Geographical Analysis最新文献_第8页

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

An Extended K Function Method for Analyzing Distributions of Polygons with GIS 用GIS分析多边形分布的扩展K函数方法

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-04-08 DOI: 10.1111/gean.12326

Atsuyuki Okabe, Kayo Okabe

{"title":"An Extended K Function Method for Analyzing Distributions of Polygons with GIS","authors":"Atsuyuki Okabe, Kayo Okabe","doi":"10.1111/gean.12326","DOIUrl":"10.1111/gean.12326","url":null,"abstract":"The objective of this paper is to develop a K function method for analyzing distributions of polygon-like entities in the real world by extending Ripley’s K function method. Many empirical studies using the K function method assume that entities are represented by points. If entities are small enough in comparison with a study area, this approximation may be acceptable. If not, polygon-like entities may not be approximated by points. To deal with polygon-like entities, this paper develops a K function method for analyzing distributions of polygons. First, the paper shows a method for extending the local K function of points to that of polygons. Second, the paper compares the result obtained from the K function of polygons with that of the points representing the polygons and shows a distinctive difference. Third, the paper formulates the cross K function method of polygons to analyze the relationship between two distributions of polygons of different kinds. Fourth, the paper implements the methods in GIS. Last, the paper applies the cross K function method of polygons to actual distributions of buildings of different uses in Aoyama, Tokyo.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 2","pages":"268-279"},"PeriodicalIF":3.6,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43658331","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

Making Space in Geographical Analysis 在地理分析中制造空间

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-03-23 DOI: 10.1111/gean.12325

Rachel S. Franklin, Elizabeth C. Delmelle, Clio Andris, Tao Cheng, Somayeh Dodge, Janet Franklin, Alison Heppenstall, Mei-Po Kwan, WenWen Li, Sara McLafferty, Jennifer A. Miller, Darla K. Munroe, Trisalyn Nelson, Özge Öner, Denise Pumain, Kathleen Stewart, Daoqin Tong, Elizabeth A. Wentz

引用次数: 5

Automated Detection of Missing Links in Bicycle Networks 自行车网络中缺失环节的自动检测

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-03-21 DOI: 10.1111/gean.12324

Anastassia Vybornova, Tiago Cunha, Astrid Gühnemann, Michael Szell

{"title":"Automated Detection of Missing Links in Bicycle Networks","authors":"Anastassia Vybornova, Tiago Cunha, Astrid Gühnemann, Michael Szell","doi":"10.1111/gean.12324","DOIUrl":"10.1111/gean.12324","url":null,"abstract":"Cycling is an effective solution for making urban transport more sustainable. However, bicycle networks are typically developed in a slow, piecewise process that leaves open a large number of gaps, even in well-developed cycling cities like Copenhagen. Here, we develop the IPDC procedure (Identify, Prioritize, Decluster, Classify) for finding the most important missing links in urban bicycle networks, using data from OpenStreetMap. In this procedure we first identify all possible gaps following a multiplex network approach, prioritize them according to a flow-based metric, decluster emerging gap clusters, and manually classify the types of gaps. We apply the IPDC procedure to Copenhagen and report the 105 top priority gaps. For evaluation, we compare these gaps with the city’s most recent Cycle Path Prioritization Plan and find considerable overlaps. Our results show how network analysis with minimal data requirements can serve as a cost-efficient support tool for bicycle network planning. By taking into account the whole city network for consolidating urban bicycle infrastructure, our data-driven framework can complement localized, manual planning processes for more effective, city-wide decision-making.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 2","pages":"239-267"},"PeriodicalIF":3.6,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48855635","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: 13

Applying Local Indicators of Spatial Association to Analyze Longitudinal Data: The Absolute Perspective 运用空间关联局部指标分析纵向数据:绝对视角

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-03-12 DOI: 10.1111/gean.12323

Ran Tao, Yuzhou Chen

{"title":"Applying Local Indicators of Spatial Association to Analyze Longitudinal Data: The Absolute Perspective","authors":"Ran Tao, Yuzhou Chen","doi":"10.1111/gean.12323","DOIUrl":"10.1111/gean.12323","url":null,"abstract":"Local Indicators of Spatial Association (LISA) are a class of spatial statistical methods that have been widely applied in various scientific fields. When applying LISA to make longitudinal comparisons of spatial data, a common way is to run LISA analysis at each time point, then compare the results to infer the distributional dynamics of spatial processes. Given that LISA hinges on the global mean value that often varies across time, the LISA result generated at time Ti reflects the spatial patterns strictly with respect to Ti. Therefore, the typical comparative cross-sectional analysis with LISA can only characterize the relative distributional dynamics. However, the relative perspective alone is inadequate to comprehend the full picture, as the patterns are not directly associated with the changes of the spatial process’s intensity. We argue that it is important to obtain the absolute distribution dynamics to complement the relative perspective, especially for tracking how spatial processes evolve across time at the local level. We develop a solution that modifies the significance test when implementing LISA analysis of longitudinal data to reveal and visualize the absolute distribution dynamics. Experiments were conducted with Mongolian livestock data and Rwanda population data.","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"55 2","pages":"225-238"},"PeriodicalIF":3.6,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42844572","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

The Majority Theorem for the Single (p = 1) Median Problem and Local Spatial Autocorrelation 单（p=1）中值问题的多数定理与局部空间自相关

IF 3.6 3区地球科学

Geographical Analysis Pub Date : 2022-03-10 DOI: 10.1111/gean.12321

Daniel A. Griffith, Yongwan Chun, Hyun Kim

引用次数: 0