Applied Spatial Analysis and Policy最新文献

{"title":"Spatial Analysis and Time Trend Regression of Multifactorial Violence-Related Death and its Connection with Public Health in Nigeria","authors":"Oluyemi A. Okunlola,&nbsp;Oluwaseun A. Otekunrin,&nbsp;Idowu P. Adewumi,&nbsp;Toyin O. Oguntola,&nbsp;OlaOluwa S. Yaya","doi":"10.1007/s12061-025-09642-w","DOIUrl":"10.1007/s12061-025-09642-w","url":null,"abstract":"<div><p>Interpersonal violence poses a formidable obstacle to harmonious coexistence, socioeconomic development, and public health globally, given its deleterious consequences and attendant mortality. In a multicultural society like Nigeria, violence is an unfortunate inevitability. This study undertakes a spatial analysis and Poisson time trend analysis of violence-related mortality cases in Nigeria, aiming to elucidate the dynamics, assess the public health burden, estimate relative risk, identify hotspots, and inform policy interventions to mitigate violence in severely affected areas. A total of 195,170 cases were recorded between 2006 and 2023, with Borno (46,425), Lagos (12,086), and Kaduna (10,548) accounting for 24%, 6%, and 5% of cases, respectively. In contrast, Ekiti state had the lowest number of cases (752). Notably, death rates in 2014 and 2015 accounted for 12% and 9% of all deaths rates that were attributed to violence during the period considered. The violent death rate showed clear regional differences, with over half of all death rates occurring in the North Central and North East regions. North West and South South regions contributed 12% and 14%, respectively while South East and South West regions contributed 8% and 10% of the remaining share, respectively. These figures show statistically significant socioeconomic and public health differences between the country's northern and southern regions (<i>P</i> &lt; 0.000). Analysis of relative risk showed that while Plateau, Cross River, and Anambra had constant incidence rates, 27 states had elevated relative risk and seven states had a minimal drop in violence-related death. According to the study's findings, violence can have a significant impact on the health of mothers and children, making the nation's already fragile public health situation much worse. These findings underscore the complexity of Nigeria's violence landscape, highlighting the need for targeted, region-specific interventions to address the escalating violence and its public health repercussions. Policymakers and governments at all levels must prioritize evidence-based strategies to mitigate violence and promote peaceful coexistence in Nigeria.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Spatio-temporal Heterogeneity of the Impacts of Urban Form on the Ground-level Anthropogenic PM2.5 Pollution in Chinese Cities","authors":"Yuanzheng Cui,&nbsp;Dong Hua,&nbsp;Mi Zhang,&nbsp;Hui Zha,&nbsp;Xiangbo Fan,&nbsp;Lulu Chen,&nbsp;Lei Jiang,&nbsp;Lei Wang,&nbsp;Xuejun Duan","doi":"10.1007/s12061-025-09641-x","DOIUrl":"10.1007/s12061-025-09641-x","url":null,"abstract":"<div><p>In recent years, the impact of urban form evolution on atmospheric pollution has become increasingly prominent. However, previous studies have rarely examined the combined influence of urban spatial forms and human perception on air pollution, while excluding emissions from natural sources. To address this gap, our study investigates the spatiotemporal dynamics of the relationship between anthropogenic PM_2.5 pollution and urban form in China from 2000 to 2019. Using the Geographically and Temporally Weighted Regression (GTWR) model, we analyze the spatial heterogeneity of the impact of urban form on PM_2.5 pollution. Our findings reveal that anthropogenic PM_2.5 concentrations in China exhibited an initial increase, followed by a decline after 2013. In heavily polluted regions, such as the Beijing-Tianjin-Hebei area, annual average concentrations in most areas exceeded 60 μg/m³, with southern Hebei exceeding 100 μg/m³. The northern, southwestern, and Yangtze River Economic Belt regions had relatively lower concentrations, but still ranged between 20 and 60 μg/m³. Increasing urban compactness, reducing urban sprawl, and enhancing the complexity of urban form were found to contribute to lower anthropogenic PM_2.5 levels in most cities. Additionally, climate conditions characterized by high precipitation and temperature, along with urban form patterns featuring high density, cohesion, and controlled expansion, were associated with reduced anthropogenic PM_2.5 concentrations. In contrast, high humidity, dense populations, a thriving secondary sector, heavy traffic flow, and large, complex urban forms were likely to exacerbate anthropogenic PM_2.5 pollution. These findings provide scientific insights for coordinated strategies to control atmospheric pollution in Chinese cities.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modal Accessibility Gap in Curitiba (Brazil). Dynamic Analysis Considering Time and Spatial Variations","authors":"Paulo de Almeida Correia Jr.,&nbsp;José Carpio-Pinedo,&nbsp;Borja Moya-Gómez,&nbsp;Ana Condeço-Mehorado","doi":"10.1007/s12061-025-09639-5","DOIUrl":"10.1007/s12061-025-09639-5","url":null,"abstract":"<div><p>This paper analyzes the accessibility of Curitiba, Brazil, by combining high-detail, big-data-informed automobile dynamic distance matrices from TomTom Traffic Stats and a bus network database - GTFS data - provided by the Curitiba City Council. Accessibility is measured dynamically, considering the changing conditions of congestion levels and bus frequencies, along with the daily variation of mobility patterns. The accessibility gap between private and bus modes is estimated, and its daily variation is analyzed regarding its spatial and temporal distribution. This study identifies places with greater public transport supply deficiencies and locations with the greatest needs for public transport improvements, suggesting priority intervention areas to improve the accessibility of the population while promoting a shift toward more sustainable transport modes. The outcomes show the relative advantage of cars versus buses and that a higher portion of Curitiba's population lives in areas with high accessibility gaps.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional Distances and Internal Migration in China: Spatial Patterns, Driving Factors and Regional Heterogeneity","authors":"Jiangbin Yin,&nbsp;Zhipeng Xu,&nbsp;Qianqian Zhang,&nbsp;Zhewen Kang","doi":"10.1007/s12061-025-09636-8","DOIUrl":"10.1007/s12061-025-09636-8","url":null,"abstract":"<div><p>At the global scale, cross-border migration as well as intra-country migration is common. As an individual-level adaptive strategy, migration has an important impact on economic development, socio-political and cultural process. However, scholars have mostly focused on spatial-temporal variations, predictions about migration using models and individuals’ behavior at the micro-level, only limiting researches that analyze migration from a multidimensional perspective. Therefore, in this paper, we focus on China’s floating population, empirically reveal the spatial distribution trend of migration and its influence mechanisms by constructing a multidimensional distances model. Results show that (1) The net migrating population shows a community structure, with low-value area’s agglomeration, and a multi-polar distribution in high-value areas, and some provincial capitals experiencing an obvious ‘population filling’ phenomenon. The migration flows are mainly from prefecture-level cities to capitals of the same province, and from neighboring cities to megacities such as Beijing, Shanghai, Tianjin, etc. (2) After controlling the characteristic factors of the out-migrating place and the destination city, economic distance significantly promotes migration flows, while geographic, administrative and cultural distance hinders migration. (3) In different regions, there are significant differences in the mechanisms by which multidimensional distances affect migration. The study has constructed a relatively complete and unified analytical framework for the impact of multidimensional distances on migration, which can help enrich the study of migration in geography and provide scientific references for relevant policy formulations.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143108317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GeoCrime Analytic Framework (G.C.A.F.): A Comprehensive Framework for Dynamic Spatial Temporal Crime Analysis","authors":"Rojan Roshankar,&nbsp;Mohammad Reza Keyvanpour","doi":"10.1007/s12061-025-09640-y","DOIUrl":"10.1007/s12061-025-09640-y","url":null,"abstract":"<div><p>Crime can drastically alter a neighborhood’s social and economic fabric, creating fear and instability that disrupt communal harmony and daily life. To address the growing impact of crime and the need for efficient analysis and predictions, we introduce the Geographic Crime Analysis Framework (G.C.A.F.). This new framework enhances the capability to analyze and predict urban crime activities through advanced spatial–temporal geographic crime analysis techniques. The G.C.A.F. addresses gaps in existing methods by comprehensively evaluating various approaches, discussing their advantages and disadvantages, and determining their suitability for specific situations. Additionally, it introduces criteria for evaluating the efficiency of different geographic crime prediction methods, aiding in selecting the most appropriate approach for given objectives. The framework concludes with a comparison of the effectiveness of each method in crime prediction and analysis. By implementing the G.C.A.F., law enforcement, and policymakers can more effectively combat crime, thereby improving public safety.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143108332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining Rental Housing Market Segmentation in Chinese Megacities: The Case of Beijing","authors":"Jiajie Liu,&nbsp;Tao Liu,&nbsp;Guangzhong Cao","doi":"10.1007/s12061-025-09637-7","DOIUrl":"10.1007/s12061-025-09637-7","url":null,"abstract":"<div><p>Given the complex urban internal spatial structure, the housing market in megacities is usually not a unified one but consists of multiple local submarkets. Compared to the housing purchase/sales market, rental housing market segmentation is more intricate due to specific rental demands and seasonal market fluctuations. This paper fills the literature gap by detecting general determinants and seasonal variations of rental prices, proposing a conceptual framework, and presenting an effective approach of rental submarkets identification. The global regression model confirmed the general effects of location, job accessibility, amenities and built environment on housing rental prices. A significant seasonal effect was observed in the rental market. The multiscale geographically weighted regression model suggested the spatially varying effects of various hedonic attributes. The local relationship between housing rents and hedonic attributes is determined greatly by the accessibility to the main function of the local area. Rental submarkets were identified based on the dominant factors influencing rents in local areas. The submarkets dominated by centre-location and the submarkets dominated by job accessibility cover most areas. There are few local premiums for amenities and no amenity-dominated submarkets. Finally, the improved approach to identifying urban housing submarkets and the optimisation of zoning housing policies were discussed.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143108250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Critical Shelter Analysis Considering Social Vulnerability and Accessibility: A Case Study of Hurricane Michael Track Uncertainty","authors":"Jieya Yang,&nbsp;Onur Alisan,&nbsp;Linoj Vijayan,&nbsp;Wenrui Huang,&nbsp;Eren Erman Ozguven","doi":"10.1007/s12061-025-09635-9","DOIUrl":"10.1007/s12061-025-09635-9","url":null,"abstract":"<div><p>This research focused on the evaluation of critical shelters in high-risk hurricane-impacted coastal areas of Florida integrating two key indices on evacuation accessibility to emergency facilities and social vulnerability. Prioritizing shelters for those with special needs, such as the elderly, disabled, or economically disadvantaged, was enabled through the consideration of social vulnerability whereas the strategic placement of critical shelters was ensured through accessibility analysis. The case study of Hurricane Michael was utilized to determine critical shelters in three populated regions of northwest Florida: Pensacola, Destin, and Panama City, according to 2018 National Hurricane Center predictions of Hurricane Michael tracks. While the accessibility index was estimated via floating catchment area method. By combining access to hurricane shelters with vulnerability and population data, new weights were derived to identify critical shelters by solving <i>r</i>-interdiction median problem for these areas. Findings provides possible emergency plans based on critical hurricane shelters that not only catered to vulnerable populations but also ensured broader community access. This integrated approach can empower emergency response agencies in optimizing shelter allocation and evacuation strategies, leading to minimized delays and enhanced safety for diverse populations during hurricanes.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143109401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Combinational Effects of Access to Urban Amenities on Housing Prices: A Perspective on the “15-Minute City”","authors":"Peiyu Tian,&nbsp;Weiye Xiao,&nbsp;Feng Yuan","doi":"10.1007/s12061-025-09638-6","DOIUrl":"10.1007/s12061-025-09638-6","url":null,"abstract":"<div><p>Although the “15-min city” concept has gained currency in urban planning, limited attention has been paid to the comprehensive effects of multiple accessible amenities on urban outcomes. This study tried to provide insight into outcomes of the 15-min city by examining the combinational effects of living service amenities on housing prices in Shanghai, China. An enhanced two-step floating catchment area (E2SFCA) method was employed to measure the supply–demand relationship between urban amenities and residences, and a gradient boosting regression tree (GBRT) was applied to identify the combinational effects of urban amenities on housing prices. E2SFCA showed polycentric patterns in the supply–demand relationship between population and amenities, distinguished from traditional measures like distance and density. According to the LightGBM model, we find that accessibility of commerce amenities shows strong positive correlation with housing price, while accessibility of other amenities show nonlinear association with housing price. Further analysis identify the combinational effects of amenities on housing price. Three types of combinational effects have been identified, including positive interaction, incompatible interaction and conditional interaction. For example, there is positive interaction between sports and education amenity that contributed to higher housing prices; culture and education amenities were incompatible to reduce housing prices; The combinational effects between healthcare amenities and commerce amenities on housing prices were only found when accessibility of commerce amenities is low. These findings are helpful in understanding the nexus relationship between urban amenities and housing prices under the concept of the 15-min city.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143109224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond Numbers: Mapping Poverty Disparities in Pakistan through a Spatial Lens","authors":"Syed Hassan Raza,&nbsp;Laiba Khan","doi":"10.1007/s12061-024-09626-2","DOIUrl":"10.1007/s12061-024-09626-2","url":null,"abstract":"<div><p>The pursuit of a comprehensive understanding of poverty has driven the formulation of innovative methodologies, with the multidimensional poverty index (MPI) standing as a prominent metric. But under empirical literature, role of geography concerning poverty remains under-documented; little emphasis has been placed to evaluating the pockets of poverty from geographic lens. This study employs the Alkire and Foster methodology to estimate MPI across diverse districts in Pakistan, utilizing data from the 2019-20 Pakistan Social and Living Standards Measurement (PSLM) survey. To identify spatial clusters Hot Spot Analysis is used along with bivariate mapping analysis, revealing spatial patterns of poverty and nuanced variations in MPI. Findings expose a disconcerting reality: 18% of Pakistan’s population grapples with multidimensional poverty, notably concentrated in Baluchistan and rural areas. Logistic regression analysis and Marginal Effects emphasizes the interplay of household demographics, with impoverished households showing larger dependency ratios and higher child proportions, while non-impoverished counterparts have a higher prevalence of working-age, employed, and educated individuals. The study underscores the critical need to tailor poverty alleviation strategies to diverse socio-economic and geographic contexts for effective policymaking and interventions.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142995724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Downscaling Amphibian Species Richness Maps to Explore the Role of Spatial Scale in Conservation","authors":"Siqing Li,&nbsp;Amaël Borzée,&nbsp;Zhaoning Wu,&nbsp;Yicheng Ren,&nbsp;Jiechen Wang","doi":"10.1007/s12061-024-09634-2","DOIUrl":"10.1007/s12061-024-09634-2","url":null,"abstract":"<div><p>Mapping species richness is a key goal of conservation research, but low data resolution and limited survey data make it challenging to accurately assess distribution patterns. In this study, the random forest (RF) and geographical random forest (GRF) models were used to construct a model of relationships between environmental factors and species richness, and high-resolution environmental data was used to downscale amphibian species distribution maps. The derived multi-scale species richness maps of 10 km, 5 km, and 1 km, revealed that the factors influencing the distribution of species richness and the locations of species richness hotspots vary with spatial scale. GRF outperformed GF in species richness map downscaling, with R² above 97% and RMSE between 0.98 and 1.29. GRF analysis shows that the spatial distribution of environmental factors affecting species distribution varies greatly, and precipitation dominates the distribution of most regions. This study suggests that machine learning algorithms can be used to downscale species richness maps. The multiscale species richness distribution map demonstrates the sensitivity of species richness patterns to spatial scales, which is crucial for macro-ecological analysis and identifying priority conservation areas. This information should be taken into account in future conservation planning.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142995635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}