Precise distinction of mixed functions on urban land is essential for urban studies and planning, while existing methods are limited by high sampling bias, low observation frequency, and lack of semantic information in common data sources. In this paper, we introduce a new proxy for human behavior, the telecom traffic data as a remedy to the above limitations, and present an analytical framework which utilizes anonymized and aggregated telecom traffic data to infer mixed urban functions at spatiotemporal granularities as fine as buildings and hours. A time-series decomposition method is designed to map the mixture of urban functions, which is further refined by a hierarchical agglomerative clustering method taking urban textures as an additional source of information. In a case study in Shenzhen, China, we find the function of urban buildings can be decomposed into the mixture of three basic functions, namely dwelling, work, and recreation. We further find that the introduction of urban texture information helps identify particular forms of functional combination, which indicate special-function buildings such as urban villages and roadside shops. This study implies ways to improve urban management through methodological contributions in mixed urban function identification alongside the introduction of the telecom traffic, a kind of “high-frequency” urban data, and also helps inspire a rethinking of the form/function dichotomy in the era of “High-frequent” cities.
{"title":"Inferring “high-frequent” mixed urban functions from telecom traffic","authors":"Jintong Tang, Ximeng Cheng, Aihan Liu, Qian Huang, Yinsheng Zhou, Zhou Huang, Yu Liu, Liyan Xu","doi":"10.1177/23998083231221867","DOIUrl":"https://doi.org/10.1177/23998083231221867","url":null,"abstract":"Precise distinction of mixed functions on urban land is essential for urban studies and planning, while existing methods are limited by high sampling bias, low observation frequency, and lack of semantic information in common data sources. In this paper, we introduce a new proxy for human behavior, the telecom traffic data as a remedy to the above limitations, and present an analytical framework which utilizes anonymized and aggregated telecom traffic data to infer mixed urban functions at spatiotemporal granularities as fine as buildings and hours. A time-series decomposition method is designed to map the mixture of urban functions, which is further refined by a hierarchical agglomerative clustering method taking urban textures as an additional source of information. In a case study in Shenzhen, China, we find the function of urban buildings can be decomposed into the mixture of three basic functions, namely dwelling, work, and recreation. We further find that the introduction of urban texture information helps identify particular forms of functional combination, which indicate special-function buildings such as urban villages and roadside shops. This study implies ways to improve urban management through methodological contributions in mixed urban function identification alongside the introduction of the telecom traffic, a kind of “high-frequency” urban data, and also helps inspire a rethinking of the form/function dichotomy in the era of “High-frequent” cities.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"106 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138979529","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 : 2023-12-08DOI: 10.1177/23998083231219364
Yubo Liu, Kai Hu, Qiaoming Deng
This research proposes a design system that combines a case-based learning algorithm with a rule-based optimization algorithm to automatically generate and revise urban form prototypes based on historical cases and user requirements. The system aims to address the challenges of existing generative methods for urban forms, such as the lack of flexibility and organicity of rule-based methods and the insufficient manipulability and interpretability of the newest GAN-integrated case-based methods. It can help designers generate multiple solutions with specific indicators in the conceptual stage and has the potential to facilitate citizen participation in urban planning and design. This research demonstrates the feasibility and effectiveness of the system through a case study in Shenzhen. The research further extends the discussion about the application of the proposed system and the alternative evolution approach for the next generation of automatic design methods.
{"title":"Evolvable case-based design: An artificial intelligence system for urban form generation with specific indicators","authors":"Yubo Liu, Kai Hu, Qiaoming Deng","doi":"10.1177/23998083231219364","DOIUrl":"https://doi.org/10.1177/23998083231219364","url":null,"abstract":"This research proposes a design system that combines a case-based learning algorithm with a rule-based optimization algorithm to automatically generate and revise urban form prototypes based on historical cases and user requirements. The system aims to address the challenges of existing generative methods for urban forms, such as the lack of flexibility and organicity of rule-based methods and the insufficient manipulability and interpretability of the newest GAN-integrated case-based methods. It can help designers generate multiple solutions with specific indicators in the conceptual stage and has the potential to facilitate citizen participation in urban planning and design. This research demonstrates the feasibility and effectiveness of the system through a case study in Shenzhen. The research further extends the discussion about the application of the proposed system and the alternative evolution approach for the next generation of automatic design methods.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"11 3","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138590286","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 : 2023-12-07DOI: 10.1177/23998083231215822
Piyushimita (Vonu) Thakuriah, Christina Boididou, Jinhyun Hong
This study analyzed physical distancing in people’s daily lives and its association with travel behavior and the use of transportation modes before the COVID-19 outbreak. We used data from photographic images acquired automatically by lifelogging devices every 5 seconds, on average, from 170 participants of a 2-day wearable camera study, in order to identify their physical distancing status throughout the day. Using deep-learning computer vision algorithms, we developed three measures which provided a near-continuous quantification of the proportion of time spent without anyone else within a distance of approximately 13 meters, as well as the proportion of time spent without others within approximately 2 meters. These measures are then used as outcomes in beta regression and multinomial logit models to explore the association between the participant’s physical distancing and travel behavior and transportation choices. The multidisciplinary research approach to understand these associations accounted for a number of social, economic, and cultural factors that potentially influenced their physical isolation levels. We found that participants spend a significant amount of time physically separated from others, without anyone else within 2 meters. The use of public transportation, automobiles, active travel, and an increase in trip frequency, including trips to transportation facilities, reduced the extent of physical distancing, with public transportation having the most significant impact. Higher incomes, strong social networks, and a sense of belonging to the community reduced the tendency for physical distancing. In contrast, factors such as age, obesity, dog ownership, intensive use of the Internet, and being knowledgeable about climate change issues increased the likelihood of physical distancing. The paper addresses a crucial gap in our understanding of how these factors intersect to create the dynamics of physical distancing in non-emergency situations and highlights their planning and operational implications while showcasing the use of unique person-based physical distancing measures derived from autonomously collected image data.
{"title":"Physical distancing and its association with travel behavior in daily pre-pandemic urban life: An analysis utilizing lifelogging images and composite survey and mobility data","authors":"Piyushimita (Vonu) Thakuriah, Christina Boididou, Jinhyun Hong","doi":"10.1177/23998083231215822","DOIUrl":"https://doi.org/10.1177/23998083231215822","url":null,"abstract":"This study analyzed physical distancing in people’s daily lives and its association with travel behavior and the use of transportation modes before the COVID-19 outbreak. We used data from photographic images acquired automatically by lifelogging devices every 5 seconds, on average, from 170 participants of a 2-day wearable camera study, in order to identify their physical distancing status throughout the day. Using deep-learning computer vision algorithms, we developed three measures which provided a near-continuous quantification of the proportion of time spent without anyone else within a distance of approximately 13 meters, as well as the proportion of time spent without others within approximately 2 meters. These measures are then used as outcomes in beta regression and multinomial logit models to explore the association between the participant’s physical distancing and travel behavior and transportation choices. The multidisciplinary research approach to understand these associations accounted for a number of social, economic, and cultural factors that potentially influenced their physical isolation levels. We found that participants spend a significant amount of time physically separated from others, without anyone else within 2 meters. The use of public transportation, automobiles, active travel, and an increase in trip frequency, including trips to transportation facilities, reduced the extent of physical distancing, with public transportation having the most significant impact. Higher incomes, strong social networks, and a sense of belonging to the community reduced the tendency for physical distancing. In contrast, factors such as age, obesity, dog ownership, intensive use of the Internet, and being knowledgeable about climate change issues increased the likelihood of physical distancing. The paper addresses a crucial gap in our understanding of how these factors intersect to create the dynamics of physical distancing in non-emergency situations and highlights their planning and operational implications while showcasing the use of unique person-based physical distancing measures derived from autonomously collected image data.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"56 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138592904","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 : 2023-12-05DOI: 10.1177/23998083231217606
Stefano De Sabbata, Katy Bennett, Zoe Gardner
Events are the driving force behind social media, whether we try to create them or keep up with them. A wide range of studies has focused on how content from social media can be used to detect, model and predict events and identify key topics of discussion. At the same time, very limited attention has been given so far to the quantitative study of the everyday, which has fascinated qualitative human geography research in the past few decades. That is partly due to the lack of a formal definition of what constitutes the everyday. In this paper, we aim to advance our understanding of the everyday, not by reducing it to any kind of definition but by bringing it into view through a quantitative analysis. We hypothesise that the by-products of current methods focused on event detection might be used to quantitatively explore everyday geographies as represented through Twitter data. We consider the use of both statistical approaches based on term frequency and state-of-the-art large language models, and we conduct a case study on content posted on Twitter and geolocated in the city of Leicester. Our paper makes two key advances for research concerned with the everyday and the analysis of geographic information. First, we illustrate how large language models combined with spatial analysis and visualisation can foster the study of everyday geographies, providing an insight into the still elusive concept of the everyday, representing what other approaches to the everyday have struggled to qualify. Secondly, we showcase the potential held by large language models and visual analytics in democratising sophisticated natural language processing and thus providing new tools for research in human geography.
{"title":"Towards a study of everyday geographic information: Bringing the everyday into view","authors":"Stefano De Sabbata, Katy Bennett, Zoe Gardner","doi":"10.1177/23998083231217606","DOIUrl":"https://doi.org/10.1177/23998083231217606","url":null,"abstract":"Events are the driving force behind social media, whether we try to create them or keep up with them. A wide range of studies has focused on how content from social media can be used to detect, model and predict events and identify key topics of discussion. At the same time, very limited attention has been given so far to the quantitative study of the everyday, which has fascinated qualitative human geography research in the past few decades. That is partly due to the lack of a formal definition of what constitutes the everyday. In this paper, we aim to advance our understanding of the everyday, not by reducing it to any kind of definition but by bringing it into view through a quantitative analysis. We hypothesise that the by-products of current methods focused on event detection might be used to quantitatively explore everyday geographies as represented through Twitter data. We consider the use of both statistical approaches based on term frequency and state-of-the-art large language models, and we conduct a case study on content posted on Twitter and geolocated in the city of Leicester. Our paper makes two key advances for research concerned with the everyday and the analysis of geographic information. First, we illustrate how large language models combined with spatial analysis and visualisation can foster the study of everyday geographies, providing an insight into the still elusive concept of the everyday, representing what other approaches to the everyday have struggled to qualify. Secondly, we showcase the potential held by large language models and visual analytics in democratising sophisticated natural language processing and thus providing new tools for research in human geography.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"126 50","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138599015","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 : 2023-12-05DOI: 10.1177/23998083231219048
Miguel G. Silva, Sara C. Madeira, Rui Henriques
Mobile phones share location records, offering the opportunity to monitor and understand emerging population dynamics in urban centers. With the aim of supporting urban planning, this study introduces a scalable methodology grounded on extracting and organizing spatiotemporal statistics from decomposed population density data. The proposed methodology serves three major purposes: (i) assess the predictability of spatiotemporal citizen density patterns; (ii) detect emerging spatiotemporal trends in population density; and (iii) uncover multi-level seasonality patterns with guarantees of actionability. Additionally, it makes available an open-access tool for deploying the proposed methodology and analyzing mobile phone network data with easy-to-use spatiotemporal visualization and navigation facilities. The results obtained from real-world, large-scale mobile data in Lisbon, Portugal, demonstrate the effectiveness and validity of the proposed methodology in extracting actionable statistics in linear time to guide both tactic and strategic urban planning.
{"title":"Actionable descriptors of spatiotemporal urban dynamics from large-scale mobile data: A case study in Lisbon city","authors":"Miguel G. Silva, Sara C. Madeira, Rui Henriques","doi":"10.1177/23998083231219048","DOIUrl":"https://doi.org/10.1177/23998083231219048","url":null,"abstract":"Mobile phones share location records, offering the opportunity to monitor and understand emerging population dynamics in urban centers. With the aim of supporting urban planning, this study introduces a scalable methodology grounded on extracting and organizing spatiotemporal statistics from decomposed population density data. The proposed methodology serves three major purposes: (i) assess the predictability of spatiotemporal citizen density patterns; (ii) detect emerging spatiotemporal trends in population density; and (iii) uncover multi-level seasonality patterns with guarantees of actionability. Additionally, it makes available an open-access tool for deploying the proposed methodology and analyzing mobile phone network data with easy-to-use spatiotemporal visualization and navigation facilities. The results obtained from real-world, large-scale mobile data in Lisbon, Portugal, demonstrate the effectiveness and validity of the proposed methodology in extracting actionable statistics in linear time to guide both tactic and strategic urban planning.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"129 27","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138599002","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 : 2023-12-04DOI: 10.1177/23998083231218779
L. Saganeiti, Lorena Fiorini, F. Zullo, B. Murgante
The 2022 United Nations Climate Change Conference (COP27) reaffirmed the most urgent need to build actions to accelerate the restoration of policies to arrest and reverse the loss of natural ecosystems by 2030 and move towards full ecosystem recovery by 2050. Land take is a significant source of emissions and contributes to global warming and biodiversity loss in natural ecosystems. Consequently, it is crucial to act on it by investigating the phenomenon quantitatively and formally, thus contributing to the goal of zero net land take. In recent years, land take worldwide has become massive, leading in some cases to forming compact, high-density urban settlements. In other cases, it has led to dispersed, low-density urban settlements. The basic assumption underlying this research is that a compact context is more sustainable (environmentally, economically, and socially) than a dispersed urban one. Consequently, this research aims to investigate the evolution of land take from the point of view of the pattern of urban settlements and their dispersion over the Italian territory. The spatial configuration of the Italian settlement pattern at the regional and provincial level was analyzed through a Spatio-temporal analysis of the global Moran index and other quantitative variables. The results provide, for each territory, a reading of the main expansion dynamics that occurred from the ‘50s to nowadays: compact city, urban sprawl, or urban sprinkling.
{"title":"Urban dispersion indicator to assess the Italian settlement pattern","authors":"L. Saganeiti, Lorena Fiorini, F. Zullo, B. Murgante","doi":"10.1177/23998083231218779","DOIUrl":"https://doi.org/10.1177/23998083231218779","url":null,"abstract":"The 2022 United Nations Climate Change Conference (COP27) reaffirmed the most urgent need to build actions to accelerate the restoration of policies to arrest and reverse the loss of natural ecosystems by 2030 and move towards full ecosystem recovery by 2050. Land take is a significant source of emissions and contributes to global warming and biodiversity loss in natural ecosystems. Consequently, it is crucial to act on it by investigating the phenomenon quantitatively and formally, thus contributing to the goal of zero net land take. In recent years, land take worldwide has become massive, leading in some cases to forming compact, high-density urban settlements. In other cases, it has led to dispersed, low-density urban settlements. The basic assumption underlying this research is that a compact context is more sustainable (environmentally, economically, and socially) than a dispersed urban one. Consequently, this research aims to investigate the evolution of land take from the point of view of the pattern of urban settlements and their dispersion over the Italian territory. The spatial configuration of the Italian settlement pattern at the regional and provincial level was analyzed through a Spatio-temporal analysis of the global Moran index and other quantitative variables. The results provide, for each territory, a reading of the main expansion dynamics that occurred from the ‘50s to nowadays: compact city, urban sprawl, or urban sprinkling.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"20 24","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138603279","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 : 2023-12-04DOI: 10.1177/23998083231219322
Minghao Liu, Zhonghua Gou
Due to COVID-19, the urban lockdown has caused a significant impact on the mental health of residents. However, limited research investigates the role of neighborhood factors on residents’ mental health during and after the lockdown. This study examines Wuhan, the first city to experience the COVID-19 outbreak, employing multiple linear regression and XGBoost algorithms to analyze the emotional status and distribution of Wuhan residents. The goal of this study is to identify the moderating effect of the neighborhood environment scale on emotional positivity and the marginal effect of the neighborhood environment on residents’ emotions. The results of the study indicate that specific neighborhood environmental characteristics have varying effects on residents’ positive emotions, both before and after the COVID-19 lockdown. The green space ratio, attraction density, waterfront space density, and service facility density all positively affected mood within different distance ranges. Shopping facilities, on the other hand, had mainly positive effects during the open period, with negative effects during the closed period. Furthermore, this study determined scale thresholds where neighborhood environments had a positive effect on mood. For instance, attractions and waterfront areas improved the mood of residents in residential areas, up to at least 3 km away. Medical facilities had a positive effect on residents’ mood beyond 2.2 km. This study highlights crucial implications for planning and managing neighborhoods to promote resilience during future public health crises.
{"title":"Examining the impact of neighborhood environment factors on residents’ emotions during COVID-19 lockdown and reopening: A Wuhan study on mediation and moderation","authors":"Minghao Liu, Zhonghua Gou","doi":"10.1177/23998083231219322","DOIUrl":"https://doi.org/10.1177/23998083231219322","url":null,"abstract":"Due to COVID-19, the urban lockdown has caused a significant impact on the mental health of residents. However, limited research investigates the role of neighborhood factors on residents’ mental health during and after the lockdown. This study examines Wuhan, the first city to experience the COVID-19 outbreak, employing multiple linear regression and XGBoost algorithms to analyze the emotional status and distribution of Wuhan residents. The goal of this study is to identify the moderating effect of the neighborhood environment scale on emotional positivity and the marginal effect of the neighborhood environment on residents’ emotions. The results of the study indicate that specific neighborhood environmental characteristics have varying effects on residents’ positive emotions, both before and after the COVID-19 lockdown. The green space ratio, attraction density, waterfront space density, and service facility density all positively affected mood within different distance ranges. Shopping facilities, on the other hand, had mainly positive effects during the open period, with negative effects during the closed period. Furthermore, this study determined scale thresholds where neighborhood environments had a positive effect on mood. For instance, attractions and waterfront areas improved the mood of residents in residential areas, up to at least 3 km away. Medical facilities had a positive effect on residents’ mood beyond 2.2 km. This study highlights crucial implications for planning and managing neighborhoods to promote resilience during future public health crises.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"61 14","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138604871","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 : 2023-11-30DOI: 10.1177/23998083231217784
Raz Weiner, Filipe Mello Rose, Batel Yossef Ravid, Jörg Rainer Noennig, Meirav Aharon-Gutman
Despite planning support systems (PSS) becoming increasingly useful for citizen participation processes, the effects of such systems’ material and spatial setup on citizen participation processes still need to be studied. PSS have long been equated to software- and data-based technologies, and only little attention has been put on place-bound PSS that prescribe onsite face-to-face collaboration. As closing the ‘implementation gap’ requires extensive conceptualisation, description, and critical analysis of different ideal types, workings, and use cases of PSS, this study researches this understudied place-bound type of PSS. More precisely, this study uses empirical material from Haifa’s 3 S Lab to contribute to closing the implementation gap by identifying place-bound PSS – an under-studied type of PSS – as useful for deliberative decision-making – an overlooked implementation context. This research advances the conceptualisation of PSS by discussing place-bound PSS and their hypothesised utility, practical setup, and empirically tested benefits for deliberative citizen participation. We find that the benefits of place-bound PSS for planning lie in deliberative affordances that ease the communication and comprehension deficiencies that often plague deliberative citizen participation processes. As place-bound PSS, the 3 S Lab provides an immersive shared space that improves communication, while its interactive visualisation techniques afford improved comprehension of complex urban issues.
尽管规划支持系统（PSS）对公民参与过程的作用越来越大，但此类系统的物质和空间设置对公民参与过程的影响仍有待研究。长期以来，规划支持系统一直等同于以软件和数据为基础的技术，人们很少关注那些需要现场面对面合作的、与地点相关的规划支持系统。要缩小 "实施差距"，需要对 PSS 的不同理想类型、工作原理和使用案例进行广泛的概念化、描述和批判性分析，因此本研究对这一未被充分研究的地点绑定型 PSS 进行了研究。更确切地说，本研究利用海法 3 S 实验室的经验材料，通过确定场所约束型 PSS（一种研究不足的 PSS 类型）对审议决策（一种被忽视的实施环境）的有用性，为缩小实施差距做出贡献。本研究通过讨论与地点相关的个人和社会服务及其假设效用、实际设置以及经过实证检验的公民参与议事的益处，推进了个人和社会服务的概念化。我们发现，与地点相关的计划支助服务对规划的益处在于其审议能力，它能缓解经常困扰公民审议参与过程的沟通和理解缺陷。3 S 实验室作为与地点相关的 PSS，提供了一个身临其境的共享空间，改善了交流，而其交互式可视化技术则提高了对复杂城市问题的理解能力。
{"title":"Place-bound planning support systems for deliberation: Affording better communication and comprehension","authors":"Raz Weiner, Filipe Mello Rose, Batel Yossef Ravid, Jörg Rainer Noennig, Meirav Aharon-Gutman","doi":"10.1177/23998083231217784","DOIUrl":"https://doi.org/10.1177/23998083231217784","url":null,"abstract":"Despite planning support systems (PSS) becoming increasingly useful for citizen participation processes, the effects of such systems’ material and spatial setup on citizen participation processes still need to be studied. PSS have long been equated to software- and data-based technologies, and only little attention has been put on place-bound PSS that prescribe onsite face-to-face collaboration. As closing the ‘implementation gap’ requires extensive conceptualisation, description, and critical analysis of different ideal types, workings, and use cases of PSS, this study researches this understudied place-bound type of PSS. More precisely, this study uses empirical material from Haifa’s 3 S Lab to contribute to closing the implementation gap by identifying place-bound PSS – an under-studied type of PSS – as useful for deliberative decision-making – an overlooked implementation context. This research advances the conceptualisation of PSS by discussing place-bound PSS and their hypothesised utility, practical setup, and empirically tested benefits for deliberative citizen participation. We find that the benefits of place-bound PSS for planning lie in deliberative affordances that ease the communication and comprehension deficiencies that often plague deliberative citizen participation processes. As place-bound PSS, the 3 S Lab provides an immersive shared space that improves communication, while its interactive visualisation techniques afford improved comprehension of complex urban issues.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"864 ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139204885","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 : 2023-11-28DOI: 10.1177/23998083231217349
Y. Kamata, Jung Eun Kang
This study aimed to analyze the improvement in outdoor thermal environment by greening of persistently vacant housing and open areas in a densely built old downtown area of Busan Metropolitan City using ENVI-met. Simulation was performed for a summer day by constructing four scenarios for four areas considering the building density and slope direction. The results indicate that compared to the current scenario, the concrete scenario had the worst thermal environment, where the average temperature, mean radiant temperature (MRT), and physiological equivalent temperature (PET) increased by 0.04°C, 1.49°C, and 0.51°C, respectively. In contrast, the tree scenario exhibited the most significant improvement. The average temperature, MRT, and PET decreased by 0.03°C, 1.66°C, and 0.65°C, respectively. Moreover, the removal of vacant houses in dense residential areas improved ventilation, and PET decreased by approximately 8°C locally. Planting trees higher than the demolished vacant houses mitigated the thermal environment considerably. The effect of greening was the strongest in the residential areas located on the south-facing slope with the worst thermal environment. This study provides essential data for implementing greening as a smart reduction strategy in the sustainable management of vacant houses.
{"title":"Effect of greening vacant houses on improvement in thermal environment using ENVI-met simulation: A case study on Busan metropolitan city","authors":"Y. Kamata, Jung Eun Kang","doi":"10.1177/23998083231217349","DOIUrl":"https://doi.org/10.1177/23998083231217349","url":null,"abstract":"This study aimed to analyze the improvement in outdoor thermal environment by greening of persistently vacant housing and open areas in a densely built old downtown area of Busan Metropolitan City using ENVI-met. Simulation was performed for a summer day by constructing four scenarios for four areas considering the building density and slope direction. The results indicate that compared to the current scenario, the concrete scenario had the worst thermal environment, where the average temperature, mean radiant temperature (MRT), and physiological equivalent temperature (PET) increased by 0.04°C, 1.49°C, and 0.51°C, respectively. In contrast, the tree scenario exhibited the most significant improvement. The average temperature, MRT, and PET decreased by 0.03°C, 1.66°C, and 0.65°C, respectively. Moreover, the removal of vacant houses in dense residential areas improved ventilation, and PET decreased by approximately 8°C locally. Planting trees higher than the demolished vacant houses mitigated the thermal environment considerably. The effect of greening was the strongest in the residential areas located on the south-facing slope with the worst thermal environment. This study provides essential data for implementing greening as a smart reduction strategy in the sustainable management of vacant houses.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"43 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139219524","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 : 2023-11-28DOI: 10.1177/23998083231218774
Flavia Lopes, Lucas Figueiredo, Jorge Gil, Edja Trigueiro
Addressing housing deficits and inequalities remains a key challenge for cities in promoting more sustainable urban development. In response to these challenges, governments around the world, particularly in the Global South, have made substantial investments in housing policies for middle- and low-income individuals. Nevertheless, while these initiatives increase housing provision, they often face criticism for not adequately considering the location of new residences. This oversight has far-reaching effects on the accessibility to essential facilities, which play a pivotal role in determining spatial advantages and disadvantages, and consequently, in the degree of inclusion of individuals in both the city and society. Addressing this critical role of accessibility, this paper introduces a methodology for assessing the potential impact of housing policies on the lives of their beneficiaries, by quantifying changes in cumulative accessibility levels between individuals' former house locations and the location of the housing projects into which they moved. Accessibility is calculated for three distinct transport modes: walking, cycling, and public transport, using unimodal and multimodal urban network models. A case study was conducted in Natal, northeastern Brazil, on the implementation of the Minha Casa, Minha Vida (My House, My Life, MCMV) housing policy, initiated in 2009 and still active today. The results of the study revealed a significant decrease in accessibility across all transportation modes when individuals moved to the new housing estates. The decline was particularly pronounced among individuals with lower incomes, potentially raising their regular expenses after relocation and, ultimately, leading to spatial isolation and social exclusion. These findings demonstrate the contribution of the methodology to capturing the impacts of housing policies on the everyday accessibility of their beneficiaries, while emphasizing the importance of re-evaluating these policies with a particular focus on fostering the social and urban inclusion of beneficiaries.
{"title":"Evaluating the impact of social housing policies: Measuring accessibility changes when individuals move to social housing projects","authors":"Flavia Lopes, Lucas Figueiredo, Jorge Gil, Edja Trigueiro","doi":"10.1177/23998083231218774","DOIUrl":"https://doi.org/10.1177/23998083231218774","url":null,"abstract":"Addressing housing deficits and inequalities remains a key challenge for cities in promoting more sustainable urban development. In response to these challenges, governments around the world, particularly in the Global South, have made substantial investments in housing policies for middle- and low-income individuals. Nevertheless, while these initiatives increase housing provision, they often face criticism for not adequately considering the location of new residences. This oversight has far-reaching effects on the accessibility to essential facilities, which play a pivotal role in determining spatial advantages and disadvantages, and consequently, in the degree of inclusion of individuals in both the city and society. Addressing this critical role of accessibility, this paper introduces a methodology for assessing the potential impact of housing policies on the lives of their beneficiaries, by quantifying changes in cumulative accessibility levels between individuals' former house locations and the location of the housing projects into which they moved. Accessibility is calculated for three distinct transport modes: walking, cycling, and public transport, using unimodal and multimodal urban network models. A case study was conducted in Natal, northeastern Brazil, on the implementation of the Minha Casa, Minha Vida (My House, My Life, MCMV) housing policy, initiated in 2009 and still active today. The results of the study revealed a significant decrease in accessibility across all transportation modes when individuals moved to the new housing estates. The decline was particularly pronounced among individuals with lower incomes, potentially raising their regular expenses after relocation and, ultimately, leading to spatial isolation and social exclusion. These findings demonstrate the contribution of the methodology to capturing the impacts of housing policies on the everyday accessibility of their beneficiaries, while emphasizing the importance of re-evaluating these policies with a particular focus on fostering the social and urban inclusion of beneficiaries.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"29 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139227264","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}
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