Environmental characteristics affect how individuals perceive an environment, and the emotions created by environmental characteristics originate from subjective feelings. Despite cities being crucial human living spaces, few studies have used geospatial technology to determine the relationship between urban environments and emotions. Therefore, this study explored the effects of urban environmental characteristics on emotions by surveying 50 sampling areas in Taipei City. Deep learning was performed with the DeepLab V3 architecture in combination with the LaDeco tool to identify environmental characteristics in over 200,000 Google Street View (GSV) images. These characteristics were divided into five major types, namely, vegetationscapes, waterscapes, streetscapes, landformscapes, and archiscapes, then further classified into 53 categories. To identify the emotions related to urban environments, 2090 participants who were asked to view GSV videos and report their emotions. Subsequent multiple regression analyses revealed that in vegetationscapes and waterscapes, grass and fountains induced positive emotions, whereas trees reduced negative emotions. Meanwhile, dense, old, and disorganized buildings, such as hovels, reduced positive emotions. The results of this study may serve as a reference to help designers create an urban environment that fosters positive emotions.
{"title":"Revealing emotional responses to urban environmental elements through street view data and deep learning.","authors":"Li-Chih Ho, Yin-Ting Wei, Dongying Li, Yen-Cheng Chiang","doi":"10.1177/23998083251348280","DOIUrl":"10.1177/23998083251348280","url":null,"abstract":"<p><p>Environmental characteristics affect how individuals perceive an environment, and the emotions created by environmental characteristics originate from subjective feelings. Despite cities being crucial human living spaces, few studies have used geospatial technology to determine the relationship between urban environments and emotions. Therefore, this study explored the effects of urban environmental characteristics on emotions by surveying 50 sampling areas in Taipei City. Deep learning was performed with the DeepLab V3 architecture in combination with the LaDeco tool to identify environmental characteristics in over 200,000 Google Street View (GSV) images. These characteristics were divided into five major types, namely, vegetationscapes, waterscapes, streetscapes, landformscapes, and archiscapes, then further classified into 53 categories. To identify the emotions related to urban environments, 2090 participants who were asked to view GSV videos and report their emotions. Subsequent multiple regression analyses revealed that in vegetationscapes and waterscapes, grass and fountains induced positive emotions, whereas trees reduced negative emotions. Meanwhile, dense, old, and disorganized buildings, such as hovels, reduced positive emotions. The results of this study may serve as a reference to help designers create an urban environment that fosters positive emotions.</p>","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12629224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145562486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-04DOI: 10.1177/23998083251325909
Rui Zhu, Yang Song, Galen Newman
Urban green space disparities persist amid rapid urbanization, widening the supply-demand gap between parks and developed area. Population density is a critical determinant in estimating park visitors, defining suitable park locations, and allocating facilities for park accessibility. Conventionally, population density data were used as a foundational basis for urban green space planning decisions, often derived from sources like the US Census Bureau, primarily reflecting "nighttime residential" distribution. However, this approach fails to capture the dynamic urban life where daily routines and mobility significantly shape park usage. This study bridges this gap by exploring the relationship between daytime and nighttime mobility patterns and their influence on park visitations across diverse park types during weekdays, using Austin, TX as study area. Methodologically, we employ a fixed effects regression analysis integrating longitudinal data from SafeGraph for park visitation and LandScan USA for daytime-to-nighttime population density ratios, within 1 km buffers around each park. Control variables encompass socio-economic factors at the block group scale, park attributes, and weather conditions. Findings suggest that neighborhood and pocket parks demonstrate positive associations with daytime population density, while district and metropolitan parks exhibit stronger ties with nighttime population density. Further, median age, unemployment rate, and higher education attainment exhibit positive correlations with park visitation, especially during daytime. Park amenities, especially playgrounds and water features, significantly contribute to increased visitation across all park types. The findings offer valuable guidance for policymakers and urban planners, informing the reimagining of park distribution strategies, optimizing facilities, and fostering inclusive park spaces accessibility.
{"title":"Exploring the relationship between daytime and nighttime mobility and park visitation: A case study of Austin, TX.","authors":"Rui Zhu, Yang Song, Galen Newman","doi":"10.1177/23998083251325909","DOIUrl":"10.1177/23998083251325909","url":null,"abstract":"<p><p>Urban green space disparities persist amid rapid urbanization, widening the supply-demand gap between parks and developed area. Population density is a critical determinant in estimating park visitors, defining suitable park locations, and allocating facilities for park accessibility. Conventionally, population density data were used as a foundational basis for urban green space planning decisions, often derived from sources like the US Census Bureau, primarily reflecting \"nighttime residential\" distribution. However, this approach fails to capture the dynamic urban life where daily routines and mobility significantly shape park usage. This study bridges this gap by exploring the relationship between daytime and nighttime mobility patterns and their influence on park visitations across diverse park types during weekdays, using Austin, TX as study area. Methodologically, we employ a fixed effects regression analysis integrating longitudinal data from SafeGraph for park visitation and LandScan USA for daytime-to-nighttime population density ratios, within 1 km buffers around each park. Control variables encompass socio-economic factors at the block group scale, park attributes, and weather conditions. Findings suggest that neighborhood and pocket parks demonstrate positive associations with daytime population density, while district and metropolitan parks exhibit stronger ties with nighttime population density. Further, median age, unemployment rate, and higher education attainment exhibit positive correlations with park visitation, especially during daytime. Park amenities, especially playgrounds and water features, significantly contribute to increased visitation across all park types. The findings offer valuable guidance for policymakers and urban planners, informing the reimagining of park distribution strategies, optimizing facilities, and fostering inclusive park spaces accessibility.</p>","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12412770/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145014215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1177/23998083251316064
Xinyue Ye, Tianchen Huang, Yang Song, Xin Li, Galen Newman, Dayong Jason Wu, Yijun Zeng
This study explores the integration of text-to-image generative AI, particularly Stable Diffusion, in conjunction with ControlNet and LoRA models in conceptual landscape design. Traditional methods in landscape design are often time-consuming and limited by the designer's individual creativity, also often lacking efficiency in the exploration of diverse design solutions. By leveraging AI tools, we demonstrate a workflow that efficiently generates detailed and visually coherent landscape designs, including natural parks, city plazas, and courtyard gardens. Through both qualitative and quantitative evaluations, our results indicate that fine-tuned models produce superior designs compared to non-fine-tuned models, maintaining spatial consistency, control over scale, and relevant landscape elements. This research advances the efficiency of conceptual design processes and underscores the potential of AI in enhancing creativity and innovation in landscape architecture.
{"title":"Generating conceptual landscape design via text-to-image generative AI model.","authors":"Xinyue Ye, Tianchen Huang, Yang Song, Xin Li, Galen Newman, Dayong Jason Wu, Yijun Zeng","doi":"10.1177/23998083251316064","DOIUrl":"10.1177/23998083251316064","url":null,"abstract":"<p><p>This study explores the integration of text-to-image generative AI, particularly Stable Diffusion, in conjunction with ControlNet and LoRA models in conceptual landscape design. Traditional methods in landscape design are often time-consuming and limited by the designer's individual creativity, also often lacking efficiency in the exploration of diverse design solutions. By leveraging AI tools, we demonstrate a workflow that efficiently generates detailed and visually coherent landscape designs, including natural parks, city plazas, and courtyard gardens. Through both qualitative and quantitative evaluations, our results indicate that fine-tuned models produce superior designs compared to non-fine-tuned models, maintaining spatial consistency, control over scale, and relevant landscape elements. This research advances the efficiency of conceptual design processes and underscores the potential of AI in enhancing creativity and innovation in landscape architecture.</p>","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12424439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145063770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1177/23998083241284824
Tazyeen Alam, Ankhi Banerjee
Urban populations are snowballing, increasing household (HH) water consumption. The growing housing density, the expanding infrastructure, and altered land use patterns place increasing pressure on the water supply and usage. This makes it harder for urban HHs to obtain clean water and worsens water scarcity, with infrastructural and environmental implications for highly populated metropolitan areas. This study aims to quantitatively evaluate the impact of urban morphology on household water use in a developing economy using a Structural Equation Model (SEM), specifically within the growing urban centres surrounding Kolkata in South Bengal. The primary hypothesis projects an increase in urban morphological indicators and HH characteristics that significantly affect water use. The findings reveal that increases in urban morphological indicators are associated with a 34.2% decrease in HH water use, highlighting the importance of urban planning strategies that emphasize compact and diverse urban forms. This work highlights new ways of building cities that consider morphological aspects and allow cities to expand in a way that conserves HH water while being resilient to rapid urban change.
{"title":"Investigating urban morphological drivers of household water use in developing economies: A structural equation model approach","authors":"Tazyeen Alam, Ankhi Banerjee","doi":"10.1177/23998083241284824","DOIUrl":"https://doi.org/10.1177/23998083241284824","url":null,"abstract":"Urban populations are snowballing, increasing household (HH) water consumption. The growing housing density, the expanding infrastructure, and altered land use patterns place increasing pressure on the water supply and usage. This makes it harder for urban HHs to obtain clean water and worsens water scarcity, with infrastructural and environmental implications for highly populated metropolitan areas. This study aims to quantitatively evaluate the impact of urban morphology on household water use in a developing economy using a Structural Equation Model (SEM), specifically within the growing urban centres surrounding Kolkata in South Bengal. The primary hypothesis projects an increase in urban morphological indicators and HH characteristics that significantly affect water use. The findings reveal that increases in urban morphological indicators are associated with a 34.2% decrease in HH water use, highlighting the importance of urban planning strategies that emphasize compact and diverse urban forms. This work highlights new ways of building cities that consider morphological aspects and allow cities to expand in a way that conserves HH water while being resilient to rapid urban change.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"6 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-14DOI: 10.1177/23998083241282092
Apostolos Lagarias, Demetris Stathakis
Despite its importance as a research issue, a widely accepted methodology of estimating land take resulting from urbanization has not yet been reached. Accurate geospatial datasets are currently available at a European and global level; however, different methods of quantifying urban land take could lead to diverse outputs, potentially resulting in underestimation. This can be alarming as encroaching urban sprawl is emerging as a major environmental challenge by destroying natural habitats, consuming productive agricultural land, and contributing to climate change by increasing energy demands. To address this knowledge gap, we propose an estimation of urban land take that combines cadastral parcels and building footprints. Land parcels can be considered as a suitable minimum mapping unit as they are directly related to the spatial level where economic decisions on land use conversion are made. The proposed geospatial method is compared to methods that depend on datasets of High Resolution Layer Imperviousness, Global Building Footprints (alone), Corine Land Cover, Urban Atlas, and Global Human Settlement Layer. The method is exemplified in case studies in Greece, specifically: (a) two islands of the South Aegean Region (Mykonos and Thera), that are heavily impacted by tourism development and sprawl and (b) a peri-urban zone (Thermaikos-Michaniona) within the metropolitan area of Thessaloniki, impacted by intense suburbanization. Results show that urban land consumes important shares of available land since the mid-20th century, this fact highlighting the dynamic encroachment of urban development. Calculation shows that other methods could underestimate urbanized areas by up to 80%–90%. In the discussion section, the advantages of shifting the focus from the pixel to the parcel are further justified, while explicit links to spatial planning policies for sprawl containment are drawn. Such policies could be informed by more realistic estimations of urban land take, in order to proceed with strategic and regulatory measures to support the ‘no net land take’ policy of Europe.
{"title":"Towards a more realistic estimation of urban land take by combining cadastral parcels and building footprints","authors":"Apostolos Lagarias, Demetris Stathakis","doi":"10.1177/23998083241282092","DOIUrl":"https://doi.org/10.1177/23998083241282092","url":null,"abstract":"Despite its importance as a research issue, a widely accepted methodology of estimating land take resulting from urbanization has not yet been reached. Accurate geospatial datasets are currently available at a European and global level; however, different methods of quantifying urban land take could lead to diverse outputs, potentially resulting in underestimation. This can be alarming as encroaching urban sprawl is emerging as a major environmental challenge by destroying natural habitats, consuming productive agricultural land, and contributing to climate change by increasing energy demands. To address this knowledge gap, we propose an estimation of urban land take that combines cadastral parcels and building footprints. Land parcels can be considered as a suitable minimum mapping unit as they are directly related to the spatial level where economic decisions on land use conversion are made. The proposed geospatial method is compared to methods that depend on datasets of High Resolution Layer Imperviousness, Global Building Footprints (alone), Corine Land Cover, Urban Atlas, and Global Human Settlement Layer. The method is exemplified in case studies in Greece, specifically: (a) two islands of the South Aegean Region (Mykonos and Thera), that are heavily impacted by tourism development and sprawl and (b) a peri-urban zone (Thermaikos-Michaniona) within the metropolitan area of Thessaloniki, impacted by intense suburbanization. Results show that urban land consumes important shares of available land since the mid-20th century, this fact highlighting the dynamic encroachment of urban development. Calculation shows that other methods could underestimate urbanized areas by up to 80%–90%. In the discussion section, the advantages of shifting the focus from the pixel to the parcel are further justified, while explicit links to spatial planning policies for sprawl containment are drawn. Such policies could be informed by more realistic estimations of urban land take, in order to proceed with strategic and regulatory measures to support the ‘no net land take’ policy of Europe.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"47 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-10DOI: 10.1177/23998083241280746
Nicola Colaninno, Rounaq Basu, Maryam Hosseini, Abdulaziz Alhassan, Liu Liu, Andres Sevtsuk
Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and risk in urban areas by integrating the Universal Thermal Climate Index (UTCI) as the hazard and pedestrian trips to critical destinations as exposure. We considered temporal variation, in both hazard and exposure, by examining different time periods during the day—morning peak, midday, and evening peak. In addition to hazard and exposure, we also considered vulnerability by focusing on young children and older adults. We contribute to improving the spatial resolution of heat risk assessment by analyzing the hazard for pedestrian trips between home locations and five critical destinations—bus stops, rail stations, parks, schools, and commercial amenities—at the address-point level and using a pedestrian network comprising sidewalks and crosswalks. Our framework helps identify sidewalks with high heat exposure levels as well as home locations with high cumulative heat risk, accounting for walking trips to critical destinations along feasible routes. We demonstrated the effectiveness of this framework by applying it to a 36-square-kilometer area of central Los Angeles, CA. Our findings offer valuable information to urban planners and policy-makers, supporting evidence-based prioritization of intervention sites, climate adaptation strategies, and policy decisions essential for climate-proof planning. By implementing targeted interventions in areas where heat hazard is expected to affect the most vulnerable pedestrians, planners can create heat-resilient, pedestrian-friendly environments while prioritizing the health and well-being of vulnerable groups. This study contributes to the growing knowledge of robust risk assessment methodologies for climate-proof planning, specifically with regard to addressing outdoor heat-related risks during extreme heat events.
{"title":"A sidewalk-level urban heat risk assessment framework using pedestrian mobility and urban microclimate modeling","authors":"Nicola Colaninno, Rounaq Basu, Maryam Hosseini, Abdulaziz Alhassan, Liu Liu, Andres Sevtsuk","doi":"10.1177/23998083241280746","DOIUrl":"https://doi.org/10.1177/23998083241280746","url":null,"abstract":"Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and risk in urban areas by integrating the Universal Thermal Climate Index (UTCI) as the hazard and pedestrian trips to critical destinations as exposure. We considered temporal variation, in both hazard and exposure, by examining different time periods during the day—morning peak, midday, and evening peak. In addition to hazard and exposure, we also considered vulnerability by focusing on young children and older adults. We contribute to improving the spatial resolution of heat risk assessment by analyzing the hazard for pedestrian trips between home locations and five critical destinations—bus stops, rail stations, parks, schools, and commercial amenities—at the address-point level and using a pedestrian network comprising sidewalks and crosswalks. Our framework helps identify sidewalks with high heat exposure levels as well as home locations with high cumulative heat risk, accounting for walking trips to critical destinations along feasible routes. We demonstrated the effectiveness of this framework by applying it to a 36-square-kilometer area of central Los Angeles, CA. Our findings offer valuable information to urban planners and policy-makers, supporting evidence-based prioritization of intervention sites, climate adaptation strategies, and policy decisions essential for climate-proof planning. By implementing targeted interventions in areas where heat hazard is expected to affect the most vulnerable pedestrians, planners can create heat-resilient, pedestrian-friendly environments while prioritizing the health and well-being of vulnerable groups. This study contributes to the growing knowledge of robust risk assessment methodologies for climate-proof planning, specifically with regard to addressing outdoor heat-related risks during extreme heat events.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"17 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1177/23998083241279992
Xinghan Chen, Xiangwen Ding, Yu Ye
Sense of place, as an intangible perception, is widely recognized as an urban identity and of great value in both cross-cultural studies and contemporary urbanism. Building façade material can effectively capture sense of place due to its combination of physical and social attributes. Nevertheless, there are no widely implementable and high-resolution approaches to identify façade materials on a large scale. As a response, this study proposes a method using street view images (SVIs) and a set of deep Convolutional Neural Networks (CNNs) to identify building façade materials. Specifically, a large cross-cultural training set was built to promote generalizability. Buildings within SVIs were divided into high-resolution rectangular images and classified using a well-trained Residual Network-50 (ResNet-50) model. Sense of place and its spatial patterns were then depicted by measuring façade material and analytical indicators including diversity and continuity. Eight cities worldwide with distinctive urban identities were examined. The findings revealed that compared to Asian cities, New York City, Chicago, and London are similar, while Paris and Tokyo are more distinctive. While challenges persist in comprehensively measuring the sense of place, the analysis of façade materials offers an insightful indicator that can assist in enhancing urban identity for contemporary urbanism. This study not only promotes the fine development of urban science through the empowerment of intelligent algorithms but also introduces a new perspective on exploring unmeasurable qualities based on the objective physical environment.
{"title":"Mapping sense of place as a measurable urban identity: Using street view images and machine learning to identify building façade materials","authors":"Xinghan Chen, Xiangwen Ding, Yu Ye","doi":"10.1177/23998083241279992","DOIUrl":"https://doi.org/10.1177/23998083241279992","url":null,"abstract":"Sense of place, as an intangible perception, is widely recognized as an urban identity and of great value in both cross-cultural studies and contemporary urbanism. Building façade material can effectively capture sense of place due to its combination of physical and social attributes. Nevertheless, there are no widely implementable and high-resolution approaches to identify façade materials on a large scale. As a response, this study proposes a method using street view images (SVIs) and a set of deep Convolutional Neural Networks (CNNs) to identify building façade materials. Specifically, a large cross-cultural training set was built to promote generalizability. Buildings within SVIs were divided into high-resolution rectangular images and classified using a well-trained Residual Network-50 (ResNet-50) model. Sense of place and its spatial patterns were then depicted by measuring façade material and analytical indicators including diversity and continuity. Eight cities worldwide with distinctive urban identities were examined. The findings revealed that compared to Asian cities, New York City, Chicago, and London are similar, while Paris and Tokyo are more distinctive. While challenges persist in comprehensively measuring the sense of place, the analysis of façade materials offers an insightful indicator that can assist in enhancing urban identity for contemporary urbanism. This study not only promotes the fine development of urban science through the empowerment of intelligent algorithms but also introduces a new perspective on exploring unmeasurable qualities based on the objective physical environment.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"59 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-30DOI: 10.1177/23998083241279601
Li Wan, Ying Jin, Marcial Echenique, Michael Batty, Michael Wegener
City digital twins (CDTs), as digital replica of urban systems and development processes, have been heralded as the next-generation technology for urban planning and management. Arguably, the concept of CDTs is not new. Prior to CDTs, applied urban modelling has been playing a pivot role in supporting city and infrastructure planning since the 1960s. Examining CDTs in relation to conventional urban models can thus offer valuable insights into their nature, potential, and challenges. Such a comparative, reflective exercise, however, remains rare. This commentary aims to share insights and reflections from a dedicated applied urban modelling (AUM) community. It is argued that to substantiate the power of CDTs, a theory-driven modelling strategy is essential for both practical policy analysis and knowledge discovery. Modellers must think beyond the technical perspective and exploring novel use of CDTs beyond optimisation. A blind pursuit for data without building on and expanding existing domain knowledge remains an existential risk for CDTs.
{"title":"From urban modelling to city digital twins – Reflections from the applied urban modelling (AUM) symposia","authors":"Li Wan, Ying Jin, Marcial Echenique, Michael Batty, Michael Wegener","doi":"10.1177/23998083241279601","DOIUrl":"https://doi.org/10.1177/23998083241279601","url":null,"abstract":"City digital twins (CDTs), as digital replica of urban systems and development processes, have been heralded as the next-generation technology for urban planning and management. Arguably, the concept of CDTs is not new. Prior to CDTs, applied urban modelling has been playing a pivot role in supporting city and infrastructure planning since the 1960s. Examining CDTs in relation to conventional urban models can thus offer valuable insights into their nature, potential, and challenges. Such a comparative, reflective exercise, however, remains rare. This commentary aims to share insights and reflections from a dedicated applied urban modelling (AUM) community. It is argued that to substantiate the power of CDTs, a theory-driven modelling strategy is essential for both practical policy analysis and knowledge discovery. Modellers must think beyond the technical perspective and exploring novel use of CDTs beyond optimisation. A blind pursuit for data without building on and expanding existing domain knowledge remains an existential risk for CDTs.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"12 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-30DOI: 10.1177/23998083241281134
Arnisson Andre C Ortega
Filipina migrant workers have played an important role in various economies and societal sectors across the globe, including providing vital support to healthcare systems during the height of the COVID-19 pandemic. This graphics article visualizes their overseas global deployment, mapping their migration into countries that have at least 100 Filipina workers in 2019. The map illustrates sizable deployment of Filipinas to the Middle East and East and Southeast Asia, from 2015 to 2019. While labor migration to East and Southeast Asia has been traditionally female-dominated, the Middle East experienced a gendered shift, from a more male-dominated stock working in the oil industry to a more female workforce supporting the thriving service and commercial industries. Meanwhile, European countries have emerged as major destinations for Filipina workers, experiencing high rates of growth of Filipina deployment. These patterns can potentially inspire future research in understanding gendered shifts in labor migration and help guide policy on labor migration and support systems for Filipinas and their families left behind in the Philippines.
{"title":"Visualizing the global deployment of Filipina workers","authors":"Arnisson Andre C Ortega","doi":"10.1177/23998083241281134","DOIUrl":"https://doi.org/10.1177/23998083241281134","url":null,"abstract":"Filipina migrant workers have played an important role in various economies and societal sectors across the globe, including providing vital support to healthcare systems during the height of the COVID-19 pandemic. This graphics article visualizes their overseas global deployment, mapping their migration into countries that have at least 100 Filipina workers in 2019. The map illustrates sizable deployment of Filipinas to the Middle East and East and Southeast Asia, from 2015 to 2019. While labor migration to East and Southeast Asia has been traditionally female-dominated, the Middle East experienced a gendered shift, from a more male-dominated stock working in the oil industry to a more female workforce supporting the thriving service and commercial industries. Meanwhile, European countries have emerged as major destinations for Filipina workers, experiencing high rates of growth of Filipina deployment. These patterns can potentially inspire future research in understanding gendered shifts in labor migration and help guide policy on labor migration and support systems for Filipinas and their families left behind in the Philippines.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"23 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-30DOI: 10.1177/23998083241272096
Onur Tümtürk, Justyna Karakiewicz, Fjalar J de Haan
The importance of urban form as a key factor affecting future development and transformation patterns is well-recognised in urban morphology. However, despite the need for a diachronic approach to rigorously understand the form-change relationship, studies utilising longitudinal datasets remain scarce, and only a small fraction employs quantitative methodologies and morphometric approaches. This paper aims to quantitatively examine how the character of urban form elements and their spatial arrangements influence patterns of physical change, and to assess the performance of geometric and configurational urban form measures of plots, buildings, and streets in explaining physical change patterns over time. We hypothesise that configurational measures, being more sensitive to the relations between urban form elements, can better explain physical changes compared to conventional geometric measures predominantly adopted thus far. To test this hypothesis, we present a diachronic and quantitative methodology to measure urban form conditions and the patterns of physical change in Midtown Manhattan through four time frames (1890, 1920, 1956, and 2021), using a longitudinal geospatial database generated from historical cartographic resources and recent digital datasets. The association between urban form and physical change is demonstrated through statistical analysis. The findings prove that while the prevailing hypotheses emphasising the effect of geometric measures, such as size and shape, are often off the mark, configurational and access-based measures of plots and streets can accurately describe the dynamic relationships between form and change. The character of urban form patterns and structures measured by configurational variables is more reliable than the individual and geometric quality of urban form elements in explaining the dynamics of physical change and persistence. Our empirical findings add to the rapidly expanding fields of urban morphometrics and provide data-informed insights to improve the resilience and adaptive capacity of urban spaces.
{"title":"The impact of urban form on physical change: A quantitative and diachronic analysis of urban form evolution in Midtown Manhattan","authors":"Onur Tümtürk, Justyna Karakiewicz, Fjalar J de Haan","doi":"10.1177/23998083241272096","DOIUrl":"https://doi.org/10.1177/23998083241272096","url":null,"abstract":"The importance of urban form as a key factor affecting future development and transformation patterns is well-recognised in urban morphology. However, despite the need for a diachronic approach to rigorously understand the form-change relationship, studies utilising longitudinal datasets remain scarce, and only a small fraction employs quantitative methodologies and morphometric approaches. This paper aims to quantitatively examine how the character of urban form elements and their spatial arrangements influence patterns of physical change, and to assess the performance of geometric and configurational urban form measures of plots, buildings, and streets in explaining physical change patterns over time. We hypothesise that configurational measures, being more sensitive to the relations between urban form elements, can better explain physical changes compared to conventional geometric measures predominantly adopted thus far. To test this hypothesis, we present a diachronic and quantitative methodology to measure urban form conditions and the patterns of physical change in Midtown Manhattan through four time frames (1890, 1920, 1956, and 2021), using a longitudinal geospatial database generated from historical cartographic resources and recent digital datasets. The association between urban form and physical change is demonstrated through statistical analysis. The findings prove that while the prevailing hypotheses emphasising the effect of geometric measures, such as size and shape, are often off the mark, configurational and access-based measures of plots and streets can accurately describe the dynamic relationships between form and change. The character of urban form patterns and structures measured by configurational variables is more reliable than the individual and geometric quality of urban form elements in explaining the dynamics of physical change and persistence. Our empirical findings add to the rapidly expanding fields of urban morphometrics and provide data-informed insights to improve the resilience and adaptive capacity of urban spaces.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"441 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号