Pub Date : 2023-11-26DOI: 10.1177/23998083231217770
Gabriel Valença, Filipe Moura, Ana Morais de Sá
Road space distribution has traditionally been based on the hierarchical classification of streets. In arterials, the majority of space is dedicated to traffic lanes, whereas local streets typically have fewer traffic lanes and more space for parking or sidewalks. Within urban areas, road space is contested between two main types of spaces: corridors of movement, and places for access and standing/stillness/staying. Given the limited availability of urban space, particularly in central areas, deciding how to allocate space for these functions poses a dilemma and requires tradeoffs. Nonetheless, certain areas experience underutilization and inefficiencies in space utilization over time. In this context, we propose a site selection methodology to identify complex zones within a city where different types of users and demands compete for space. These zones present the potential for dynamically allocating road space based on fluctuating demands and policy objectives. This methodology serves as an initial guide for planners to identify zones that require a thorough evaluation of activities and diverse temporal-spatial demands when reallocating road space. We use network centrality, land use indicators, traffic, and public transport dynamics indicators to detect complex zones and apply them to a Lisbon case study.
{"title":"Where is it complex to reallocate road space?","authors":"Gabriel Valença, Filipe Moura, Ana Morais de Sá","doi":"10.1177/23998083231217770","DOIUrl":"https://doi.org/10.1177/23998083231217770","url":null,"abstract":"Road space distribution has traditionally been based on the hierarchical classification of streets. In arterials, the majority of space is dedicated to traffic lanes, whereas local streets typically have fewer traffic lanes and more space for parking or sidewalks. Within urban areas, road space is contested between two main types of spaces: corridors of movement, and places for access and standing/stillness/staying. Given the limited availability of urban space, particularly in central areas, deciding how to allocate space for these functions poses a dilemma and requires tradeoffs. Nonetheless, certain areas experience underutilization and inefficiencies in space utilization over time. In this context, we propose a site selection methodology to identify complex zones within a city where different types of users and demands compete for space. These zones present the potential for dynamically allocating road space based on fluctuating demands and policy objectives. This methodology serves as an initial guide for planners to identify zones that require a thorough evaluation of activities and diverse temporal-spatial demands when reallocating road space. We use network centrality, land use indicators, traffic, and public transport dynamics indicators to detect complex zones and apply them to a Lisbon case study.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"41 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235666","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 : 2023-11-23DOI: 10.1177/23998083231217014
Antoine Peris, Laure Casanova Enault
This paper contributes to the debate on the liquidity of real estate investment in the context of financialisation. Using microdata built from tax registers, we analyse the geography of rental housing purchases by private individuals from three French cities. We develop a modelling approach in order to better understand the respective roles of space and market characteristics in determining buy-to-let investment flows. Considering the distribution of the data and our objective of integrating both intra- and intercity housing investments in a single model, we use an adaptive zoning approach. This approach allows high spatial resolution where interactions are strong to be kept and the aggregation of more distant, less populated areas. We demonstrate that geographical proximity is highly determinant in explaining flows of buy-to-let investments from private individuals. We also uncover striking facts related to the geography of rental investments, such as the convergence of investments from rich suburbs toward the centre of agglomerations and preferential flows from the Paris region to southern and coastal cities. Finally, we find that investors tend to buy in upmarket areas and in places that are more expensive than their market of residence. Our results indicate that geographical proximity and safety of investments are key factors in housing wealth accumulation by private individuals.
{"title":"Proximity or opportunity? Spatial and market determinants of private individuals’ buy-to-let investments","authors":"Antoine Peris, Laure Casanova Enault","doi":"10.1177/23998083231217014","DOIUrl":"https://doi.org/10.1177/23998083231217014","url":null,"abstract":"This paper contributes to the debate on the liquidity of real estate investment in the context of financialisation. Using microdata built from tax registers, we analyse the geography of rental housing purchases by private individuals from three French cities. We develop a modelling approach in order to better understand the respective roles of space and market characteristics in determining buy-to-let investment flows. Considering the distribution of the data and our objective of integrating both intra- and intercity housing investments in a single model, we use an adaptive zoning approach. This approach allows high spatial resolution where interactions are strong to be kept and the aggregation of more distant, less populated areas. We demonstrate that geographical proximity is highly determinant in explaining flows of buy-to-let investments from private individuals. We also uncover striking facts related to the geography of rental investments, such as the convergence of investments from rich suburbs toward the centre of agglomerations and preferential flows from the Paris region to southern and coastal cities. Finally, we find that investors tend to buy in upmarket areas and in places that are more expensive than their market of residence. Our results indicate that geographical proximity and safety of investments are key factors in housing wealth accumulation by private individuals.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"105 ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139244294","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 : 2023-11-21DOI: 10.1177/23998083231217013
J. Jeong
Although administrative boundaries are non-physical, they can cause regional inequalities through boundary effects that result in discontinuities between areas. The boundary effect refers to the disparities in policy, economic, and social aspects between areas caused by administrative boundaries, which can lead to regional differences. This study aims to identify the mechanisms that induce discontinuities in regional development due to administrative boundaries. The boundary effect mechanism assumed to include the spillover, fragmentation, and hierarchy effects were examined using six scenarios, each modeled using a spatial economic model. Through the comparison of various scenarios, we have demonstrated the potential validity of the three components comprising the assumed boundary effect. Furthermore, we have confirmed that the model incorporating all effects that we assumed in our research, namely spillover, fragmentation, and hierarchy effects, provides the best fit. We hypothesized and verified the mechanism of boundary effects that disrupt regional development, thereby enhancing the understanding of these effects.
{"title":"Discontinuities in regional economic development due to administrative boundaries: Examining the mechanisms of the boundary effect","authors":"J. Jeong","doi":"10.1177/23998083231217013","DOIUrl":"https://doi.org/10.1177/23998083231217013","url":null,"abstract":"Although administrative boundaries are non-physical, they can cause regional inequalities through boundary effects that result in discontinuities between areas. The boundary effect refers to the disparities in policy, economic, and social aspects between areas caused by administrative boundaries, which can lead to regional differences. This study aims to identify the mechanisms that induce discontinuities in regional development due to administrative boundaries. The boundary effect mechanism assumed to include the spillover, fragmentation, and hierarchy effects were examined using six scenarios, each modeled using a spatial economic model. Through the comparison of various scenarios, we have demonstrated the potential validity of the three components comprising the assumed boundary effect. Furthermore, we have confirmed that the model incorporating all effects that we assumed in our research, namely spillover, fragmentation, and hierarchy effects, provides the best fit. We hypothesized and verified the mechanism of boundary effects that disrupt regional development, thereby enhancing the understanding of these effects.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"115 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139252851","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 : 2023-11-16DOI: 10.1177/23998083231215825
Yue Lin
Small area estimation is critical for a wide range of applications, including urban planning, funding distribution, and policy formulation. Individual-level population data, which typically include each individual’s socio-demographic characteristics and small area location, are a rich source of information for small area estimation. However, individual-level population data are often not made public due to confidentiality concerns. This paper describes the development of a public-use synthetic individual-level population dataset in the United States that can be useful for small area estimation. This dataset contains characteristics of housing type, age, sex, race, and Hispanic or Latino origin for all 308,745,538 individuals in the United States at the census block group level, based on publicly available aggregated data from the 2010 Census. Experimental results suggest the validity of the synthetic data by comparing it to different data sources, and we show examples of how this dataset can be used in small area estimation.
{"title":"Synthetic population data for small area estimation in the United States","authors":"Yue Lin","doi":"10.1177/23998083231215825","DOIUrl":"https://doi.org/10.1177/23998083231215825","url":null,"abstract":"Small area estimation is critical for a wide range of applications, including urban planning, funding distribution, and policy formulation. Individual-level population data, which typically include each individual’s socio-demographic characteristics and small area location, are a rich source of information for small area estimation. However, individual-level population data are often not made public due to confidentiality concerns. This paper describes the development of a public-use synthetic individual-level population dataset in the United States that can be useful for small area estimation. This dataset contains characteristics of housing type, age, sex, race, and Hispanic or Latino origin for all 308,745,538 individuals in the United States at the census block group level, based on publicly available aggregated data from the 2010 Census. Experimental results suggest the validity of the synthetic data by comparing it to different data sources, and we show examples of how this dataset can be used in small area estimation.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"78 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139269652","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 : 2023-11-16DOI: 10.1177/23998083231217012
Zoltán Bereczki, G. Csomós, Jenő Zsold Farkas
Globally, dramatic changes in park visitation have accompanied the COVID-19 pandemic. In general, cities have experienced an overall increase in park visitation after strict lockdowns imposed in the pandemic’s first wave have been removed. However, previous research conducted in Hungary has demonstrated that park visitation varied across parks with different sizes and locations in the city. We hypothesized that the degree of the park’s integration into the urban fabric significantly affected changes in visitation. To test this hypothesis, we conducted a space syntax analysis. Findings show that community parks with an area of 10.01–50.00 hectares and a mean spatial integration of 83.37 experienced the highest increase in the number of visitors (based on mobile devices’ GNSS data). Surprisingly, large metropolitan parks providing highly complex ecosystem services lost many visitors during the pandemic, which might be due to their low spatial integration.
{"title":"Analyzing urban parks’ spatial integration in Budapest to understand changes in visitation patterns during the COVID-19 pandemic","authors":"Zoltán Bereczki, G. Csomós, Jenő Zsold Farkas","doi":"10.1177/23998083231217012","DOIUrl":"https://doi.org/10.1177/23998083231217012","url":null,"abstract":"Globally, dramatic changes in park visitation have accompanied the COVID-19 pandemic. In general, cities have experienced an overall increase in park visitation after strict lockdowns imposed in the pandemic’s first wave have been removed. However, previous research conducted in Hungary has demonstrated that park visitation varied across parks with different sizes and locations in the city. We hypothesized that the degree of the park’s integration into the urban fabric significantly affected changes in visitation. To test this hypothesis, we conducted a space syntax analysis. Findings show that community parks with an area of 10.01–50.00 hectares and a mean spatial integration of 83.37 experienced the highest increase in the number of visitors (based on mobile devices’ GNSS data). Surprisingly, large metropolitan parks providing highly complex ecosystem services lost many visitors during the pandemic, which might be due to their low spatial integration.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"35 4","pages":"286 - 289"},"PeriodicalIF":3.5,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139269489","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 : 2023-11-16DOI: 10.1177/23998083231215463
Will B. Payne, Evangeline McGlynn
When mapping relationships across multiple spatial scales, prevailing visualization techniques treat every mile of distance equally, which may not be appropriate for studying phenomena with long-tail distributions of distances from a common point of reference (e.g., retail customer locations, remittance flows, and migration data). While quantitative geography has long acknowledged that non-Cartesian spaces and distances are often more appropriate for analyzing and visualizing real-world data and complex spatial phenomena, commonly available GIS software solutions make working with non-linear distances extremely difficult. Our Relational Reprojection Platform (RRP) fills this gap with a simple stereographic projection engine centering any given data point to the rest of the set, and transforming great circle distances from this point to the other locations using a set of broadly applicable non-linear functions as options. This method of reprojecting data allows users to quickly and easily explore how non-linear distance transformations (including square root and logarithmic reprojections) reveal more complex spatial patterns within datasets than standard projections allow. Our initial release allows users to upload comma separated value (CSV) files with geographic coordinates and data columns and minimal cleaning and explore a variety of spatial transformations of their data. We hope this heuristic tool will enhance the exploratory stages of social research using spatial data.
{"title":"Relational Reprojection Platform: Non-linear distance transformations of spatial data in R","authors":"Will B. Payne, Evangeline McGlynn","doi":"10.1177/23998083231215463","DOIUrl":"https://doi.org/10.1177/23998083231215463","url":null,"abstract":"When mapping relationships across multiple spatial scales, prevailing visualization techniques treat every mile of distance equally, which may not be appropriate for studying phenomena with long-tail distributions of distances from a common point of reference (e.g., retail customer locations, remittance flows, and migration data). While quantitative geography has long acknowledged that non-Cartesian spaces and distances are often more appropriate for analyzing and visualizing real-world data and complex spatial phenomena, commonly available GIS software solutions make working with non-linear distances extremely difficult. Our Relational Reprojection Platform (RRP) fills this gap with a simple stereographic projection engine centering any given data point to the rest of the set, and transforming great circle distances from this point to the other locations using a set of broadly applicable non-linear functions as options. This method of reprojecting data allows users to quickly and easily explore how non-linear distance transformations (including square root and logarithmic reprojections) reveal more complex spatial patterns within datasets than standard projections allow. Our initial release allows users to upload comma separated value (CSV) files with geographic coordinates and data columns and minimal cleaning and explore a variety of spatial transformations of their data. We hope this heuristic tool will enhance the exploratory stages of social research using spatial data.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"93 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139270258","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 : 2023-11-15DOI: 10.1177/23998083231215462
Heather Anne Kaths
The pathways used by cyclists, pedestrians, and users of micromobility to cross intersections do not always align with those planned by traffic engineers. Observing actual usage patterns could lead to a better understanding of the tactical behavior of users of active and micromobility, allowing planners and engineers to create urban environments specifically for these road users. An open-source Python tool is introduced that uses clustering to automatically identify the forms of pathways used by road users. The tool was used to cluster trajectories from five intersections in Germany. The exemplar of each cluster is selected to represent the average shape of each pathway type. The open-source Python tool RoadUserPathways is introduced, the case studies are examined and use cases are presented.
{"title":"Crossing intersections: A tool for investigating road user pathways","authors":"Heather Anne Kaths","doi":"10.1177/23998083231215462","DOIUrl":"https://doi.org/10.1177/23998083231215462","url":null,"abstract":"The pathways used by cyclists, pedestrians, and users of micromobility to cross intersections do not always align with those planned by traffic engineers. Observing actual usage patterns could lead to a better understanding of the tactical behavior of users of active and micromobility, allowing planners and engineers to create urban environments specifically for these road users. An open-source Python tool is introduced that uses clustering to automatically identify the forms of pathways used by road users. The tool was used to cluster trajectories from five intersections in Germany. The exemplar of each cluster is selected to represent the average shape of each pathway type. The open-source Python tool RoadUserPathways is introduced, the case studies are examined and use cases are presented.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"110 1","pages":"275 - 281"},"PeriodicalIF":3.5,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139274407","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 : 2023-11-08DOI: 10.1177/23998083231213695
Hulusi Eren Efeoglu, Anssi Joutsiniemi, Skirmante Mozuriunaite
This study examines the impact of the morphological characteristics of plots in the Helsinki Metropolitan Area (HMA) on the retail landscape, with a focus on understanding the ways in which the morphological characteristics potentially influence the distribution, agglomeration and diversity of retail businesses. Although frequently underestimated in contemporary placemaking practices, this research emphasizes the role of the dual nature of plots as an element of urban form and an element of control over the retail landscape of the city. In this sense, the role of the morphological characteristics of plots in shaping the retail landscape of the city was investigated. The compositional (size, frontage ratio) and configurational (integration, betweenness, frequency) features of the plot in the HMA ( n = 77,736) were measured. Thereafter an unsupervised two-step clustering method was applied to reveal the subtle morphological regions through plot patterns. Computational plot characterization with open data sets yielded six plot types having different morphological characteristics and geographic distribution patterns. The spatial capacities of each plot type for retail distribution, agglomeration and diversity were then analysed and compared. This research argues that the interrelationship of the dual nature of plot plays an important role in placemaking processes. The results suggest that the spatial capacity of plots to accommodate street-based retail clusters is improved with spatially integrated, fine-grained urban fabric with independent micro-businesses involving a diversity of uses and actors. The study argues that these spatial conditions might also increase retail resilience and contribute to the vitality and viability of the retail landscape.
{"title":"Exploring the plot patterns of the retail landscape: The case of the Helsinki Metropolitan area","authors":"Hulusi Eren Efeoglu, Anssi Joutsiniemi, Skirmante Mozuriunaite","doi":"10.1177/23998083231213695","DOIUrl":"https://doi.org/10.1177/23998083231213695","url":null,"abstract":"This study examines the impact of the morphological characteristics of plots in the Helsinki Metropolitan Area (HMA) on the retail landscape, with a focus on understanding the ways in which the morphological characteristics potentially influence the distribution, agglomeration and diversity of retail businesses. Although frequently underestimated in contemporary placemaking practices, this research emphasizes the role of the dual nature of plots as an element of urban form and an element of control over the retail landscape of the city. In this sense, the role of the morphological characteristics of plots in shaping the retail landscape of the city was investigated. The compositional (size, frontage ratio) and configurational (integration, betweenness, frequency) features of the plot in the HMA ( n = 77,736) were measured. Thereafter an unsupervised two-step clustering method was applied to reveal the subtle morphological regions through plot patterns. Computational plot characterization with open data sets yielded six plot types having different morphological characteristics and geographic distribution patterns. The spatial capacities of each plot type for retail distribution, agglomeration and diversity were then analysed and compared. This research argues that the interrelationship of the dual nature of plot plays an important role in placemaking processes. The results suggest that the spatial capacity of plots to accommodate street-based retail clusters is improved with spatially integrated, fine-grained urban fabric with independent micro-businesses involving a diversity of uses and actors. The study argues that these spatial conditions might also increase retail resilience and contribute to the vitality and viability of the retail landscape.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":" 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135341126","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 : 2023-11-08DOI: 10.1177/23998083231213894
Atsushi Takizawa
Access graphs that indicate adjacency relationships from the perspective of flow lines of rooms are extracted automatically from a large number of floor plan images of a family-oriented rental apartment complex in Osaka Prefecture, Japan, based on a recently proposed access graph extraction method with slight modifications. We define and implement a graph convolutional network (GCN) for access graphs and propose a model to estimate the real estate value of access graphs as the floor plan value. The model, which includes the floor plan value and hedonic method using other general explanatory variables, is used to estimate rents, and their estimation accuracies are compared. In addition, the features of the floor plan that explain the rent are analyzed from the learned convolution network. The results show that the proposed method significantly improves the accuracy of rent estimation compared to that of conventional models, and it is possible to understand the specific spatial configuration rules that influence the value of a floor plan by analyzing the learned GCN.
{"title":"Extracting real estate values of rental apartment floor plans using graph convolutional networks","authors":"Atsushi Takizawa","doi":"10.1177/23998083231213894","DOIUrl":"https://doi.org/10.1177/23998083231213894","url":null,"abstract":"Access graphs that indicate adjacency relationships from the perspective of flow lines of rooms are extracted automatically from a large number of floor plan images of a family-oriented rental apartment complex in Osaka Prefecture, Japan, based on a recently proposed access graph extraction method with slight modifications. We define and implement a graph convolutional network (GCN) for access graphs and propose a model to estimate the real estate value of access graphs as the floor plan value. The model, which includes the floor plan value and hedonic method using other general explanatory variables, is used to estimate rents, and their estimation accuracies are compared. In addition, the features of the floor plan that explain the rent are analyzed from the learned convolution network. The results show that the proposed method significantly improves the accuracy of rent estimation compared to that of conventional models, and it is possible to understand the specific spatial configuration rules that influence the value of a floor plan by analyzing the learned GCN.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"9 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391143","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 : 2023-11-07DOI: 10.1177/23998083231204691
Hiroyuki Usui
Whether or not a streetscape skeleton – the 3D spaces of streets defined by the arrangement of surrounding buildings – is vertically harmonious depends to a large extent on the degree of difference between the heights of buildings adjacent to one another, known as the relative spatial variability in building heights. Surprisingly, this subject has been overlooked in previous studies examining the harmony of streetscapes. Data on precise building heights are indispensable for evaluating the relative spatial variability in building heights and its spatial association. The recent relaxation of data limitations on precise building heights in Tokyo enabled us to identify the relative spatial variability in building heights and quantify its spatial association. Therefore, in this paper we aim to answer the following question: where are harmonious or inharmonious building heights locally clustered? To this end, we computed the spatial association of the relative spatial variability in building heights as a set of edges whose indices enabled us to evaluate the local indicator of spatial association (LISA). Subsequently, we statistically demarcated locally harmonious and inharmonious building heights without having to set predetermined basic spatial units. In this respect, our methods and findings are novel and can contribute to establishing a new method for measuring the variability in vertical streetscape skeletons, which is important for developing urban design policies.
{"title":"Relative spatial variability in building heights and its spatial association: Application for the spatial clustering of harmonious and inharmonious building heights in Tokyo","authors":"Hiroyuki Usui","doi":"10.1177/23998083231204691","DOIUrl":"https://doi.org/10.1177/23998083231204691","url":null,"abstract":"Whether or not a streetscape skeleton – the 3D spaces of streets defined by the arrangement of surrounding buildings – is vertically harmonious depends to a large extent on the degree of difference between the heights of buildings adjacent to one another, known as the relative spatial variability in building heights. Surprisingly, this subject has been overlooked in previous studies examining the harmony of streetscapes. Data on precise building heights are indispensable for evaluating the relative spatial variability in building heights and its spatial association. The recent relaxation of data limitations on precise building heights in Tokyo enabled us to identify the relative spatial variability in building heights and quantify its spatial association. Therefore, in this paper we aim to answer the following question: where are harmonious or inharmonious building heights locally clustered? To this end, we computed the spatial association of the relative spatial variability in building heights as a set of edges whose indices enabled us to evaluate the local indicator of spatial association (LISA). Subsequently, we statistically demarcated locally harmonious and inharmonious building heights without having to set predetermined basic spatial units. In this respect, our methods and findings are novel and can contribute to establishing a new method for measuring the variability in vertical streetscape skeletons, which is important for developing urban design policies.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"316 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135474918","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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