Assessing healthy cities is a crucial strategy for realizing the concept of “health in all policies”. However, most current quantitative assessment methods for healthy cities are predominantly city-level and often overlook intra-urban evaluations. Building on the concept of geographic spatial case-based reasoning (CBR), we present an innovative healthy city spatial case-based reasoning (HCSCBR) model. This model comprehensively integrates spatial relationships and attribute characteristics that impact urban health. We conducted experiments using a detailed multi-source dataset of health environment determinants for middle-layer super output areas (MSOAs) in Birmingham, England. The results demonstrate that our method surpasses traditional data mining techniques in classification performance, offering greater accuracy and efficiency than conventional CBR models. The flexibility of this method permits its application not only in intra-city health evaluations but also in extending to inter-city assessments. Our research concludes that the HCSCBR model significantly improves the precision and reliability of healthy city assessments by incorporating spatial relationships. Additionally, the model’s adaptability and efficiency render it a valuable tool for urban planners and public health researchers. Future research will focus on integrating the temporal dimension to further enhance and refine the healthy city evaluation model, thereby increasing its dynamism and predictive accuracy.
{"title":"A Spatial Case-Based Reasoning Method for Healthy City Assessment: A Case Study of Middle Layer Super Output Areas (MSOAs) in Birmingham, England","authors":"Shuguang Deng, Wei Liu, Ying Peng, Binglin Liu","doi":"10.3390/ijgi13080271","DOIUrl":"https://doi.org/10.3390/ijgi13080271","url":null,"abstract":"Assessing healthy cities is a crucial strategy for realizing the concept of “health in all policies”. However, most current quantitative assessment methods for healthy cities are predominantly city-level and often overlook intra-urban evaluations. Building on the concept of geographic spatial case-based reasoning (CBR), we present an innovative healthy city spatial case-based reasoning (HCSCBR) model. This model comprehensively integrates spatial relationships and attribute characteristics that impact urban health. We conducted experiments using a detailed multi-source dataset of health environment determinants for middle-layer super output areas (MSOAs) in Birmingham, England. The results demonstrate that our method surpasses traditional data mining techniques in classification performance, offering greater accuracy and efficiency than conventional CBR models. The flexibility of this method permits its application not only in intra-city health evaluations but also in extending to inter-city assessments. Our research concludes that the HCSCBR model significantly improves the precision and reliability of healthy city assessments by incorporating spatial relationships. Additionally, the model’s adaptability and efficiency render it a valuable tool for urban planners and public health researchers. Future research will focus on integrating the temporal dimension to further enhance and refine the healthy city evaluation model, thereby increasing its dynamism and predictive accuracy.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"50 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Measuring human perception of environmental safety and quantifying the street view elements that affect human perception of environmental safety are of great significance for improving the urban environment and residents’ safety perception. However, domestic large-scale quantitative research on the safety perception of Chinese local cities needs to be deepened. Therefore, this paper chooses Chaoyang District in Beijing as the research area. Firstly, the network safety perception distribution of Chaoyang District is calculated and presented through the CNN model trained based on the perception dataset constructed by Chinese local cities. Then, the street view elements are extracted from the street view images using image semantic segmentation and target detection technology. Finally, the street view elements that affect the road safety perception are identified and analyzed based on LightGBM and SHAP interpretation framework. The results show the following: (1) the overall safety perception level of Chaoyang District in Beijing is high; (2) the number of motor vehicles and the proportion of the area of roads, skies, and sidewalks are the four factors that have the greatest impact on environmental safety perception; (3) there is an interaction between different street view elements on safety perception, and the proportion and number of street view elements have interaction on safety perception; (4) in the sections with the lowest, moderate, and highest levels of safety perception, the influence of street view elements on safety perception is inconsistent. Finally, this paper summarizes the results and points out the shortcomings of the research.
{"title":"Analysis of Road Safety Perception and Influencing Factors in a Complex Urban Environment—Taking Chaoyang District, Beijing, as an Example","authors":"Xinyu Hou, Peng Chen","doi":"10.3390/ijgi13080272","DOIUrl":"https://doi.org/10.3390/ijgi13080272","url":null,"abstract":"Measuring human perception of environmental safety and quantifying the street view elements that affect human perception of environmental safety are of great significance for improving the urban environment and residents’ safety perception. However, domestic large-scale quantitative research on the safety perception of Chinese local cities needs to be deepened. Therefore, this paper chooses Chaoyang District in Beijing as the research area. Firstly, the network safety perception distribution of Chaoyang District is calculated and presented through the CNN model trained based on the perception dataset constructed by Chinese local cities. Then, the street view elements are extracted from the street view images using image semantic segmentation and target detection technology. Finally, the street view elements that affect the road safety perception are identified and analyzed based on LightGBM and SHAP interpretation framework. The results show the following: (1) the overall safety perception level of Chaoyang District in Beijing is high; (2) the number of motor vehicles and the proportion of the area of roads, skies, and sidewalks are the four factors that have the greatest impact on environmental safety perception; (3) there is an interaction between different street view elements on safety perception, and the proportion and number of street view elements have interaction on safety perception; (4) in the sections with the lowest, moderate, and highest levels of safety perception, the influence of street view elements on safety perception is inconsistent. Finally, this paper summarizes the results and points out the shortcomings of the research.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"88 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper contributes to the expansion of green energy production, which is being pursued in order to mitigate climate change and carbon emissions from energy production. It addresses the delineation of areas that are suitable for the application of photovoltaics in the context of agricultural areas, water bodies, and parking spaces. Three specific photovoltaic types are examined in order to find out which criteria influence their geographic potential and whether spatial multi-criteria decision analysis methods are suitable for identifying suitable areas. The proposed approach consists of four steps: (1) collecting factors through expert interviews and questionnaires; (2) mapping the criteria to the spatial datasets; (3) deriving weighted scores for individual criteria through expert interviews; (4) applying the multi-criteria decision analysis method to compute and aggregate the final scores. We test our methodology at selected sites in the state of Styria, Austria. The test sites represent the topographical characteristics of the state and are about 5% of the size of Styria, approximately 820 km2. The key contributions are a weighted set of criteria that are relevant for the geographic potential of alternative photovoltaic types and the developed methodology to determine this potential.
{"title":"Multi-Criteria Decision Analysis to Evaluate the Geographic Potential of Alternative Photovoltaic Types","authors":"Franziska Hübl, Franz Welscher, Johannes Scholz","doi":"10.3390/ijgi13080269","DOIUrl":"https://doi.org/10.3390/ijgi13080269","url":null,"abstract":"This paper contributes to the expansion of green energy production, which is being pursued in order to mitigate climate change and carbon emissions from energy production. It addresses the delineation of areas that are suitable for the application of photovoltaics in the context of agricultural areas, water bodies, and parking spaces. Three specific photovoltaic types are examined in order to find out which criteria influence their geographic potential and whether spatial multi-criteria decision analysis methods are suitable for identifying suitable areas. The proposed approach consists of four steps: (1) collecting factors through expert interviews and questionnaires; (2) mapping the criteria to the spatial datasets; (3) deriving weighted scores for individual criteria through expert interviews; (4) applying the multi-criteria decision analysis method to compute and aggregate the final scores. We test our methodology at selected sites in the state of Styria, Austria. The test sites represent the topographical characteristics of the state and are about 5% of the size of Styria, approximately 820 km2. The key contributions are a weighted set of criteria that are relevant for the geographic potential of alternative photovoltaic types and the developed methodology to determine this potential.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"212 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
António Fernandes, Nataša Kovač, Hélder Fraga, André Fonseca, Sanja Šućur Radonjić, Marko Simeunović, Kruna Ratković, Christoph Menz, Sergi Costafreda-Aumedes, João A. Santos
The Montenegrin climate is characterised as very heterogeneous due to its complex topography. The viticultural heritage, dating back to before the Roman empire, is settled in a Mediterranean climate region, located south of the capital Podgorica, where climate conditions favour red wine production. However, an overall increase in warmer and drier periods affects traditional viticulture. The present study aims to discuss climate change impacts on Montenegrin viticulture. Bioclimatic indices, ensembled from five climate models, were analysed for both historical (1981–2010) and future (2041–2070) periods upon three socio-economic pathways: SSP1-2.6, SSP3-7.0 and SSP5-8.5. CHELSA (≈1 km) was the selected dataset for this analysis. Obtained results for all scenarios have shown the suppression of baseline conditions for viticulture. The average summer temperature might reach around 29.5 °C, and the growing season average temperature could become higher than 23.5 °C, advancing phenological events. The Winkler index is estimated to range from 2900 °C up to 3100 °C, which is too hot for viticulture. Montenegrin viticulture requires the application of adaptation measures focused on reducing temperature-increase impacts. The implementation of adaptation measures shall start in the coming years, to assure the lasting productivity and sustainability of viticulture.
由于地形复杂,黑山的气候特征非常多变。位于首都波德戈里察南部的地中海气候区的葡萄栽培传统可追溯到罗马帝国之前,那里的气候条件有利于红葡萄酒的生产。然而,气候变暖和干旱期的总体增加影响了传统的葡萄栽培。本研究旨在讨论气候变化对黑山葡萄栽培的影响。本研究根据三种社会经济路径,分析了由五个气候模型组合而成的历史(1981-2010 年)和未来(2041-2070 年)时期的生物气候指数:SSP1-2.6、SSP3-7.0 和 SSP5-8.5。本次分析选择了 CHELSA(≈1 km)数据集。所有方案的结果都表明,葡萄栽培的基准条件受到抑制。夏季平均气温可能达到 29.5 °C左右,生长季节平均气温可能高于 23.5 °C,使物候期提前。温克勒指数估计在 2900 °C 至 3100 °C 之间,这对葡萄栽培来说太热了。黑山葡萄栽培需要采取适应措施,重点是减少温度升高的影响。适应措施应在未来几年开始实施,以确保葡萄栽培的持久生产力和可持续性。
{"title":"Challenges to Viticulture in Montenegro under Climate Change","authors":"António Fernandes, Nataša Kovač, Hélder Fraga, André Fonseca, Sanja Šućur Radonjić, Marko Simeunović, Kruna Ratković, Christoph Menz, Sergi Costafreda-Aumedes, João A. Santos","doi":"10.3390/ijgi13080270","DOIUrl":"https://doi.org/10.3390/ijgi13080270","url":null,"abstract":"The Montenegrin climate is characterised as very heterogeneous due to its complex topography. The viticultural heritage, dating back to before the Roman empire, is settled in a Mediterranean climate region, located south of the capital Podgorica, where climate conditions favour red wine production. However, an overall increase in warmer and drier periods affects traditional viticulture. The present study aims to discuss climate change impacts on Montenegrin viticulture. Bioclimatic indices, ensembled from five climate models, were analysed for both historical (1981–2010) and future (2041–2070) periods upon three socio-economic pathways: SSP1-2.6, SSP3-7.0 and SSP5-8.5. CHELSA (≈1 km) was the selected dataset for this analysis. Obtained results for all scenarios have shown the suppression of baseline conditions for viticulture. The average summer temperature might reach around 29.5 °C, and the growing season average temperature could become higher than 23.5 °C, advancing phenological events. The Winkler index is estimated to range from 2900 °C up to 3100 °C, which is too hot for viticulture. Montenegrin viticulture requires the application of adaptation measures focused on reducing temperature-increase impacts. The implementation of adaptation measures shall start in the coming years, to assure the lasting productivity and sustainability of viticulture.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"34 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global population aging poses new challenges in allocating care facilities for the elderly. This demographic trend also influences economic development and the quality of urban life. However, current research focuses on the supply of elderly care facilities and primarily uses administrative divisions as a scale, resulting in low spatiotemporal sensitivity in evaluating the spatial equilibrium of elderly care facilities (SEECF). The relationship between the SEECF and economic development is not clear. In response to these problems, we proposed a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS) and explored the spatiotemporal associations between the SEECF and economic development. Considering the spatial accessibility rate of elderly care services (SARecs) and the spatiotemporal supply–demand ratio for elderly care services (STSDRecs), two types of supply–demand relationship factors were constructed. Then, a spatiotemporal accessibility of medical services (STAms) factor was obtained based on a modified two-step floating catchment area (M2SFCA) method. On this basis, the SEM-HSTS was constructed based on the theory of coordinated development. Further, a panel threshold model was employed to evaluate the influence relationships among population aging, SEECF, and gross domestic product (GDP) in different phases. Finally, spatial autocorrelation and Geodetector explored the spatial associations between SEECF and GDP across complex urban land use categories (ULUC). The experimental results at a 100-m grid scale showed that the SEM-HSTS exhibited higher spatiotemporal heterogeneity than the classical accessibility method, with elevated spatiotemporal sensitivity. Effectively identified various spatial imbalances, such as undersupply and resource waste. The panel model captured phased relationship changes, showing that SEECF had inhibitory and promotional effects on GDP in pre- and post-aging societies, with stronger effects as balance approached. Moreover, the combined interaction of ULUC and GDP had a more significant influence on SEECF than any individual factor, with GDP exerting a more significant influence. This study provides an empirical basis for creating resource-efficient elderly care facility systems and optimizing layouts.
全球人口老龄化给老年人护理设施的分配带来了新的挑战。这一人口趋势也影响着经济发展和城市生活质量。然而,目前的研究侧重于养老设施的供给,主要以行政区划为尺度,导致评估养老设施空间均衡(SEECF)的时空敏感性较低。同时,SEECF 与经济发展之间的关系也不明确。针对这些问题,我们提出了高时空敏感性的养老设施空间均衡模型(SEM-HSTS),并探讨了 SEECF 与经济发展之间的时空关联。考虑到养老服务空间可达率(SARecs)和养老服务时空供求比(STSDRecs),构建了两类供求关系因子。然后,根据修正的两步浮动集水区(M2SFCA)方法,得到了医疗服务时空可达性(STAms)因子。在此基础上,根据协调发展理论构建了 SEM-HSTS。然后,运用面板阈值模型评估了不同阶段人口老龄化、SEECF 和国内生产总值(GDP)之间的影响关系。最后,空间自相关和 Geodetector 探索了 SEECF 和 GDP 在复杂的城市土地利用类别(ULUC)中的空间关联。100 米网格尺度的实验结果表明,与经典的可达性方法相比,SEM-HSTS 表现出更高的时空异质性,具有更高的时空敏感性。有效识别了各种空间失衡现象,如供应不足和资源浪费。面板模型捕捉到了阶段性的关系变化,表明 SEECF 在老龄化前和老龄化后社会中对 GDP 有抑制和促进作用,随着平衡的临近,抑制和促进作用更强。此外,ULUC 和 GDP 的综合交互作用对 SEECF 的影响比任何单独因素都要显著,其中 GDP 的影响更为显著。这项研究为创建资源节约型养老设施系统和优化布局提供了实证依据。
{"title":"The Spatial Equilibrium Model of Elderly Care Facilities with High Spatiotemporal Sensitivity and Its Economic Associations Study","authors":"Hongyan Li, Rui Li, Jing Cai, Shunli Wang","doi":"10.3390/ijgi13080268","DOIUrl":"https://doi.org/10.3390/ijgi13080268","url":null,"abstract":"The global population aging poses new challenges in allocating care facilities for the elderly. This demographic trend also influences economic development and the quality of urban life. However, current research focuses on the supply of elderly care facilities and primarily uses administrative divisions as a scale, resulting in low spatiotemporal sensitivity in evaluating the spatial equilibrium of elderly care facilities (SEECF). The relationship between the SEECF and economic development is not clear. In response to these problems, we proposed a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS) and explored the spatiotemporal associations between the SEECF and economic development. Considering the spatial accessibility rate of elderly care services (SARecs) and the spatiotemporal supply–demand ratio for elderly care services (STSDRecs), two types of supply–demand relationship factors were constructed. Then, a spatiotemporal accessibility of medical services (STAms) factor was obtained based on a modified two-step floating catchment area (M2SFCA) method. On this basis, the SEM-HSTS was constructed based on the theory of coordinated development. Further, a panel threshold model was employed to evaluate the influence relationships among population aging, SEECF, and gross domestic product (GDP) in different phases. Finally, spatial autocorrelation and Geodetector explored the spatial associations between SEECF and GDP across complex urban land use categories (ULUC). The experimental results at a 100-m grid scale showed that the SEM-HSTS exhibited higher spatiotemporal heterogeneity than the classical accessibility method, with elevated spatiotemporal sensitivity. Effectively identified various spatial imbalances, such as undersupply and resource waste. The panel model captured phased relationship changes, showing that SEECF had inhibitory and promotional effects on GDP in pre- and post-aging societies, with stronger effects as balance approached. Moreover, the combined interaction of ULUC and GDP had a more significant influence on SEECF than any individual factor, with GDP exerting a more significant influence. This study provides an empirical basis for creating resource-efficient elderly care facility systems and optimizing layouts.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"35 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vicente Aprigliano, Sebastian Seriani, Catalina Toro, Gonzalo Rojas, Mitsuyoshi Fukushi, Marcus Cardoso, Marcelino Aurelio Vieira da Silva, Cristo Cucumides, Ualison Rébula de Oliveira, Cristián Henríquez, Andreas Braun, Volker Hochschild
The growing relevance of promoting a transition of urban mobility toward more sustainable modes of transport is leading to efforts to understand the effects of the built environment on the use of railway systems. In this direction, there are challenges regarding the creation of coherence between the locations of metro stations and their surroundings, which has been explored extensively in the academic community. This process is called Transit-Oriented Development (TOD). Within the context of Latin America, this study seeks to assess the influence of the built environment on the metro ridership in the metropolitan area of Valparaíso, Chile, testing two approaches of influence area definition, one of which is a fixed distance from the stations, and the other is based on the origin and destination survey of the study area. The analysis is based on Ordinary Least Squares regression (OLS) to identify the factors from the built environment, which affects the metro’s ridership. Results show that the models based on the area of influence defined through the use of the origin and destination survey explain the metro ridership better. Moreover, this study reveals that the metro system in Greater Valparaíso was not planned in harmony with urban development. The models demonstrate an inverse effect of the built environment on ridership, contrasting with the expected outcomes of a metro station designed following a Transit-Oriented Development approach.
{"title":"Built Environment Effect on Metro Ridership in Metropolitan Area of Valparaíso, Chile, under Different Influence Area Approaches","authors":"Vicente Aprigliano, Sebastian Seriani, Catalina Toro, Gonzalo Rojas, Mitsuyoshi Fukushi, Marcus Cardoso, Marcelino Aurelio Vieira da Silva, Cristo Cucumides, Ualison Rébula de Oliveira, Cristián Henríquez, Andreas Braun, Volker Hochschild","doi":"10.3390/ijgi13080266","DOIUrl":"https://doi.org/10.3390/ijgi13080266","url":null,"abstract":"The growing relevance of promoting a transition of urban mobility toward more sustainable modes of transport is leading to efforts to understand the effects of the built environment on the use of railway systems. In this direction, there are challenges regarding the creation of coherence between the locations of metro stations and their surroundings, which has been explored extensively in the academic community. This process is called Transit-Oriented Development (TOD). Within the context of Latin America, this study seeks to assess the influence of the built environment on the metro ridership in the metropolitan area of Valparaíso, Chile, testing two approaches of influence area definition, one of which is a fixed distance from the stations, and the other is based on the origin and destination survey of the study area. The analysis is based on Ordinary Least Squares regression (OLS) to identify the factors from the built environment, which affects the metro’s ridership. Results show that the models based on the area of influence defined through the use of the origin and destination survey explain the metro ridership better. Moreover, this study reveals that the metro system in Greater Valparaíso was not planned in harmony with urban development. The models demonstrate an inverse effect of the built environment on ridership, contrasting with the expected outcomes of a metro station designed following a Transit-Oriented Development approach.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"67 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study introduces an innovative scheme for classifying uncrewed aerial vehicle (UAV)-derived vehicle trajectory behaviors by employing machine learning (ML) techniques to transform original trajectories into various sequences: space–time, speed–time, and azimuth–time. These transformed sequences were subjected to normalization for uniform data analysis, facilitating the classification of trajectories into six distinct categories through the application of three ML classifiers: random forest, time series forest (TSF), and canonical time series characteristics. Testing was performed across three different intersections to reveal an accuracy exceeding 90%, underlining the superior performance of integrating azimuth–time and speed–time sequences over conventional space–time sequences for analyzing trajectory behaviors. This research highlights the TSF classifier’s robustness when incorporating speed data, demonstrating its efficiency in feature extraction and reliability in intricate trajectory pattern handling. This study’s results indicate that integrating direction and speed information significantly enhances predictive accuracy and model robustness. This comprehensive approach, which leverages UAV-derived trajectories and advanced ML techniques, represents a significant step forward in understanding vehicle trajectory behaviors, aligning with the goals of enhancing traffic control and management strategies for better urban mobility.
本研究采用机器学习(ML)技术,将原始轨迹转换为各种序列:时空、速度-时间和方位-时间,从而提出了一种创新方案,用于对无人驾驶航空飞行器(UAV)产生的飞行轨迹行为进行分类。对这些转换后的序列进行归一化处理,以便进行统一的数据分析,通过应用三种 ML 分类器(随机森林、时间序列森林 (TSF) 和典型时间序列特征)将轨迹分为六个不同的类别。在三个不同的交叉路口进行了测试,结果显示准确率超过 90%,这突出表明在分析轨迹行为时,方位角-时间序列和速度-时间序列的整合性能优于传统的时空序列。这项研究凸显了 TSF 分类器在整合速度数据时的鲁棒性,证明了其在特征提取方面的效率以及在处理复杂轨迹模式方面的可靠性。研究结果表明,整合方向和速度信息可显著提高预测准确性和模型稳健性。这种综合方法利用了无人机衍生轨迹和先进的 ML 技术,在理解车辆轨迹行为方面迈出了重要一步,符合加强交通控制和管理策略以改善城市交通的目标。
{"title":"Automatic Vehicle Trajectory Behavior Classification Based on Unmanned Aerial Vehicle-Derived Trajectories Using Machine Learning Techniques","authors":"Tee-Ann Teo, Min-Jhen Chang, Tsung-Han Wen","doi":"10.3390/ijgi13080264","DOIUrl":"https://doi.org/10.3390/ijgi13080264","url":null,"abstract":"This study introduces an innovative scheme for classifying uncrewed aerial vehicle (UAV)-derived vehicle trajectory behaviors by employing machine learning (ML) techniques to transform original trajectories into various sequences: space–time, speed–time, and azimuth–time. These transformed sequences were subjected to normalization for uniform data analysis, facilitating the classification of trajectories into six distinct categories through the application of three ML classifiers: random forest, time series forest (TSF), and canonical time series characteristics. Testing was performed across three different intersections to reveal an accuracy exceeding 90%, underlining the superior performance of integrating azimuth–time and speed–time sequences over conventional space–time sequences for analyzing trajectory behaviors. This research highlights the TSF classifier’s robustness when incorporating speed data, demonstrating its efficiency in feature extraction and reliability in intricate trajectory pattern handling. This study’s results indicate that integrating direction and speed information significantly enhances predictive accuracy and model robustness. This comprehensive approach, which leverages UAV-derived trajectories and advanced ML techniques, represents a significant step forward in understanding vehicle trajectory behaviors, aligning with the goals of enhancing traffic control and management strategies for better urban mobility.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"25 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite extensive investigations on urban metro passenger flows, their evolving spatiotemporal patterns with the extensions of urban metro networks have not been well understood. Using Shenzhen as a case study city, our study initiates an investigation into this matter by analyzing the evolving network topology of Shenzhen Metro. Subsequently, leveraging long-term smart card data, we analyze the evolving spatiotemporal patterns of passenger flows and develop an analytical approach to pinpoint the major passenger sources of urban metro congestion. While the passenger travel demand and the passenger flow volumes kept increasing with the extension of the urban metro network, the major passenger sources were very stable in space, highlighting the inherent invariance in the evolution of the urban metro system. Finally, we analyze the impact of population and land use factors on passenger flow contributions of passenger sources, obtaining useful clues to foresee future passenger flow conditions.
{"title":"Exploring the Spatiotemporal Patterns of Passenger Flows in Expanding Urban Metros: A Case Study of Shenzhen","authors":"Sirui Lv, Hu Yang, Xin Lu, Fan Zhang, Pu Wang","doi":"10.3390/ijgi13080267","DOIUrl":"https://doi.org/10.3390/ijgi13080267","url":null,"abstract":"Despite extensive investigations on urban metro passenger flows, their evolving spatiotemporal patterns with the extensions of urban metro networks have not been well understood. Using Shenzhen as a case study city, our study initiates an investigation into this matter by analyzing the evolving network topology of Shenzhen Metro. Subsequently, leveraging long-term smart card data, we analyze the evolving spatiotemporal patterns of passenger flows and develop an analytical approach to pinpoint the major passenger sources of urban metro congestion. While the passenger travel demand and the passenger flow volumes kept increasing with the extension of the urban metro network, the major passenger sources were very stable in space, highlighting the inherent invariance in the evolution of the urban metro system. Finally, we analyze the impact of population and land use factors on passenger flow contributions of passenger sources, obtaining useful clues to foresee future passenger flow conditions.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"64 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Building height (BH) estimation is crucial for urban spatial planning and development. BH estimation using digital surface model data involves obtaining ground and roof elevations. However, vegetation and shadows around buildings affect the selection of the required elevation, resulting in large BH estimation errors. In highly urbanized areas, buildings of similar heights often have similar characteristics and spatial proximity, which have reference significance in BH estimation but are rarely utilized. Herein, we propose a BH estimation method based on BIRCH clustering and a random forest (RF) model. We obtain the initial BH results using a method based on the optimal ground search area and a multi-index evaluation. BIRCH clustering and an RF classification model are used to match buildings of similar heights based on their spatial distance and attribute characteristics. Finally, the BH is adjusted based on the ground elevation obtained from the secondary screening and the BH matching. The validation results from two areas with over 12,000 buildings show that the proposed method reduces the root-mean-square error of the final BH results compared with the initial results. Comparing the obtained height maps shows that the final results produce a relatively accurate BH in areas with high shading and vegetation coverage, as well as in areas with dense buildings. Thus, the proposed method has been validated for its effectiveness and reliability.
{"title":"Building Height Extraction Based on Spatial Clustering and a Random Forest Model","authors":"Jingxin Chang, Yonghua Jiang, Meilin Tan, Yunming Wang, Shaodong Wei","doi":"10.3390/ijgi13080265","DOIUrl":"https://doi.org/10.3390/ijgi13080265","url":null,"abstract":"Building height (BH) estimation is crucial for urban spatial planning and development. BH estimation using digital surface model data involves obtaining ground and roof elevations. However, vegetation and shadows around buildings affect the selection of the required elevation, resulting in large BH estimation errors. In highly urbanized areas, buildings of similar heights often have similar characteristics and spatial proximity, which have reference significance in BH estimation but are rarely utilized. Herein, we propose a BH estimation method based on BIRCH clustering and a random forest (RF) model. We obtain the initial BH results using a method based on the optimal ground search area and a multi-index evaluation. BIRCH clustering and an RF classification model are used to match buildings of similar heights based on their spatial distance and attribute characteristics. Finally, the BH is adjusted based on the ground elevation obtained from the secondary screening and the BH matching. The validation results from two areas with over 12,000 buildings show that the proposed method reduces the root-mean-square error of the final BH results compared with the initial results. Comparing the obtained height maps shows that the final results produce a relatively accurate BH in areas with high shading and vegetation coverage, as well as in areas with dense buildings. Thus, the proposed method has been validated for its effectiveness and reliability.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"49 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Measuring the accessibility of each traffic zone to high-speed railway stations can evaluate the ease of the transportation hub in the transportation system. The utility-based model, which captures individual travel behavior and subjective perception, is often used to quantify the travel impedance on accessibility for a given origin–destination pair. However, existing studies neglect the impacts of travel time uncertainty on utility and possible choice set when measuring accessibility, especially in high-timeliness travel (e.g., railway stations or airports). This study proposes a novel integration of the utility-based model and multimodal space–time prism under travel time uncertainty to measure reliable accessibility to high-speed railway stations. First, the reliable multimodal space–time prism is developed to generate a reliable travel mode choice set constrained by travel time budgets. Then, the reliable choice set is integrated into the utility-based model with the utility function derived from a proposed mean–standard deviation logit-based mode choice model. Finally, this study contributes to measuring reliable accessibility within areas from Beijing’s 5th Ring Road to the Beijing South Railway Station. Based on the results, policymakers can effectively evaluate the distribution of transportation resources and urban planning.
{"title":"Measuring Reliable Accessibility to High-Speed Railway Stations by Integrating the Utility-Based Model and Multimodal Space–Time Prism under Travel Time Uncertainty","authors":"Yongsheng Zhang, Kangyu Liang, Enjian Yao, Mingyi Gu","doi":"10.3390/ijgi13080263","DOIUrl":"https://doi.org/10.3390/ijgi13080263","url":null,"abstract":"Measuring the accessibility of each traffic zone to high-speed railway stations can evaluate the ease of the transportation hub in the transportation system. The utility-based model, which captures individual travel behavior and subjective perception, is often used to quantify the travel impedance on accessibility for a given origin–destination pair. However, existing studies neglect the impacts of travel time uncertainty on utility and possible choice set when measuring accessibility, especially in high-timeliness travel (e.g., railway stations or airports). This study proposes a novel integration of the utility-based model and multimodal space–time prism under travel time uncertainty to measure reliable accessibility to high-speed railway stations. First, the reliable multimodal space–time prism is developed to generate a reliable travel mode choice set constrained by travel time budgets. Then, the reliable choice set is integrated into the utility-based model with the utility function derived from a proposed mean–standard deviation logit-based mode choice model. Finally, this study contributes to measuring reliable accessibility within areas from Beijing’s 5th Ring Road to the Beijing South Railway Station. Based on the results, policymakers can effectively evaluate the distribution of transportation resources and urban planning.","PeriodicalId":48738,"journal":{"name":"ISPRS International Journal of Geo-Information","volume":"9 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}