Pub Date : 2026-01-01DOI: 10.1016/j.cacint.2026.100294
Yu-Yun Liu , Yin-Hao Chiu , Sung-Ta Liu
Climate change intensifies urban heat, affecting residents’ use of low-carbon transportation and participation in outdoor activities. This study surveyed six municipalities in Taiwan to assess how different population groups respond under normal and high-temperature conditions. Latent profile analysis of survey data identified five psycho-behavioral segments—HeatSensitive, TransportSensitive, HeatEndurer, HeatProofer, and OutdoorSensitive—each exhibiting distinct psychographic, socioeconomic, regional, and behavioral characteristics. Results indicate that high temperatures significantly reduce intentions to engage in low-carbon transportation and outdoor activities, with older adults and lower-income groups being most affected. In contrast, residents with higher socioeconomic status demonstrate greater resilience, maintaining both mobility and outdoor activity. These findings highlight the need for targeted policy interventions, including climate adaptation communications, transit-oriented urban planning, and shaded public spaces, to promote inclusive, equitable, and climate-resilient urban adaptation strategies.
{"title":"Effects of high urban temperatures on use of low-carbon transportation and participation in outdoor physical activities","authors":"Yu-Yun Liu , Yin-Hao Chiu , Sung-Ta Liu","doi":"10.1016/j.cacint.2026.100294","DOIUrl":"10.1016/j.cacint.2026.100294","url":null,"abstract":"<div><div>Climate change intensifies urban heat, affecting residents’ use of low-carbon transportation and participation in outdoor activities. This study surveyed six municipalities in Taiwan to assess how different population groups respond under normal and high-temperature conditions. Latent profile analysis of survey data identified five psycho-behavioral segments—HeatSensitive, TransportSensitive, HeatEndurer, HeatProofer, and OutdoorSensitive—each exhibiting distinct psychographic, socioeconomic, regional, and behavioral characteristics. Results indicate that high temperatures significantly reduce intentions to engage in low-carbon transportation and outdoor activities, with older adults and lower-income groups being most affected. In contrast, residents with higher socioeconomic status demonstrate greater resilience, maintaining both mobility and outdoor activity. These findings highlight the need for targeted policy interventions, including climate adaptation communications, transit-oriented urban planning, and shaded public spaces, to promote inclusive, equitable, and climate-resilient urban adaptation strategies.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100294"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.cacint.2026.100301
Heiko Aydt , Juan Angel Acero , Jordan Ivanchev , Ido Nevat , Ayu Sukma Adelia , Jerin Benny Chalakkal , Mathias Niffeler , Minn Lin Wong , Ander Zozaya , Kristina Orehounig
Urban climate is influenced by many different factors, and identifying the optimal set of measures to improve well-being in cities requires expertise and information from different fields and tools to support planners and decision makers. In this paper, we present a Digital Urban Climate Twin (DUCT) that couples relevant computational models with various accessible data sets in cities to evaluate their impact on indicators related to urban climate and energy efficiency. The DUCT focuses on integrating climate models at the meso(city)- and micro(neighbourhood)- scales with anthropogenic heat emission models from buildings, traffic, industry, and power plants, which are not explicitly resolved in their original setup. The digital twin is structured into three subsystems: a Simulation-as-a-Service platform, the federation of models, and an easy-to-use user interface. The concept of the Digital Urban Climate Twin has been applied to the city of Singapore to demonstrate the methodology.
{"title":"Tools to manage Singapore’s heat: Coupled climate and anthropogenic heat emission models for urban comfort in a digital twin framework","authors":"Heiko Aydt , Juan Angel Acero , Jordan Ivanchev , Ido Nevat , Ayu Sukma Adelia , Jerin Benny Chalakkal , Mathias Niffeler , Minn Lin Wong , Ander Zozaya , Kristina Orehounig","doi":"10.1016/j.cacint.2026.100301","DOIUrl":"10.1016/j.cacint.2026.100301","url":null,"abstract":"<div><div>Urban climate is influenced by many different factors, and identifying the optimal set of measures to improve well-being in cities requires expertise and information from different fields and tools to support planners and decision makers. In this paper, we present a Digital Urban Climate Twin (DUCT) that couples relevant computational models with various accessible data sets in cities to evaluate their impact on indicators related to urban climate and energy efficiency. The DUCT focuses on integrating climate models at the meso(city)- and micro(neighbourhood)- scales with anthropogenic heat emission models from buildings, traffic, industry, and power plants, which are not explicitly resolved in their original setup. The digital twin is structured into three subsystems: a Simulation-as-a-Service platform, the federation of models, and an easy-to-use user interface. The concept of the Digital Urban Climate Twin has been applied to the city of Singapore to demonstrate the methodology.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100301"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contemporary urban planning faces many challenges. Cities worldwide need to cope with rapid urbanisation, inequality, environmental pressures, and changing populations. To respond effectively, it is essential to use modern technologies to understand urban dynamics better. Cities must also adopt flexible and innovative strategies that prioritise sustainable development. The study employs a comprehensive approach combining Geographic Information Systems (GIS) and historical analysis. The goal is to examine how Muesmann’s plan has influenced today’s urban infrastructure and green spaces in Sofia, Bulgaria. The findings show that Muesmann’s ideas, especially about green spaces and zoning, have strongly shaped Sofia’s growth.
This can be seen in the city’s radial layout, the railway and airport expansion, the building of the ring road, and the link between parks and urban areas. Based on these findings, the study suggests that Muesmann’s contributions should be recognised. His master plan can still guide modern planning when combined with new tools, such as zoning and long-term vision. The findings are relevant not only to Sofia but also to other contexts, such as post-socialist cities, urban environments shaped by Garden City legacies, and cities where master plans were only partially implemented. They demonstrate how historical ideas can be combined with modern strategies for sustainable growth.
{"title":"Influence of Muesmann’s plan on contemporary urban planning in Sofia City","authors":"Lidia Lazarova Vitanova , Shigehisa Matsumura , Dessislava Petrova-Antonova","doi":"10.1016/j.cacint.2026.100303","DOIUrl":"10.1016/j.cacint.2026.100303","url":null,"abstract":"<div><div>Contemporary urban planning faces many challenges. Cities worldwide need to cope with rapid urbanisation, inequality, environmental pressures, and changing populations. To respond effectively, it is essential to use modern technologies to understand urban dynamics better. Cities must also adopt flexible and innovative strategies that prioritise sustainable development. The study employs a comprehensive approach combining Geographic Information Systems (GIS) and historical analysis. The goal is to examine how Muesmann’s plan has influenced today’s urban infrastructure and green spaces in Sofia, Bulgaria. The findings show that Muesmann’s ideas, especially about green spaces and zoning, have strongly shaped Sofia’s growth.</div><div>This can be seen in the city’s radial layout, the railway and airport expansion, the building of the ring road, and the link between parks and urban areas. Based on these findings, the study suggests that Muesmann’s contributions should be recognised. His master plan can still guide modern planning when combined with new tools, such as zoning and long-term vision. The findings are relevant not only to Sofia but also to other contexts, such as post-socialist cities, urban environments shaped by Garden City legacies, and cities where master plans were only partially implemented. They demonstrate how historical ideas can be combined with modern strategies for sustainable growth.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100303"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.cacint.2026.100313
Wirat Parntrasri , Sitthichok Puangthongthub
In Northeastern (NE) Thailand, cardiovascular mortality can increase during brief PM2.5 surges; however, subnational health risks associated with extreme events remain poorly characterized. We constructed a province-week panel (2017–2023) by linking de-identified vital statistics for cardiovascular disease (CVD) and ischemic heart disease (IHD) with routine PM2.5 monitoring data. The analysis was restricted to 10 of 20 NE provinces with continuously operating monitors meeting predefined completeness criteria, enabling consistent weekly time-series inference. We estimated weekly attributable deaths (ADwk) using short-term concentration–response functions with lag01 exposure over a WHO-consistent counterfactual (b15 = 15 µg/m3). We then quantified extreme mortality surges using Extreme Value Theory (EVT) via generalized extreme-value (GEV) models for annual maxima and peaks-over-threshold generalized Pareto (POT–GPD) models for weekly exceedances, yielding return levels (RLT, T = 2–50 years). Return-level results indicated that rare haze-related weeks can substantially exceed typical weekly burdens, with risks clustering in the dry season (November-April; peaking December-March). The highest return levels occurred in Khon Kaen, Nakhon Ratchasima, and Ubon Ratchathani, where RL5 exceeded baseline ADwk by more than 2.5-fold. Nine province-cause series (CVD = 4; IHD = 5) met quality standards and showed acceptable cross-framework RL5 concordance (Set B). Complementary 26-week province-specific forecasts provided near-term situational awareness consistent with seasonal haze dynamics. Although the analysis relies on ambient PM2.5 observations without source apportionment, the findings underscore the public health significance of episodic haze extremes and support early-warning and preparedness strategies alongside long-term air-quality mitigation.
{"title":"Weekly extremes of PM2.5-attributable cardiovascular mortality in Northeastern Thailand: Extreme-value return levels and 26-week forecasts","authors":"Wirat Parntrasri , Sitthichok Puangthongthub","doi":"10.1016/j.cacint.2026.100313","DOIUrl":"10.1016/j.cacint.2026.100313","url":null,"abstract":"<div><div>In Northeastern (NE) Thailand, cardiovascular mortality can increase during brief PM<sub>2.5</sub> surges; however, subnational health risks associated with extreme events remain poorly characterized. We constructed a province-week panel (2017–2023) by linking de-identified vital statistics for cardiovascular disease (CVD) and ischemic heart disease (IHD) with routine PM<sub>2.5</sub> monitoring data. The analysis was restricted to 10 of 20 NE provinces with continuously operating monitors meeting predefined completeness criteria, enabling consistent weekly time-series inference. We estimated weekly attributable deaths (AD<sub>wk</sub>) using short-term concentration–response functions with lag<sub>01</sub> exposure over a WHO-consistent counterfactual (b<sub>15</sub> = 15 µg/m<sup>3</sup>). We then quantified extreme mortality surges using Extreme Value Theory (EVT) via generalized extreme-value (GEV) models for annual maxima and peaks-over-threshold generalized Pareto (POT–GPD) models for weekly exceedances, yielding return levels (RL<em><sub>T</sub></em>, T = 2–50 years). Return-level results indicated that rare haze-related weeks can substantially exceed typical weekly burdens, with risks clustering in the dry season (November-April; peaking December-March). The highest return levels occurred in Khon Kaen, Nakhon Ratchasima, and Ubon Ratchathani, where RL<sub>5</sub> exceeded baseline AD<sub>wk</sub> by more than 2.5-fold. Nine province-cause series (CVD = 4; IHD = 5) met quality standards and showed acceptable cross-framework RL<sub>5</sub> concordance (Set B). Complementary 26-week province-specific forecasts provided near-term situational awareness consistent with seasonal haze dynamics. Although the analysis relies on ambient PM<sub>2.5</sub> observations without source apportionment, the findings underscore the public health significance of episodic haze extremes and support early-warning and preparedness strategies alongside long-term air-quality mitigation.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100313"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.cacint.2026.100302
Nils Eingrüber , Paul Berg , Wolfgang Korres , Ulrich Löhnert , Karl Schneider
Due to the expected increase in global temperature together with a predicted further densification of cities leading to an exacerbation of the urban heat island effect, health consequences caused by heat stress will become a growing risk for urban dwellers. Therefore, climate change adaptation is of particular importance for future urban planning, utilizing technical and nature-based solutions. High-resolution microclimate modelling and scenario analyses are a promising approach to evaluate thermal effects of climate change adaptation measures in urban areas. Aiming to gain knowledge regarding the involvement of citizen science into high-resolution urban microclimate modelling on quarter-scale and investigating effects of urban acupuncture in the context of heat mitigation, a physically-based, 3D-gridded ENVI-met model is setup and parameterized based on field measurements for a 16-ha residential study area in Cologne/Germany. The model is validated using a quality-controlled, standardized and distributed citizen science network of 57 sensors within the heterogeneous study area. The establishment of the citizen science network combines the scientific requirement of high resolution and accuracy with the participation and activation of stakeholders needed for later implementation of climate change adaptation measures. The study presented here is unique with respect to integration of citizen science into numerical modelling and with regards to the holistic model validation approach on a city quarter-scale including a 20-year heat event in Cologne in July 2022. A mean Nash-Sutcliffe model efficiency of 0.89 up to 0.97 for simulated air temperature underlines the accurate fit of the model to citizen sensor measurements. Significant microclimatic patterns and mean differences of up to 4.8 Kelvin between spatial units like greened inner courtyards and ungreened street corridors were identified within the study area. In the context of urban acupuncture, this shows the heat mitigation potential of climate change adaptation measures which can enable cooling effects in a magnitude of global warming and being relevant for increasing thermal comfort and human wellbeing.
{"title":"Parameterization and citizen science based validation of a high-resolution microclimate model to identify temperature patterns in a climate change adapted urban high-density area","authors":"Nils Eingrüber , Paul Berg , Wolfgang Korres , Ulrich Löhnert , Karl Schneider","doi":"10.1016/j.cacint.2026.100302","DOIUrl":"10.1016/j.cacint.2026.100302","url":null,"abstract":"<div><div>Due to the expected increase in global temperature together with a predicted further densification of cities leading to an exacerbation of the urban heat island effect, health consequences caused by heat stress will become a growing risk for urban dwellers. Therefore, climate change adaptation is of particular importance for future urban planning, utilizing technical and nature-based solutions. High-resolution microclimate modelling and scenario analyses are a promising approach to evaluate thermal effects of climate change adaptation measures in urban areas. Aiming to gain knowledge regarding the involvement of citizen science into high-resolution urban microclimate modelling on quarter-scale and investigating effects of urban acupuncture in the context of heat mitigation, a physically-based, 3D-gridded ENVI-met model is setup and parameterized based on field measurements for a 16-ha residential study area in Cologne/Germany. The model is validated using a quality-controlled, standardized and distributed citizen science network of 57 sensors within the heterogeneous study area. The establishment of the citizen science network combines the scientific requirement of high resolution and accuracy with the participation and activation of stakeholders needed for later implementation of climate change adaptation measures. The study presented here is unique with respect to integration of citizen science into numerical modelling and with regards to the holistic model validation approach on a city quarter-scale including a 20-year heat event in Cologne in July 2022. A mean Nash-Sutcliffe model efficiency of 0.89 up to 0.97 for simulated air temperature underlines the accurate fit of the model to citizen sensor measurements. Significant microclimatic patterns and mean differences of up to 4.8 Kelvin between spatial units like greened inner courtyards and ungreened street corridors were identified within the study area. In the context of urban acupuncture, this shows the heat mitigation potential of climate change adaptation measures which can enable cooling effects in a magnitude of global warming and being relevant for increasing thermal comfort and human wellbeing.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100302"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cultural and Educational Facilities are essential public resources that contribute to urban development and residents’ cultural engagement. As the capital of China, Beijing serves multiple functions as a political decision-making center, a cultural and educational highland, and a historical heritage core. This study applies spatial analysis based on POI data from 2012, 2018, and 2024 to examine spatial clustering patterns and their temporal evolution. A Multiscale Geographically Weighted Regression (MGWR) model is used to assess the influence of urban infrastructure factors on the spatial distribution of various facility types. Results show that Cultural and Educational Facilities are predominantly concentrated in central urban districts, including Dongcheng and Xicheng. Over time, policy interventions have promoted dispersion, with increasing facility presence in urban subcenters. The spatial distribution has also become more balanced, with reduced clustering in the main urban areas and accelerated development in the Tongzhou and Chaoyang districts. Furthermore, bus stop density, subway station density, and hotel density significantly impact the spatial distribution of these facilities. However, their effects vary between different types of facility, demonstrating substantial spatial heterogeneity. The findings expand our understanding of the spatial dynamics in these facilities. They also provide new insights for optimizing urban facility planning.
{"title":"Spatial distribution and influencing factors of cultural and educational facilities in Beijing: A POI-based analysis using MGWR","authors":"Ke Xiao, Ningning Wang, Meng Liu, Qinsheng Wang, Jiaqi Wang, Yutong Ren","doi":"10.1016/j.cacint.2026.100312","DOIUrl":"10.1016/j.cacint.2026.100312","url":null,"abstract":"<div><div>Cultural and Educational Facilities are essential public resources that contribute to urban development and residents’ cultural engagement. As the capital of China, Beijing serves multiple functions as a political decision-making center, a cultural and educational highland, and a historical heritage core. This study applies spatial analysis based on POI data from 2012, 2018, and 2024 to examine spatial clustering patterns and their temporal evolution. A Multiscale Geographically Weighted Regression (MGWR) model is used to assess the influence of urban infrastructure factors on the spatial distribution of various facility types. Results show that Cultural and Educational Facilities are predominantly concentrated in central urban districts, including Dongcheng and Xicheng. Over time, policy interventions have promoted dispersion, with increasing facility presence in urban subcenters. The spatial distribution has also become more balanced, with reduced clustering in the main urban areas and accelerated development in the Tongzhou and Chaoyang districts. Furthermore, bus stop density, subway station density, and hotel density significantly impact the spatial distribution of these facilities. However, their effects vary between different types of facility, demonstrating substantial spatial heterogeneity. The findings expand our understanding of the spatial dynamics in these facilities. They also provide new insights for optimizing urban facility planning.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100312"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.cacint.2026.100296
Rida Azmi , Jérôme Chenal , El Bachir Diop , Seyid Abdellahi Ebnou Abdem , Mariem Bounabi , Mohammed Hlal , Meriem Adraoui , Tarik Chafiq
This study provides a scoping review of urban data usage in African cities over the past 25 years, leveraging advanced Natural Language Processing − NLP, Machine Learning − ML, and hybrid approaches to classify urban data. The fine-tuned classification framework demonstrated robust performance, achieving an accuracy of 91.76 % in classifying relevant abstracts, with calibrated confidence scores ensuring reliable and evidence-aligned predictions. Topic modeling analysis is used combined with a personalized dictionary to extract five urban data typologies: Spatial, Digital, Commercial, Public Sector, and Sensor Data. These typologies are mapped to 15 urban contexts, revealing significant regional disparities that offer deeper insights into local practices, successes, and deficiencies. The model’s ability to capture well-defined contexts, such as Urban Settlement & Housing, highlights its strength, while lower confidence in overlapping themes, such as Urban Environment & Climate, underscores the complexity of these categories. Rigorous validation, including stratified k-fold cross-validation and stability testing of topic modeling parameters, ensures the replicability and generalizability of the framework.
To move beyond descriptive comparisons, we conducted a chi-square analysis, which revealed a statistically significant but modest association between geographic regions and urban research themes across Africa (χ2 = 219.88, df = 36, p < 0.001; Cramér’s V = 0.120), confirming that observed regional disparities reflect genuine differences in research priorities rather than random variation. The analysis reveals three continental patterns in urban research: Environment & Climate dominates overall but is unevenly distributed, with strong concentration in Southern and North Africa, while Health & Sanitation shows a clear East/West versus North/South divide. Infrastructure research exhibits the greatest regional inequality, with relative specialization in Southern Africa and under-representation in East and West Africa, likely to reflect differences in research capacity, funding, and development trajectories.
These findings not only provide actionable insights into regional urban research priorities but also establish a replicable methodology for systematically analyzing urban data in diverse and resource-constrained settings.
本研究利用先进的自然语言处理（NLP）、机器学习（ML）和混合方法对城市数据进行分类，对过去25年来非洲城市的城市数据使用情况进行了范围审查。经过微调的分类框架表现出稳健的性能，在分类相关摘要方面达到了91.76%的准确率，校准的置信度评分确保了可靠和证据一致的预测。主题建模分析与个性化词典结合使用，提取五种城市数据类型：空间、数字、商业、公共部门和传感器数据。这些类型学被映射到15个城市背景中，揭示了显著的区域差异，为当地实践、成功和不足提供了更深入的见解。该模型能够捕获定义良好的背景，如城市住区和住房，这突出了它的优势，而对重叠主题（如城市环境和气候）的信心较低，则突出了这些类别的复杂性。严格的验证，包括分层k-fold交叉验证和主题建模参数的稳定性测试，确保了框架的可复制性和泛化性。为了超越描述性比较，我们进行了卡方分析，揭示了非洲各地地理区域和城市研究主题之间存在统计学上显著但适度的关联（χ2 = 219.88, df = 36, p < 0.001; cram s V = 0.120），证实了观察到的区域差异反映了研究重点的真正差异，而不是随机变化。分析揭示了城市研究中的三种大陆模式：环境和气候总体上占主导地位，但分布不均匀，主要集中在南部和北非，而卫生和卫生显示出明显的东/西与北/南鸿沟。基础设施研究表现出最大的区域不平等，南部非洲相对专业化，东非和西非代表性不足，这可能反映了研究能力、资金和发展轨迹的差异。这些发现不仅为区域城市研究重点提供了可操作的见解，而且还建立了一种可复制的方法，用于系统地分析不同资源受限环境下的城市数据。
{"title":"A computational framework for analyzing urban data usage patterns in African cities: a 25-year data-driven review using natural language processing and machine learning","authors":"Rida Azmi , Jérôme Chenal , El Bachir Diop , Seyid Abdellahi Ebnou Abdem , Mariem Bounabi , Mohammed Hlal , Meriem Adraoui , Tarik Chafiq","doi":"10.1016/j.cacint.2026.100296","DOIUrl":"10.1016/j.cacint.2026.100296","url":null,"abstract":"<div><div>This study provides a scoping review of urban data usage in African cities over the past 25 years, leveraging advanced Natural Language Processing − NLP, Machine Learning − ML, and hybrid approaches to classify urban data. The fine-tuned classification framework demonstrated robust performance, achieving an accuracy of 91.76 % in classifying relevant abstracts, with calibrated confidence scores ensuring reliable and evidence-aligned predictions. Topic modeling analysis is used combined with a personalized dictionary to extract five urban data typologies: Spatial, Digital, Commercial, Public Sector, and Sensor Data. These typologies are mapped to 15 urban contexts, revealing significant regional disparities that offer deeper insights into local practices, successes, and deficiencies. The model’s ability to capture well-defined contexts, such as Urban Settlement & Housing, highlights its strength, while lower confidence in overlapping themes, such as Urban Environment & Climate, underscores the complexity of these categories. Rigorous validation, including stratified k-fold cross-validation and stability testing of topic modeling parameters, ensures the replicability and generalizability of the framework.</div><div>To move beyond descriptive comparisons, we conducted a chi-square analysis, which revealed a statistically significant but modest association between geographic regions and urban research themes across Africa (χ<sup>2</sup> = 219.88, df = 36, p < 0.001; Cramér’s V = 0.120), confirming that observed regional disparities reflect genuine differences in research priorities rather than random variation. The analysis reveals three continental patterns in urban research: Environment & Climate dominates overall but is unevenly distributed, with strong concentration in Southern and North Africa, while Health & Sanitation shows a clear East/West versus North/South divide. Infrastructure research exhibits the greatest regional inequality, with relative specialization in Southern Africa and under-representation in East and West Africa, likely to reflect differences in research capacity, funding, and development trajectories.</div><div>These findings not only provide actionable insights into regional urban research priorities but also establish a replicable methodology for systematically analyzing urban data in diverse and resource-constrained settings.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100296"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.cacint.2026.100306
Chané de Bruyn , Foued Ben Said , Marius Venter , Rui Alexandre Castanho
Cities around the world are facing unprecedented challenges related to climate change, demanding innovative solutions and strategic adaptation. This study carries out an in-depth bibliometric analysis of the growing research on smart cities and climate change adaptation, exploring how technological advances can improve urban resilience and sustainability. By analyzing 1348 documents from the Scopus and Web of Science databases (2009–2024), we identify the main research trends, influential authors and journals, as well as the main thematic groups. Our results reveal a growing attention paid to the integration of artificial intelligence, the Internet of Things and big data analysis in urban planning and governance for climate change mitigation and adaptation. In particular, we identify critical gaps in research, including the need for holistic evaluation frameworks, improved citizen participation strategies and reducing the gap between technological potential and actual implementation. This analysis provides an essential roadmap for future research and policy development, guiding the transition to climate-resilient smart cities.
世界各地的城市都面临着与气候变化有关的前所未有的挑战，需要创新的解决方案和战略适应。本研究对越来越多的关于智慧城市和气候变化适应的研究进行了深入的文献计量分析，探讨了技术进步如何提高城市的韧性和可持续性。通过对Scopus和Web of Science数据库（2009-2024）1348篇文献的分析，我们确定了主要的研究趋势、有影响力的作者和期刊以及主要的专题群体。我们的研究结果表明，人们越来越关注将人工智能、物联网和大数据分析整合到城市规划和治理中，以减缓和适应气候变化。我们特别指出了研究中的关键差距，包括对整体评估框架的需求、改进的公民参与战略以及缩小技术潜力与实际实施之间的差距。这一分析为未来的研究和政策制定提供了重要的路线图，指导向气候适应型智慧城市的过渡。
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Pub Date : 2025-12-15DOI: 10.1016/j.cacint.2025.100281
Sara Marzio , Jacopo Tosi , Francesca Poggi , Miguel Amado
Urban waterfronts, as dynamic interfaces between land and water, face increasing vulnerability due to climate change-induced risks such as sea-level rise, flooding, and extreme weather events, compounded by anthropogenic pressures like urbanisation, pollution, and habitat loss. Traditional hard engineering solutions, while effective in structural resilience, often neglect ecological and social dimensions. Nature-based Solutions have emerged as transformative approaches capable of addressing these multifaceted challenges, offering multifunctional benefits that integrate ecological restoration, climate adaptation and urban liveability. Despite their potential, their application in urbanised waterfronts needs a better understanding, as these techniques have traditionally been adopted in landscapes where land availability allows for larger-scale ecological interventions. This study aims to address this research gap by systematically reviewing academic literature and analysing real-world case studies to examine how NbS are conceptualised, implemented and assessed in urban waterfront regeneration. The findings identified recurring frameworks, analytical dimensions and three strategic orientations: (1) retrofitting waterfront edges with hybrid green-grey solutions to enhance resilience and biodiversity, (2) systemic ecological restoration of degraded waterfront environments and (3) increasing permeability through water-sensitive urban systems. The analysis highlights the multifunctionality of NbS, their capacity to balance ecological, social, and infrastructural objectives, and the prevalence of hybrid approaches in more space-constrained contexts. However, gaps remain in post-implementation monitoring and long-term performance evaluation. This review underscores the need for operational guidelines to scale NbS in urban waterfronts, particularly in underrepresented regions, and emphasises their role as systemic interventions for adaptive urban resilience.
{"title":"Nature-based solutions for urban waterfront regeneration: a systematic review of frameworks, strategies and applications","authors":"Sara Marzio , Jacopo Tosi , Francesca Poggi , Miguel Amado","doi":"10.1016/j.cacint.2025.100281","DOIUrl":"10.1016/j.cacint.2025.100281","url":null,"abstract":"<div><div>Urban waterfronts, as dynamic interfaces between land and water, face increasing vulnerability due to climate change-induced risks such as sea-level rise, flooding, and extreme weather events, compounded by anthropogenic pressures like urbanisation, pollution, and habitat loss. Traditional hard engineering solutions, while effective in structural resilience, often neglect ecological and social dimensions. Nature-based Solutions have emerged as transformative approaches capable of addressing these multifaceted challenges, offering multifunctional benefits that integrate ecological restoration, climate adaptation and urban liveability. Despite their potential, their application in urbanised waterfronts needs a better understanding, as these techniques have traditionally been adopted in landscapes where land availability allows for larger-scale ecological interventions. This study aims to address this research gap by systematically reviewing academic literature and analysing real-world case studies to examine how NbS are conceptualised, implemented and assessed in urban waterfront regeneration. The findings identified recurring frameworks, analytical dimensions and three strategic orientations: (1) retrofitting waterfront edges with hybrid green-grey solutions to enhance resilience and biodiversity, (2) systemic ecological restoration of degraded waterfront environments and (3) increasing permeability through water-sensitive urban systems. The analysis highlights the multifunctionality of NbS, their capacity to balance ecological, social, and infrastructural objectives, and the prevalence of hybrid approaches in more space-constrained contexts. However, gaps remain in post-implementation monitoring and long-term performance evaluation. This review underscores the need for operational guidelines to scale NbS in urban waterfronts, particularly in underrepresented regions, and emphasises their role as systemic interventions for adaptive urban resilience.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100281"},"PeriodicalIF":3.8,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As urban populations increase and tall residential buildings gradually define city skylines, their impact on microclimate and human activity in open spaces has become a critical matter for sustainable urban design. Despite growing attention to outdoor thermal comfort, most existing studies rely on simulation-based thermal indices with limited connection to real-world behavior. This study addresses this gap through investigating how tall residential structures affect both thermal conditions and actual patterns of human activity, such as walking, cycling, sitting, and socializing, in urban open spaces where both tall and low-rise buildings coexist. The novelty of this research lies in its mixed-methods approach, combining year-round behavioral mapping with microclimatic simulations using Ladybug and Honeybee tools. This study was conducted in Istanbul, which has a temperate Mediterranean climate, from 2023 to2024. The proposed methodology is a combination of experimental observations with software analyses which includes Grasshopper, Ladybug, and Honeybee based on environmental data to evaluate pedestrian comfort and space usability in different urban morphologies. The findings of this study suggest that low-rise areas have better thermal and social performance, while conditions in spaces adjacent to tall buildings are less usable. However, environmental variables such as shade, urban furniture, and wind flow play a role in these effects. Finally, this study provides practical guidelines for urban designers and planners to enhance both thermal resilience and social livability in urban environments.
{"title":"The influence of building height on microclimate and human activities in urban open spaces","authors":"Mehrdad Karimimoshaver , Alireza Gerami , Banu Ozkazanc , Amir Mosavi","doi":"10.1016/j.cacint.2025.100283","DOIUrl":"10.1016/j.cacint.2025.100283","url":null,"abstract":"<div><div>As urban populations increase and tall residential buildings gradually define city skylines, their impact on microclimate and human activity in open spaces has become a critical matter for sustainable urban design. Despite growing attention to outdoor thermal comfort, most existing studies rely on simulation-based thermal indices with limited connection to real-world behavior. This study addresses this gap through investigating how tall residential structures affect both thermal conditions and actual patterns of human activity, such as walking, cycling, sitting, and socializing, in urban open spaces where both tall and low-rise buildings coexist. The novelty of this research lies in its mixed-methods approach, combining year-round behavioral mapping with microclimatic simulations using Ladybug and Honeybee tools. This study was conducted in Istanbul, which has a temperate Mediterranean climate, from 2023 to2024. The proposed methodology is a combination of experimental observations with software analyses which includes Grasshopper, Ladybug, and Honeybee based on environmental data to evaluate pedestrian comfort and space usability in different urban morphologies. The findings of this study suggest that low-rise areas have better thermal and social performance, while conditions in spaces adjacent to tall buildings are less usable. However, environmental variables such as shade, urban furniture, and wind flow play a role in these effects. Finally, this study provides practical guidelines for urban designers and planners to enhance both thermal resilience and social livability in urban environments.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100283"},"PeriodicalIF":3.8,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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