclear. Therefore, understanding the factors that affect park cooling service (PCS) and its spatial equity is crucial for developing targeted urban climate risk mitigation strategies. This study evaluated the PCS and its spatial equity across 240 urban parks in 12 cities of the Yangtze River Delta, analyzing patterns along the urbanization gradient. The findings reveal that: (1) PCS is positively correlated with urbanization level, with the average park cooling service capacity (PCSC) in mega cities reaching 140 % of that in small cities (0.17 vs. 0.12). (2) spatial equity of PCSC also increases with urbanization, with mega cities exhibiting a 51 % improvement compared to small cities (0.47 vs. 0.95). (3) observed inequalities are mainly driven by industrial structure and urban–rural disparity, where relative temperature difference exerts the strongest positive effect on equity (0.23–18.00), while the share of the tertiary industry shows the strongest negative effect (−0.34 to −2.35). (4) smaller cities contain more parks with low cooling service levels (52 %) and have lower cooling area thresholds (0.56 km²), suggesting that PCS enhancement in smaller cities is more feasible. These findings provide valuable guidance for urban park planning and design to promote equity and livability across cities at different stages of urbanization.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106887"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contrasting frequency of global canopy and surface urban heat Island","authors":"Huyan Fu ,&nbsp;Jianghai Wen ,&nbsp;Zihan Liu ,&nbsp;Jiufeng Li ,&nbsp;Jiaxi Li ,&nbsp;Zhiru Chen","doi":"10.1016/j.scs.2025.106857","DOIUrl":"10.1016/j.scs.2025.106857","url":null,"abstract":"<div><div>The frequency of urban heat island (UHI) is a critical metric for assessing the temporal dynamics of urban heat islands and holds significant value for mitigation strategies. The investigation of the frequency of canopy UHI and surface UHI (CUHIF and SUHIF) is of great importance, as it represents different aspects of urban thermal environments. However, studies examining global CUHIF and SUHIF variations remain limited, and the mechanisms and relative contributions of various driving factors to these two types of heat island frequencies are poorly understood. This study calculated CUHIF and SUHIF for 1162 cities worldwide using global near-surface air temperature (<span><math><msub><mi>T</mi><mi>a</mi></msub></math></span>) and seamless land surface temperature (LST) datasets. The UHI frequency calculation thresholds were defined using global mean UHI intensity, specifically 0.5 K for canopy UHI and 1.0 K for surface UHI. The contributions of background climate (BGC), surface properties (SUP), and overall urban metric (OUM) were evaluated using the LightGBM model and SHAP algorithm. Results show that global daytime CUHIF and SUHIF are 72 and 217 days, respectively, whereas the nighttime values are 92 and 161 days. The tropical regions exhibit the highest daytime CUHIF and SUHIF (91 and 298 days), while arid regions have the highest nighttime values (135 and 200 days). The background climate exerts a dominant influence on daytime CUHIF and SUHIF (38% and 45%, respectively), while nighttime UHI frequencies are influenced by a combination of background climate and surface properties (52% and 36%, respectively). Meanwhile, CUHIF and SUHIF reach their annual maximums in summer and minima in winter. These findings enhance understanding of UHI frequency patterns and drivers, providing scientific evidence for mitigation strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106857"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal dynamics of land surface temperature and its drivers within the local climate zone framework","authors":"Weiting Xiong ,&nbsp;Qianlei Wu ,&nbsp;Junheng Qi ,&nbsp;Jingbo Li ,&nbsp;Sijie Zhu ,&nbsp;Bing Qiu","doi":"10.1016/j.scs.2025.106859","DOIUrl":"10.1016/j.scs.2025.106859","url":null,"abstract":"<div><div>The relationship between land surface temperature (LST) and urban morphology, particularly through the lens of Local Climate Zones (LCZs), has attracted increasing scholarly interest. However, the spatiotemporal dynamics of LST and its underlying drivers, both within and across LCZ types, remain insufficiently explored. This study integrates remote sensing and geospatial big data to investigate the differentiated mechanisms shaping LST dynamics within the LCZ framework. Taking Nanjing as a case study, we first used the World Urban Database and Access Portal Tools to classify LCZs for the years 2012 and 2022, and derived corresponding LST datasets from Landsat imagery. We then employed a Geographically Weighted Random Forest (GWRF) model to systematically examine the spatial and temporal dynamics of LST and its key drivers. Results show that mean LST increased from 39.22 °C in 2012 to 40.61 °C in 2022, with built-up LCZs consistently 5–7 °C hotter than vegetated or water-dominated zones. Vegetation demonstrated the strongest cooling capacity (NDVI reduced LST by up to 15 °C), whereas population density contributed to warming (up to +6 °C). Importantly, the magnitude and direction of driver effects varied significantly across both time and LCZ types, with landscape pattern metrics (e.g., CONTIG, FRAC) gaining influence over the decade. These findings highlight the importance of the LCZ framework for capturing heterogeneous spatiotemporal patterns of urban thermal environments and provide context-sensitive guidance for mitigating urban heat in rapidly urbanizing regions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106859"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstructing place attachment through social media: A systematic review for sustainable urban governance","authors":"Huihui Shi,&nbsp;Jinshi Zhang,&nbsp;Pengfei Huang,&nbsp;Shuchang Li","doi":"10.1016/j.scs.2025.106849","DOIUrl":"10.1016/j.scs.2025.106849","url":null,"abstract":"<div><div>Social media platforms have become pivotal actors in the realm of digital urban governance, actively reshaping how individuals cognitively, affectively, and behaviorally engage with urban environments. Following the PRISMA protocol, this review synthesizes 99 Chinese and English-language articles to examine how platforms reshape place attachment through algorithmic recommendation, emotional mobilization, and spatial re-presentation, addressing critical theoretical and policy gaps in platform governance and spatial cognition. Building on the classic Person–Process–Place model, the Platform-Embedded Place Attachment Framework is proposed, revealing place attachment as a governance variable co-constructed by platform logic, user behaviors, and urban feedback loops. The analysis identifies three interactive dimensions: (1) User Dimension—residents, tourists, and content creators co-construct emotionally charged urban spatial expressions; (2) Place Dimension—platform algorithms mediate the transformation of physical sites into affectively resonant digital places, sustaining offline–online–offline experiential loops; (3) Process Dimension—platforms modulate cognitive-affective-behavioral cycles by integrating user feedback into algorithmic systems and governance responses. Findings demonstrate that under platform modulation, place attachment evolves into a critical factor influencing spatial cognition, platform operations, and urban governance strategies. Finally, this review offers actionable governance insights by proposing three practical pathways—developing urban sensing systems based on user emotional data, establishing integrated platform-government-community management frameworks, and optimizing culturally inclusive recommendation algorithms—to directly support the construction of inclusive, resilient, and sustainable cities aligned with Sustainable Development Goal 11.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106849"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative AI of things for sustainable smart cities: Synergizing cognitive augmentation, resource efficiency, network traffic, cybersecurity, and anomaly detection for environmental performance","authors":"Simon Elias Bibri,&nbsp;Jeffrey Huang","doi":"10.1016/j.scs.2025.106826","DOIUrl":"10.1016/j.scs.2025.106826","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Artificial Intelligence of Things (AIoT) has emerged as a transformative technology driving environmental sustainability in smart city development. However, the integration of Generative Artificial Intelligence (GenAI) within AIoT ecosystems remains largely unexplored. Current research predominantly addresses conventional AIoT frameworks, overlooking the innovative potential of generative models, such as Generative Adversarial Networks, Variational Autoencoders, Diffusion Models, Transformers, and hybrid architectures, to significantly enhance situational awareness, system optimization, operational robustness, real-time responsiveness, and adaptive decision-making in complex urban environments. AIoT systems continue to face persistent challenges, including data scarcity, poor data quality, limited adaptability, imbalanced datasets, and inadequate context-awareness. This study addresses these gaps by systematically exploring how GenAI can enhance AIoT functionalities across key domains—namely cognitive augmentation, resource efficiency, network traffic, cybersecurity, and anomaly detection—while examining their synergistic potential to improve system-level environmental performance across two interconnected layers in sustainable smart cities. At the operational layer, key findings reveal that integrating GenAI with AIoT systems enhances urban efficiency, adaptability, autonomy, robustness, and resilience by conserving resources, optimizing network traffic flows, securing infrastructures, and detecting anomalies before they escalate. Specifically, the fusion of generative intelligence with federated learning promotes sustainable, energy-efficient AIoT deployments by reducing data transmission, thereby lowering communication overhead and safeguarding user privacy. In networked environments, generative models improve synthetic traffic realism and communication efficiency. They also strengthen cybersecurity through enhanced intrusion prevention and threat detection. Additionally, they enable early identification and mitigation of anomalies, boosting operational efficiency and system robustness. These improvements stabilize sustainable smart city system functioning and prevent disruptive failures. At the environmental layer, as key findings indicate, these operational gains cascade into indirect but tangible ecological benefits, while generative models advance the core pillars of AIoT by enabling proactive, autonomous, context-aware, and self-adaptive systems that further enhance the environmental performance of sustainable smart cities. Thus, while the five domains primarily underpin the operational backbone of urban systems, their cascading effects extend to ecological outcomes. The proposed conceptual framework, distilled from key findings, integrates GenAI and AIoT and highlights both domain-specific advancements and their synergistic interactions. This framework holds significant potential to drive sustainable smart city development by f","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106826"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying daily mismatch in urban cooling supply and demand at daytime and nighttime","authors":"Xuanya Huang ,&nbsp;Catharina J.E. Schulp ,&nbsp;Diep Anh Tuan Dinh ,&nbsp;Jasper van Vliet","doi":"10.1016/j.scs.2025.106851","DOIUrl":"10.1016/j.scs.2025.106851","url":null,"abstract":"<div><div>Urban green-blue infrastructure (UGBI) has been identified as a sustainable strategy for urban heat mitigation. However, most studies assessing mismatches between cooling supply and demand use coarse temporal scales, thus overlooking temporal dynamics. Specifically, they ignore variability in weather conditions, land cover, and population distribution, as well as the different cooling mechanisms at daytime and nighttime. Here, we quantify daily supply and demand for urban cooling at daytime and nighttime, for the city of Can Tho, Vietnam. We used a biophysical model to derive city-wide daytime and nighttime temperatures as cooling supply, applied heat stress thresholds to assess daytime and nighttime cooling demand, and then calculated mismatches between supply and demand to generate potential heat stress maps. These maps were overlaid with daytime and nighttime population to evaluate heat stress exposure across the study area. Results show that in 2023, more than 90% of the population experienced daytime heat stress on 293 days, compared to only 100 days at night, primarily in April and May. Temporally, nighttime exposure is less constant, particularly in low-density built-up areas. These results demonstrate how integrating daily resolution and explicit day-night dynamics provides more detailed insights into urban cooling mismatches. Consistently, our findings highlight the need for spatially and temporally explicit UGBI planning strategies to strengthen urban resilience against heat stress.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106851"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An LCZ-based machine learning framework for revealing spatial heterogeneity of thermal comfort in high-density areas: Enhancing explainability and fine-grid scale resolution","authors":"Shiqi Zhou ,&nbsp;Xiwen Geng ,&nbsp;Jingkai Zhao ,&nbsp;Jinghao Hei ,&nbsp;Tao Wu ,&nbsp;Zeyin Chen ,&nbsp;Zhiqiang Wu","doi":"10.1016/j.scs.2025.106873","DOIUrl":"10.1016/j.scs.2025.106873","url":null,"abstract":"<div><div>Rapid urbanization has intensified urban heat island, yet most universal thermal climate index (UTCI) studies remain at coarse scales and lack quantitative analysis of the mechanism. To fill these gaps, this study applied local climate zone (LCZ) framework to link morphology and thermal stress in fine-grid scale. Within the LCZ framework, a LightGBM SHAP‐based approach combining multi‐source 2D and 3D indicators was used to decouple the spatial heterogeneity and multidimensional drivers of thermal comfort in high‐density urban environments. The Bayesian-optimized LightGBM outperformed other algorithms with R² = 0.926 and RMSE = 0.153. The results demonstrated that: (1) LCZ2, 4, 6, and 8 play a dominant role in shaping the urban thermal environment and exhibit strong spatial autocorrelation based on urban spatial structure; (2) ME value exceeding approximately 10 m were associated with a pronounced mitigation in UTCI; (3) In LCZA with low UTCI, FRAC has a slight mitigating effect on UTCI when the value exceeds the threshold of 0.5; (4) Socioeconomic factors (GDP and population) together account for more than a quarter of the explanatory power of the model, and GDP can increase UTCI by up to 4 °C; (5) In the main LCZs, economic concentration promotes heat stress in compact mid-rise building areas. Building volume and mass have a significant impact on the thermal environment in open high-rise building areas, while in low-rise building areas, the impact of road density is significantly greater than in other LCZs. The study’s LCZ-integrated, explainable machine learning approach quantified universal and LCZ-specific heat drivers, revealed key mitigation thresholds, and delivered morphology-tailored planning insights.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106873"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing flood hazards threaten metro system resilience under climate and demographic changes","authors":"Chen Liang,&nbsp;Mingfu Guan","doi":"10.1016/j.scs.2025.106890","DOIUrl":"10.1016/j.scs.2025.106890","url":null,"abstract":"<div><div>Intensification of short-duration rainfall poses an increasing threat to urban metro systems, necessitating a thorough understanding of existing infrastructure's resistance in a warmer climate. This study systematically examines how future rainfall extremes and societal changes jointly affect metro system performance, using Hong Kong as a case study. We simulated city-scale flood inundation under the current climate baseline and three future representative emission scenarios using a grid-based flood hydrodynamic model. The study quantifies and characterizes flood hazard and risk, as well as metro performance curves at both station and line scales through integrating the simulated flood dynamics with demographic projections and infrastructure characteristics. Results show a substantial increase in flood hazard in low-lying coastal urban areas from the near to the far future under the highest emission scenario, while risk profiles remain comparatively stable. Short-duration rainfall intensity dominates the deterioration rates of metro functionality, while residual functionality and recovery capacity are primarily influenced by long-duration cumulative volume. Among performance-based resilience metrics, robustness emerges as the decisive factor influencing other components. High emissions in the far future present the most challenging scenario for metro system resilience, while other emission scenarios show more manageable impacts. Compared to demographic changes, climate-induced rainfall intensification exerts more significant influence on metro system resilience, particularly through cumulative rainfall volume. This research contributes a transferable framework for assessing infrastructure resilience under combined climate and societal stressors. By comparing their impacts, the study yields generalizable insights to guide adaptation of critical urban infrastructure, supporting robust planning for a complex future.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106890"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the average cooling effects of tree, artificial, and hybrid shade using city-wide IoT sensor measurements: A case study of Seoul","authors":"Seon Hyuk Kim ,&nbsp;Bona Ku ,&nbsp;Chae Yeon Park ,&nbsp;Ayano Aida ,&nbsp;Haojie Cheng ,&nbsp;Suryeon Kim ,&nbsp;Chan Park","doi":"10.1016/j.scs.2025.106855","DOIUrl":"10.1016/j.scs.2025.106855","url":null,"abstract":"<div><div>As urban heat stress continues to rise, strategies to mitigate heat for pedestrians through the provision of shade have become essential. While many studies have quantified the cooling benefits of shade and highlighted its importance for urban planning, the specific effectiveness of different shade types across various conditions remains unclear. Most previous studies have either modeled shade effects or relied on limited field measurements, leaving a research gap in evaluating the average cooling effect of shade across an entire city using real-world data.</div><div>To address this gap, this study used city-scale sensor data to analyze the cooling effects of tree, artificial, and hybrid shades during heatwaves. The results indicated that all types of shade effectively reduced air temperature and Wet Bulb Globe Temperature (WBGT). Notably, hybrid shade—artificial structures complemented by adjacent trees—exhibited superior cooling performance compared to other shade types. While the average cooling effects of tree shade and artificial shade were generally similar, the cooling effect of tree shade, which was relatively weak during the morning, became stronger than that of artificial shade in the afternoon. Moreover, shade conditions characterized by high density that can maintain low lux levels consistently demonstrate greater cooling effectiveness. These insights can help explain the inconsistencies in previous findings on the effects of shade. These findings highlight the importance of incorporating shade provision into urban planning to maximize cooling benefits. Ultimately, the improved understanding of shade effects will contribute to decision-making in cooling cities to respond to future climate change.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106855"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cooling effects of urban green spaces: A systematic review of methods applied in the past two decades","authors":"Jiongye Li ,&nbsp;Sisi Zlatanova ,&nbsp;Rudi Stouffs","doi":"10.1016/j.scs.2025.106833","DOIUrl":"10.1016/j.scs.2025.106833","url":null,"abstract":"<div><div>Research on the cooling effects of Urban Green Spaces (UGSs) has increased rapidly in recent years to address the pressing issue of Urban Heat Island (UHI). Several review papers have conducted literature review focusing on various perspectives, such as landscape metrics and correlation analyses. However, a thorough review of the methods and their components applied in this field has yet to be conducted. This review paper identifies and examines 215 relevant papers selected through the PRISMA standard, yielding several key findings. Firstly, from a temporal aspect, research in this field has grown since 2017, with a notable acceleration after 2021. Geographically, studies are concentrated in China, the USA, India, and European countries. Secondly, regarding used methods, while most studies tend to employ a single method, more recent research has begun to integrate multiple methods. Furthermore, we also found that remote sensing data can be applied across most common methods, including regression and correlation models. In contrast, certain methods, such as simulation models, are typically associated with ground-based data. Overall, this review is the first to conduct a comprehensive analysis of the methods used and their components from both a temporal and quantitative perspective. It also identifies the associations between used data, variables, and methods, and how they influence selections of each other. The findings can assist future studies in identifying appropriate methods based on their research contexts.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106833"},"PeriodicalIF":12.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}