Ryan Turner, Carl Higgs, Vuokko Heikinheimo, Ruth Hunter, Júlio Celso Borello Vargas, Shiqin Liu, Eugen Resendiz, Geoff Boeing, Deepti Adlakha, Rossano Schifanella, Giovani Longo Rosa, Daria Pugacheva, Ruoyu Chen, Mahtab Baghaie Poor, Javier Molina-García, Ana Queralt, Anna Puig-Ribera, Pau Serra del Pozo, Case Garza, Joanna Valson, Deborah Salvo, Ester Cerin, Erica Hinckson, Melanie Lowe
{"title":"Internationally Validated Open Access Indicators of Large Public Urban Green Space for Healthy and Sustainable Cities","authors":"Ryan Turner, Carl Higgs, Vuokko Heikinheimo, Ruth Hunter, Júlio Celso Borello Vargas, Shiqin Liu, Eugen Resendiz, Geoff Boeing, Deepti Adlakha, Rossano Schifanella, Giovani Longo Rosa, Daria Pugacheva, Ruoyu Chen, Mahtab Baghaie Poor, Javier Molina-García, Ana Queralt, Anna Puig-Ribera, Pau Serra del Pozo, Case Garza, Joanna Valson, Deborah Salvo, Ester Cerin, Erica Hinckson, Melanie Lowe","doi":"10.1111/gean.70023","DOIUrl":"https://doi.org/10.1111/gean.70023","url":null,"abstract":"<p>Large public urban green spaces (LPUGS) provide multiple health and environmental co-benefits by mitigating urban heat, improving air quality and biodiversity, and promoting physical activity, social interactions, and mental wellbeing. There is a lack of accessible, evidence-informed, and internationally validated LPUGS indicators to assist with benchmarking and monitoring progress toward healthy and sustainable cities globally. This study developed and validated internationally applicable spatial indicators of LPUGS availability and accessibility that are directly relevant to health and sustainability outcomes. For 13 cities across 10 middle- to high-income countries, we identified LPUGS ≥ 1 ha by fusing OpenStreetMap and satellite-derived Normalized Difference Vegetation Index data, and estimated residents' access within 500 m pedestrian network distance. We conducted a two-step validation process with local collaborators in each city. Our indicator methods identified LPUGS with greater than 80% accuracy for 12 of the 13 cities, and comparisons against official local reference data for four cities further demonstrated validity. While some open data limitations were identified, the indicators address critical gaps in existing methods by enabling standardized and comparable measurement of LPUGS in diverse cities internationally. Our customizable open-source global indicator tools can inform evidence-based green space planning for urban health and sustainability.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"793-808"},"PeriodicalIF":4.3,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alan Ricardo da Silva, Gabriela Carneiro de Almeida
{"title":"Using the Kriging Technique for Prediction of Non-Continuous Phenomena in Unmeasured Locations: Dispelling the Myth","authors":"Alan Ricardo da Silva, Gabriela Carneiro de Almeida","doi":"10.1111/gean.70022","DOIUrl":"https://doi.org/10.1111/gean.70022","url":null,"abstract":"<div>\u0000 \u0000 <p>The Kriging technique was designed to model continuous phenomena such as temperature, mineral deposits, sound, etc. However, it is often used in non-continuous phenomena, such as predicting road traffic, modeling the number of trips made on public transit, predicting critical crime locations, etc., which can result in the violation of established assumptions. In this way, recurrent confusion lies in the equivocal association between the level of measurement of a continuous random variable and the erroneously assumed continuous nature of the phenomenon under study. Thus, this study aims to demonstrate how problematic using Kriging is in non-continuous phenomena, mainly in transportation studies, and to present the Geographically Weighted Regression (GWR) as a robust competitor to this task. The results of two case studies using the variables “Households Income” and “Car Trip Rate” in the city of São Paulo, Brazil, showed some problems with the Kriging technique when there are few sampled points and very similar results between Kriging and GWR when there are many sampled points, being the latter much simpler to do.</p>\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"773-792"},"PeriodicalIF":4.3,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271974","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}
{"title":"Geographically Weighted Cronbach's Alpha (GWalpha): An Exploratory Local Measure of Reliability for Scale Construction","authors":"Sui Zhang, Ziqi Li","doi":"10.1111/gean.70021","DOIUrl":"https://doi.org/10.1111/gean.70021","url":null,"abstract":"<p>Scales, as survey instruments, are crucial for investigating people's attitudes and behaviors in social science research. Cronbach's alpha is the most frequently used measure of internal consistency reliability for multi-item survey scales. Affected by the spatial context of respondents' locations, the reliability of responses to a scale may vary geographically, whereas classical Cronbach's Alpha assumes that reliability is stationary across all samples being estimated. In this article, a local version of Cronbach's alpha, Geographically Weighted Cronbach's Alpha (GWalpha), is developed to explore how the reliability of a measure varies spatially. Issues concerning the bandwidth, inference, and interpretation are also discussed. We demonstrate the utility of GWalpha on a synthetic dataset with known parameters and an empirical dataset. Results suggest that GWalpha can effectively reveal and measure how spatial context influences survey reliability, which has been largely overlooked in the existing literature.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"758-772"},"PeriodicalIF":4.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sergio J. Rey, Elijah Knaap, Alejandra Cabral, Jennifer Syvertsen
{"title":"Exploring Space-Time Interactions in Fatal Opioid Overdoses","authors":"Sergio J. Rey, Elijah Knaap, Alejandra Cabral, Jennifer Syvertsen","doi":"10.1111/gean.70019","DOIUrl":"https://doi.org/10.1111/gean.70019","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates fatal opioid overdoses in Riverside County, California, between January 2020 and March 2023, employing advanced spatial-temporal analysis methods to uncover significant clusters and their underlying contexts. By integrating global and local Knox tests, the research identifies both broad trends and specific hotspots of fatal overdoses. The findings reveal substantial spatial disparities, with higher overdose rates in rural areas and neighborhoods characterized by lower socioeconomic status and larger Hispanic populations. Despite a lower overall overdose risk among Hispanics, their neighborhoods exhibit a higher occurrence of fatal overdoses, highlighting complex interactions between individual and environmental factors. These insights underscore the need for targeted, contextually informed public health interventions and policies to effectively address the opioid crisis.</p>\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"744-757"},"PeriodicalIF":4.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272990","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}
Anna Tort-Carrera, J. Paul Elhorst, Govert E. Bijwaard
{"title":"Determinants of Children's Mental Health: Relative Contributions When Accounting for Unobserved Heterogeneity, Endogeneity and Self-Selection","authors":"Anna Tort-Carrera, J. Paul Elhorst, Govert E. Bijwaard","doi":"10.1111/gean.70020","DOIUrl":"https://doi.org/10.1111/gean.70020","url":null,"abstract":"<p>While the neighborhood has been shown to contribute to children's mental health, the extent of this contribution is not yet sufficiently clear due to several methodological challenges. We investigate the relative contribution– sign, magnitude, and significance– of six neighborhood characteristics associated with children's mental health when accounting for unobserved heterogeneity, endogeneity, and self-selection in neighborhoods of different socio-economic status. Using a correlated random effects model in space and time and two waves of data extracted from the Lifelines Cohort Study of children between 7 and 15 years of age in northern Netherlands, we analyze both internalizing and externalizing behavior. Besides the importance of the environment for healthy child development, our empirical findings show that the magnitude and significance of neighborhood characteristics increase significantly, especially when we control for endogeneity of maternal family characteristics. Controlling for self-selection again reduces the magnitude slightly, but only for externalizing behavior. Controlling for unobserved child-invariant factors is also found to be significant, but not for unobserved heterogeneity.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"732-743"},"PeriodicalIF":4.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Optimization Framework for Spatial Component Analysis and Its Extension to Two-Scale Discriminant Function Analysis","authors":"Jie Lin","doi":"10.1111/gean.70018","DOIUrl":"https://doi.org/10.1111/gean.70018","url":null,"abstract":"<div>\u0000 \u0000 <p>This study formulates spatial component analysis as a ratio-of-trace optimization problem. Under this framework, the one-scale spatial component analysis is extended to a two-scale analysis, which is also essentially an adaptation of linear discriminant analysis (LDA). It does so by including spatial effects with respect to spatial autocorrelation at either one or both observation scales. The spatialized LDA (SLDA) seeks the projection that minimizes the similarity between neighboring regions and maximizes the similarity within regions or neighboring units within regions. Regionalization results for the AZP and Max-<i>p</i> methods are evaluated for three different heuristic algorithms. The evaluation is designed specifically to rank the ability of regionalization methods to separate classified neighbor regions in a one-dimensional subspace, which is constructed by the SLDA. The process is mainly based on the first pseudo eigenvalue of the SLDA.</p>\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"722-731"},"PeriodicalIF":4.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271995","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}
{"title":"The Convergence Process in Romania: A Multidimensional Approach","authors":"József Benedek, Ibolya Török, Valér Veres","doi":"10.1111/gean.70017","DOIUrl":"https://doi.org/10.1111/gean.70017","url":null,"abstract":"<p>The main objective of the study is to analyze the sub-national social and economic convergence in a special spatial setting of Romania, characterized by the double process of national level economic catch up to the European level and the unprecedented deepening of the sub-national, inter-regional inequalities. The main contribution of the article consists in the determination of four multi-dimensional convergence clubs at NUTS 3 level, with specific growth trajectories and characteristics. A secondary contribution is related to the multi-dimensionality of development, revealing the existence of the contradictory processes of economic divergence and social convergence among the Romanian regions.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"700-721"},"PeriodicalIF":4.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatial Optimization of the Multiple Coverage Mesh Network Problem for Multifunctional Smart Poles","authors":"Sejin Park, Gunhak Lee","doi":"10.1111/gean.70015","DOIUrl":"https://doi.org/10.1111/gean.70015","url":null,"abstract":"<p>Major metropolises worldwide are adopting the smart city approach as an aspect of their strategies to address urban challenges. This approach leverages integrated information and communications technology (ICT) to transform urban environments into more efficient and intelligent spaces. A smart pole combines varied services such as CCTV, environmental sensors, and public Wi-Fi into a single infrastructure, collecting data via the Internet of Things (IoT) and transmitting them to an integrated platform for urban management and public service delivery. Given network connectivity and budget constraints, such smart poles must be strategically deployed. However, the absence of specific criteria for establishment causes inefficient installations, contrary to their intended aims to optimize space and resources. This study integrates the optimal deployment of smart poles with an effective design for wireless mesh networking. Specifically, we propose a multiple coverage mesh network problem (MC-MNP) to enhance the placement of smart poles with multi-sensors by improving public service coverage and more efficiently using urban space. The findings of this study offer useful guidelines for optimizing the deployment of multifunctional smart poles and can ultimately deliver a viable implementation methodology for smart cities.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"686-699"},"PeriodicalIF":4.3,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Causal Inference With Spatial Econometric Models: Challenges and Applications for Epidemiologic Research","authors":"Konstantinos Christopoulos","doi":"10.1111/gean.70010","DOIUrl":"https://doi.org/10.1111/gean.70010","url":null,"abstract":"<p>Spatial econometric models have become very popular in recent years and have started to make their appearance in geospatial studies of health outcomes. Although explicit or implicit causal claims are widely made using these models, this article demonstrates with the use of causal graphs why causal vocabulary should be avoided. The article first introduces spatial causal inference from an epidemiologic perspective and then presents the challenges in the application of these specifications using this framework. Further implications and modeling options are discussed.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"676-685"},"PeriodicalIF":4.3,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eleojo Oluwaseun Abubakar, Andreas Grivas, Bruce Guthrie, Chunyu Zheng, Claire Grover, Clare Llewellyn, Clare MacRae, Richard Tobin, Beatrice Alex, Chris Dibben, Jamie Pearce, Alan Marshall
{"title":"Can Topic Modeling of Local Newspaper Texts Enhance Understanding of Neighborhood Effects on Health?","authors":"Eleojo Oluwaseun Abubakar, Andreas Grivas, Bruce Guthrie, Chunyu Zheng, Claire Grover, Clare Llewellyn, Clare MacRae, Richard Tobin, Beatrice Alex, Chris Dibben, Jamie Pearce, Alan Marshall","doi":"10.1111/gean.70016","DOIUrl":"https://doi.org/10.1111/gean.70016","url":null,"abstract":"<p>Social attributes of neighborhoods, like heritage, and low-level social disorder, are not reflected in official metrics such as deprivation indices. However, research suggests these attributes are important for understanding spatial variations in health and social outcomes. This exploratory study investigated whether recurring themes in local newspaper articles capture meaningful social characteristics that help explain neighborhood health resilience, defined as a dearth of illness after adjusting for deprivation. Topic modeling of geo-referenced texts identified and quantified 55 themes of commonly occurring words in Edinburgh, which capture salient neighborhood attributes. Correlations between the themes and domains of the Scottish Index of Multiple Deprivation (SIMD) were weak, suggesting that newspaper themes captured characteristics beyond those in the SIMD. Reassuringly, expected correlations were observed between crime metrics from newspapers and the SIMD domains. Stepwise regression modeling revealed theoretically plausible themes associated with neighborhood health resilience/vulnerability. Themes on heritage and community sports identity were positively associated with health resilience, whereas low-level social disorder (e.g., littering, antisocial behavior) and “local politics” were negatively associated. This study underscores the potential of using area-based topic modeling of newspaper texts to capture neighborhood aspects neglected in official statistics but could further explain spatial variations in neighborhood health outcomes.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"662-675"},"PeriodicalIF":4.3,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}