Geographical Analysis最新文献_第8页

The Spatiotemporal Evolution of Sydney's Tram Network Using Network Econometrics 基于网络计量经济学的悉尼有轨电车网络时空演化研究

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-07-17 DOI: 10.1111/gean.12341

Yingshuo Wang, Bahman Lahoorpoor, David M. Levinson

{"title":"The Spatiotemporal Evolution of Sydney's Tram Network Using Network Econometrics","authors":"Yingshuo Wang, Bahman Lahoorpoor, David M. Levinson","doi":"10.1111/gean.12341","DOIUrl":"10.1111/gean.12341","url":null,"abstract":"This paper examines the evolution of Sydney trams using network econometrics approaches. Network econometrics extends spatial econometrics by developing weight matrices based on the physical structure of the network, allowing for competing and complementary elements to have distinct effects. This research establishes a digitized database of Sydney historical tramway network, providing a complete set of geo-referenced data of the opening and closing year and frequencies by time of day for every line. An autoregressive distributed lag model is specified and reveals that the combination of correlation strength and magnitude of lagged flow change on correlated links is a significant predictor of future tram service. The results indicate that complementary and competitive links play distinct roles in shaping the network structure. A link is more likely to undergo the same structural change highly complementary (upstream or downstream) links underwent previously, where the influence is measured by a combination of correlation strength and link importance, reflected by historical service levels.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 3","pages":"367-383"},"PeriodicalIF":3.6,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12341","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47263754","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 Examination of the Stochastic Distribution of Spatial Accessibility to Intensive Care Unit Beds during the COVID-19 Pandemic: A Case Study of the Greater Houston Area of Texas COVID-19大流行期间重症监护病房床位空间可达性随机分布研究——以德克萨斯州大休斯顿地区为例

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-07-09 DOI: 10.1111/gean.12340

Jinwoo Park, Daniel W. Goldberg

{"title":"An Examination of the Stochastic Distribution of Spatial Accessibility to Intensive Care Unit Beds during the COVID-19 Pandemic: A Case Study of the Greater Houston Area of Texas","authors":"Jinwoo Park, Daniel W. Goldberg","doi":"10.1111/gean.12340","DOIUrl":"10.1111/gean.12340","url":null,"abstract":"Sufficient and reliable health care access is necessary for people to be able to maintain good health. Hence, investigating the uncertainty embedded in the temporal changes of inputs would be beneficial for understanding their impact on spatial accessibility. However, previous studies are limited to implementing only the uncertainty of mobility, while health care resource availability is a significant concern during the coronavirus disease (COVID-19) pandemic. Our study examined the stochastic distribution of spatial accessibility under the uncertainties underlying the availability of intensive care unit (ICU) beds and ease of mobility in the Greater Houston area of Texas. Based on the randomized supply and mobility from their historical changes, we employed Monte Carlo simulation to measure ICU bed accessibility with an enhanced two-step floating catchment area (E2SFCA) method. We then conducted hierarchical clustering to classify regions of adequate (sufficient and reliable) accessibility and inadequate (insufficient and unreliable) accessibility. Lastly, we investigated the relationship between the accessibility measures and the case fatality ratio of COVID-19. As result, locations of sufficient access also had reliable accessibility; downtown and outer counties, respectively, had adequate and inadequate accessibility. We also raised the possibility that inadequate health care accessibility may cause higher COVID-19 fatality ratios.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 3","pages":"384-398"},"PeriodicalIF":3.6,"publicationDate":"2022-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9350384/pdf/GEAN-9999-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40679752","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: 5

A Framework for Inserting Visually Supported Inferences into Geographical Analysis Workflow: Application to Road Safety Research 在地理分析工作流程中插入视觉支持推理的框架：在道路安全研究中的应用

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-07-06 DOI: 10.1111/gean.12338

Roger Beecham, Robin Lovelace

{"title":"A Framework for Inserting Visually Supported Inferences into Geographical Analysis Workflow: Application to Road Safety Research","authors":"Roger Beecham, Robin Lovelace","doi":"10.1111/gean.12338","DOIUrl":"https://doi.org/10.1111/gean.12338","url":null,"abstract":"Road safety research is a data-rich field with large social impacts. Like in medical research, the ambition is to build knowledge around risk factors that can save lives. Unlike medical research, road safety research generates empirical findings from messy observational datasets. Records of road crashes contain numerous intersecting categorical variables, dominating patterns that are complicated by confounding and, when conditioning on data to make inferences net of this, observed effects that are subject to uncertainty due to diminishing sample sizes. We demonstrate how visual data analysis approaches can inject rigor into exploratory analysis of such datasets. A framework is presented whereby graphics are used to expose, model and evaluate spatial patterns in observational data, as well as protect against false discovery. Evidence for the framework is presented through an applied data analysis of national crash patterns recorded in STATS19, the main source of road crash information in Great Britain. Our framework moves beyond typical depictions of exploratory data analysis and transfers to complex data analysis decision spaces characteristic of modern geographical analysis.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 3","pages":"345-366"},"PeriodicalIF":3.6,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12338","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50122658","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

A Multi-objective Optimization Approach for Disaggregating Employment Data 就业数据分解的多目标优化方法

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-07-01 DOI: 10.1111/gean.12328

Chantel Ludick, Quintin van Heerden

{"title":"A Multi-objective Optimization Approach for Disaggregating Employment Data","authors":"Chantel Ludick, Quintin van Heerden","doi":"10.1111/gean.12328","DOIUrl":"10.1111/gean.12328","url":null,"abstract":"In many countries, including South Africa, data on employment is rarely available on a downscaled level, such as building level, and is only available on less detailed levels, such as municipal level. The aim of this research was to develop a methodology to disaggregate the employment data that is available at an aggregate level to a disaggregate, detailed building level. To achieve this, the methodology consisted of two parts. First, a method was established that could be used to prepare a base data set to be used for disaggregating the employment data. Second, a multiobjective optimization approach was used to allocate the number of employment opportunities within a municipality to building level. The algorithm was developed using an Evolutionary Algorithm framework and applied to a case study in a metropolitan municipality in South Africa. The results showed favorable use of multiobjective optimization to disaggregate employment data to building level. By enhancing the detail of employment data, planners, policy makers, modelers and other users of such data can benefit from understanding employment patterns at a much more detailed level and making improved decisions based on disaggregated data and models.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 2","pages":"300-324"},"PeriodicalIF":3.6,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12328","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48521423","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

Open Source Software for Spatial Data Science 空间数据科学的开源软件

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-06-28 DOI: 10.1111/gean.12339

Luc Anselin, Sergio J. Rey

引用次数: 7

gwverse: A Template for a New Generic Geographically Weighted R Package gwverse:一个新的通用地理加权R包模板

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-06-28 DOI: 10.1111/gean.12337

Alexis Comber, Martin Callaghan, Paul Harris, Binbin Lu, Nick Malleson, Chris Brunsdon

{"title":"gwverse: A Template for a New Generic Geographically Weighted R Package","authors":"Alexis Comber, Martin Callaghan, Paul Harris, Binbin Lu, Nick Malleson, Chris Brunsdon","doi":"10.1111/gean.12337","DOIUrl":"10.1111/gean.12337","url":null,"abstract":"GWR is a popular approach for investigating the spatial variation in relationships between response and predictor variables, and critically for investigating and understanding process spatial heterogeneity. The geographically weighted (GW) framework is increasingly used to accommodate different types of models and analyses, reflecting a wider desire to explore spatial variation in model parameters and outputs. However, the growth in the use of GWR and different GW models has only been partially supported by package development in both R and Python, the major coding environments for spatial analysis. The result is that refinements have been inconsistently included within GWR and GW functions in any given package. This paper outlines the structure of a new gwverse\u0000package, that may over time replace GWmodel, that takes advantage of recent developments in the composition of complex, integrated packages. It conceptualizes gwverse as having a modular structure, that separates core GW functionality and applications such as GWR. It adopts a function factory approach, in which bespoke functions are created and returned to the user based on user-defined parameters. The paper introduces two demonstrator modules that can be used to undertake GWR and identifies a number of key considerations and next steps.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"54 3","pages":"685-709"},"PeriodicalIF":3.6,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12337","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46767628","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: 2

Effects of Vaccination and the Spatio-Temporal Diffusion of Covid-19 Incidence in Turkey 疫苗接种对土耳其Covid-19发病率时空扩散的影响

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-06-04 DOI: 10.1111/gean.12335

Firat Bilgel, Burhan Can Karahasan

{"title":"Effects of Vaccination and the Spatio-Temporal Diffusion of Covid-19 Incidence in Turkey","authors":"Firat Bilgel, Burhan Can Karahasan","doi":"10.1111/gean.12335","DOIUrl":"10.1111/gean.12335","url":null,"abstract":"This study assesses the spatio-temporal impact of vaccination efforts on Covid-19 incidence growth in Turkey. Incorporating geographical features of SARS-CoV-2 transmission, we adopt a spatial Susceptible–Infected–Recovered (SIR) model that serves as a guide of our empirical specification. Using provincial weekly panel data, we estimate a dynamic spatial autoregressive (SAR) model to elucidate the short- and the long-run impact of vaccination on Covid-19 incidence growth after controlling for temporal and spatio-temporal diffusion, testing capacity, social distancing behavior and unobserved space-varying confounders. Results show that vaccination growth reduces Covid-19 incidence growth rate directly and indirectly by creating a positive externality over space. The significant association between vaccination and Covid-19 incidence is robust to a host of spatial weight matrix specifications. Conspicuous spatial and temporal diffusion effects of Covid-19 incidence growth were found across all specifications: the former being a severer threat to the containment of the pandemic than the latter.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 3","pages":"399-426"},"PeriodicalIF":3.6,"publicationDate":"2022-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467643/pdf/GEAN-9999-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40366127","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

Big Code 大代码

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-06-04 DOI: 10.1111/gean.12330

Sergio J. Rey

引用次数: 3

The Spatial Association of Demographic and Population Health Characteristics with COVID-19 Prevalence Across Districts in India 人口和人口健康特征与印度各区COVID-19流行的空间关系

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-05-30 DOI: 10.1111/gean.12336

Sarbeswar Praharaj, Harsimran Kaur, Elizabeth Wentz

{"title":"The Spatial Association of Demographic and Population Health Characteristics with COVID-19 Prevalence Across Districts in India","authors":"Sarbeswar Praharaj, Harsimran Kaur, Elizabeth Wentz","doi":"10.1111/gean.12336","DOIUrl":"10.1111/gean.12336","url":null,"abstract":"In less-developed countries, the lack of granular data limits the researcher's ability to study the spatial interaction of different factors on the COVID-19 pandemic. This study designs a novel database to examine the spatial effects of demographic and population health factors on COVID-19 prevalence across 640 districts in India. The goal is to provide a robust understanding of how spatial associations and the interconnections between places influence disease spread. In addition to the linear Ordinary Least Square regression model, three spatial regression models—Spatial Lag Model, Spatial Error Model, and Geographically Weighted Regression are employed to study and compare the variables explanatory power in shaping geographic variations in the COVID-19 prevalence. We found that the local GWR model is more robust and effective at predicting spatial relationships. The findings indicate that among the demographic factors, a high share of the population living in slums is positively associated with a higher incidence of COVID-19 across districts. The spatial variations in COVID-19 deaths were explained by obesity and high blood sugar, indicating a strong association between pre-existing health conditions and COVID-19 fatalities. The study brings forth the critical factors that expose the poor and vulnerable populations to severe public health risks and highlight the application of geographical analysis vis-a-vis spatial regression models to help explain those associations.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 3","pages":"427-449"},"PeriodicalIF":3.6,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348190/pdf/GEAN-9999-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40679753","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: 3

A Long Way to Complexity: Nonlinear “Growth Stages” and Spatially Uncoordinated Settlement Expansion in a Compact City (Athens, Greece) 走向复杂的漫漫长路:紧凑型城市的非线性“成长阶段”与空间不协调的聚落扩张(雅典，希腊)

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-05-15 DOI: 10.1111/gean.12327

Luca Salvati

{"title":"A Long Way to Complexity: Nonlinear “Growth Stages” and Spatially Uncoordinated Settlement Expansion in a Compact City (Athens, Greece)","authors":"Luca Salvati","doi":"10.1111/gean.12327","DOIUrl":"10.1111/gean.12327","url":null,"abstract":"Recent urbanization trends reflect an increasing dependence on regional economic transformations, local population dynamics, and planning constraints, becoming intrinsically complex and nonlinear. Following this assumption, the present study proposes a new approach for the analysis of long-term urban expansion in a compact metropolitan region (Athens, Greece), clarifying the importance of spatial heterogeneity and volatility in building activity over more than one century. A spatially explicit statistical approach was used to define a development cycle reflecting the stratification of heterogeneous waves of compact and dispersed urbanization at municipal scale. While resulting in distinctive spatial patterns of building activity, long-term urban growth emerged as a multifaceted response to market stimuli, social change, and diversified territorial contexts. Results of a spatially explicit analysis of long-term urban expansion based on official statistics shed further light on processes of metropolitan growth and change, and contribute to design integrated strategies enhancing spatial coordination and a more balanced socioeconomic development of contemporary cities.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 2","pages":"280-299"},"PeriodicalIF":3.6,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45084045","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: 2