Geographical Analysis最新文献_第6页

Arriaga Meets Kitagawa. Life Expectancy Decomposition With Population Subgroups Arriaga遇见Kitagawa。人口亚群的预期寿命分解

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2026-02-25 DOI: 10.1111/gean.70033

Timothy Riffe, Rustam Tursun-zade, Sergi Trias Llimós

{"title":"Arriaga Meets Kitagawa. Life Expectancy Decomposition With Population Subgroups","authors":"Timothy Riffe, Rustam Tursun-zade, Sergi Trias Llimós","doi":"10.1111/gean.70033","DOIUrl":"10.1111/gean.70033","url":null,"abstract":"<p>An Arriaga decomposition partitions differences in life expectancy into contributions from mortality rate differences in each age. A Kitagawa decomposition partitions a difference between two weighted means into effects from differences in structure and from differences in each element of the weighted value. Life expectancy differences between like-defined subpopulations can be decomposed using the Arriaga method, or a different suitable decomposition method. If combined (or total) life expectancy is treated as a weighted average of the subpopulations, then the results of subgroup-specific decompositions can substitute the rate component from a Kitagawa decomposition of combined life expectancy. This is valid as long as the relative weight of each subpopulation is part of the initial conditions of the combined lifetable, and group prevalence in later ages is determined only by mortality. The composition component of the same Kitagawa decomposition gives the effect of differing subgroup composition on total life expectancy differences. Notable properties of the method include: (i) it accommodates any number of subpopulations, (ii) it easily incorporates cause-of-death information, and (iii) composition is considered only in the initial conditions. We apply the method to Spanish cause- and education-specific data. This method can further disentangle the effects of mortality and composition differences, helping to explain or clarify paradoxes and contemporary or forthcoming life expectancy changes as partly driven by shifts in cohort composition. We give both R code and spreadsheet implementations of the method.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 2","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569247","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}

引用次数: 0

The Nonlinear Impact of Migrants on Regional Carbon Emissions in China: Evidence From Spatial Econometric Models 流动人口对中国区域碳排放的非线性影响：来自空间计量模型的证据

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2026-02-22 DOI: 10.1111/gean.70032

Nina Zhu, Yanjiao Song, Pengxin Chen

{"title":"The Nonlinear Impact of Migrants on Regional Carbon Emissions in China: Evidence From Spatial Econometric Models","authors":"Nina Zhu, Yanjiao Song, Pengxin Chen","doi":"10.1111/gean.70032","DOIUrl":"10.1111/gean.70032","url":null,"abstract":"<div>\u0000 \u0000 <p>Amid China's accelerating urbanization, the impact of migrants on carbon emissions has emerged as a critical yet underexplored dimension of environmental challenges. Drawing on data from 275 prefecture-level cities between 2010 and 2017, this study employs spatial econometric models to investigate the complex relationship between migrants and carbon emissions in China. The results reveal significant positive spatial autocorrelation in both carbon emissions and migrants. Over time, the autocorrelation of emissions has intensified, whereas that of migrants has gradually weakened. High-high clusters of both emissions and migrants are predominantly concentrated in the eastern coastal regions. Empirically, migrants exhibit an inverted U-shaped relationship with carbon emissions, with the optimization of industrial structure exerting a significant mediating effect. The analysis also highlights substantial interregional spillover effects, where the impact of migrants extends beyond city boundaries. Furthermore, environmental regulation is identified as a key factor that helps reduce carbon emissions. Heterogeneity analysis shows that migrants with higher educational attainment tend to generate lower carbon emissions, whereas older migrants are associated with higher carbon emissions. This study provides new theoretical perspectives and policy insights for understanding the environmental footprint of migrants on carbon emissions.</p>\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 2","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568070","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}

引用次数: 0

The Nonlinear Impact of Migrants on Regional Carbon Emissions in China: Evidence From Spatial Econometric Models 流动人口对中国区域碳排放的非线性影响：来自空间计量模型的证据

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2026-02-22 DOI: 10.1111/gean.70032

Nina Zhu, Yanjiao Song, Pengxin Chen

{"title":"The Nonlinear Impact of Migrants on Regional Carbon Emissions in China: Evidence From Spatial Econometric Models","authors":"Nina Zhu, Yanjiao Song, Pengxin Chen","doi":"10.1111/gean.70032","DOIUrl":"https://doi.org/10.1111/gean.70032","url":null,"abstract":"<div>\u0000 \u0000 <p>Amid China's accelerating urbanization, the impact of migrants on carbon emissions has emerged as a critical yet underexplored dimension of environmental challenges. Drawing on data from 275 prefecture-level cities between 2010 and 2017, this study employs spatial econometric models to investigate the complex relationship between migrants and carbon emissions in China. The results reveal significant positive spatial autocorrelation in both carbon emissions and migrants. Over time, the autocorrelation of emissions has intensified, whereas that of migrants has gradually weakened. High-high clusters of both emissions and migrants are predominantly concentrated in the eastern coastal regions. Empirically, migrants exhibit an inverted U-shaped relationship with carbon emissions, with the optimization of industrial structure exerting a significant mediating effect. The analysis also highlights substantial interregional spillover effects, where the impact of migrants extends beyond city boundaries. Furthermore, environmental regulation is identified as a key factor that helps reduce carbon emissions. Heterogeneity analysis shows that migrants with higher educational attainment tend to generate lower carbon emissions, whereas older migrants are associated with higher carbon emissions. This study provides new theoretical perspectives and policy insights for understanding the environmental footprint of migrants on carbon emissions.</p>\u0000 </div>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 2","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568100","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}

引用次数: 0

Transport Connectivity and Urban Development: The Case of Africa (1880–2020) 交通连通性与城市发展：以非洲为例（1880-2020）

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2026-01-09 DOI: 10.1111/gean.70028

Bárbara Polo-Martín, Daniel Castillo-Hidalgo, César Ducruet

{"title":"Transport Connectivity and Urban Development: The Case of Africa (1880–2020)","authors":"Bárbara Polo-Martín, Daniel Castillo-Hidalgo, César Ducruet","doi":"10.1111/gean.70028","DOIUrl":"https://doi.org/10.1111/gean.70028","url":null,"abstract":"<p>This paper investigates the interplay between population dynamics and transport connectivity in African municipalities from 1880 to 2020. Using an original historical dataset spanning African countries, we examine how proximity to railways and ports has shaped population dynamics over time. Through the application of Granger causality and Vector Autoregression (VAR) models—accounting for structural breaks and regime changes—we demonstrate that transport infrastructure development has a statistically significant and directional influence on urban population growth. Our findings reveal that city size and growth are not randomly distributed across space; rather, they are systematically linked to historical patterns of transport connectivity. In particular, the largest and fastest-growing cities consistently correspond to strategic nodes at the intersection of railway and maritime networks. These results, reinforced by hierarchical clustering and regime analysis, highlight the enduring impact of colonial infrastructure and institutional path dependence. The study also points to broader implications for contemporary urban planning in the context of containerization and modern global trade flows.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145964075","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}

引用次数: 0

SCADDA: Spatiotemporal Cluster Analysis With Density-Based Distance Augmentation and Its Application to Fire Carbon Emissions SCADDA：基于密度的距离增强时空聚类分析及其在火灾碳排放中的应用

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2025-12-23 DOI: 10.1111/gean.70030

Ben Moews, Antonia Gieschen

{"title":"SCADDA: Spatiotemporal Cluster Analysis With Density-Based Distance Augmentation and Its Application to Fire Carbon Emissions","authors":"Ben Moews, Antonia Gieschen","doi":"10.1111/gean.70030","DOIUrl":"https://doi.org/10.1111/gean.70030","url":null,"abstract":"<p>Spatiotemporal clustering occupies an established role in various fields dealing with geospatial analysis, spanning from healthcare analysis to environmental science. One major challenge is application in which cluster assignments are dependent on local densities, meaning that higher-density areas should be treated more strictly for spatial clustering and vice versa. We describe and implement an extended method that covers continuous and adaptive distance rescaling based on kernel density estimates and the orthodromic metric, as well as the distance between time series via dynamic time warping (DTW). In doing so, we provide the wider research community, as well as practitioners, with a way to solve an existing challenge as well as an easy-to-handle and robust open-source software tool. The resulting implementation is highly customizable to suit different application cases, and we verify and test the latter on both an idealized scenario and the recreation of prior work on broadband antibiotics prescriptions in Scotland to demonstrate well-behaved comparative performance. Following this, we apply our approach to fire emissions in Sub-Saharan Africa using data from Earth-observing satellites, and show our implementation's ability to uncover seasonality shifts in carbon emissions of subgroups as a result of time series-driven cluster splits.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145825199","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}

引用次数: 0

An Overview of Tourism on Dal Lake: A Spatial Analysis 达利湖旅游发展概况：空间分析

3区地球科学

Geographical Analysis Pub Date : 2025-11-29 DOI: 10.53989/bu.ga.v14i1.24.176

Supratim Karmakar, Dhruba Jyoti Mudoi, Subrata Dey

引用次数: 0

Smoothing the Edges: Reconceptualizing Space and Dealing With Modifiable Areal Unit Problems in (Un)Related Variety Research 平滑边缘：空间概念的重构与（非）相关品种研究中可修改面积单位问题的处理

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2025-11-07 DOI: 10.1111/gean.70025

Mi Hyun Seong, Milad Abbasiharofteh, Daniella Vos, Sierdjan Koster

{"title":"Smoothing the Edges: Reconceptualizing Space and Dealing With Modifiable Areal Unit Problems in (Un)Related Variety Research","authors":"Mi Hyun Seong, Milad Abbasiharofteh, Daniella Vos, Sierdjan Koster","doi":"10.1111/gean.70025","DOIUrl":"https://doi.org/10.1111/gean.70025","url":null,"abstract":"<p>Related variety studies in Economic Geography reveal regional diversification mechanisms for regional development, but often overlook geographic fundamentals. By relying on administrative units, the studies may fail to account for spatial continuity and interdependence, which can lead to Modifiable Areal Unit Problems. In this regard, this article introduces an alternative method ‘smoothing the edges’ as proof of concept to strengthen spatial conceptualization. Instead of using administrative units, we construct high-resolution grid cells and define Local Economic Environments (LEEs) around them to calculate economic factors. LEEs capture the conditioning economic context to which each grid cell is exposed. We compare Ordinary Least Squares regression outcomes across three LEE scales, equivalent to NUTS 2, NUTS 3, and municipality levels, and examine how (un)related variety effects behave across scales under the new conceptual framework. We apply two stylized facts from the literature: (Un)Related variety associates with (1) industrial specialization, and with (2) employment growth. A case study with Dutch establishment microdata LISA reveals that effects of (un)related variety are sensitive to scale, particularly in employment growth analysis. These findings highlight the importance of understanding contextual settings, which is critical in informed policy making.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145779538","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}

引用次数: 0

Feedback Loops in Rural Depopulation 农村人口减少的反馈循环

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2025-11-07 DOI: 10.1111/gean.70027

Peter Højrup Søder

引用次数: 0

A GIS-Based Framework for Modeling Hospital Accessibility in Spain Using Open and Collaborative Data 使用开放和协作数据对西班牙医院可达性建模的基于gis的框架

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2025-11-06 DOI: 10.1111/gean.70026

Virgilio Pérez

{"title":"A GIS-Based Framework for Modeling Hospital Accessibility in Spain Using Open and Collaborative Data","authors":"Virgilio Pérez","doi":"10.1111/gean.70026","DOIUrl":"https://doi.org/10.1111/gean.70026","url":null,"abstract":"<p>This study analyzes hospital accessibility in Spain at the census section level from 2010 to 2024. Using open data and open-source tools, a replicable geospatial method was developed to estimate travel times and distances to the nearest hospital by car and on foot. Over 500,000 origin–destination pairs were analyzed, combining census centroids, OpenStreetMap hospital data, and road networks. Results show stark territorial disparities, especially in rural and inland areas, where travel times often exceed 30 min and sometimes surpass the “golden hour” critical for emergency care. While over 74% of the population lived within 15 min of a hospital in 2024, around 783,000 people still faced travel times over 1 hour. Accessibility has improved over time, with the share of critically underserved residents falling from 1.91% in 2010 to 1.62% in 2024. This reflects the possible impact of healthcare planning and infrastructure investments. The study provides a scalable, adaptable framework for analyzing access to essential services in other contexts. The resulting open dataset supports further research on spatial healthcare inequalities and informs data-driven health and territorial policy decisions.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"58 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145824571","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}

引用次数: 0

How Can Clusters of Population Trajectories be Identified? Comparing the Potential of Dynamic Time Warping and Sequence Analysis 如何识别人口轨迹簇？动态时间翘曲和序列分析潜力的比较

IF 4.3 3区地球科学

Geographical Analysis Pub Date : 2025-09-23 DOI: 10.1111/gean.70024

Jonathan Gescher

{"title":"How Can Clusters of Population Trajectories be Identified? Comparing the Potential of Dynamic Time Warping and Sequence Analysis","authors":"Jonathan Gescher","doi":"10.1111/gean.70024","DOIUrl":"https://doi.org/10.1111/gean.70024","url":null,"abstract":"<p>Reducing complexity while retaining the maximum amount of information is a key challenge for population analysis. Solving this challenge becomes a necessity when looking at numerous areas over extended periods, which defy manual pattern recognition efforts. This paper introduces Dynamic Time Warping (DTW) as a novel method for population time series clustering, capable of creating distinct, well-separated groups for process-centered population analysis. DTW is benchmarked against a Sequence Analysis model and established typologies based on size, location or density with population data from nearly 3000 towns in Germany for the period 2001 to 2022. The results indicate that DTW consistently outperforms the Sequence Analysis model across various cluster quality measures, producing better-separated typologies of population trajectories. Both models are highly superior to the established typologies. The results highlight the significant advantages of using DTW for clustering continuous time series data, making it well-suited for identifying typologies of municipal population trends.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"57 4","pages":"809-829"},"PeriodicalIF":4.3,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273010","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}

引用次数: 0