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时空统计学在贫困研究中的应用及展望
引用本文:葛咏,刘梦晓,胡姗,任周鹏. 时空统计学在贫困研究中的应用及展望[J]. 地球信息科学学报, 2021, 23(1): 58-74. DOI: 10.12082/dqxxkx.2021.200628
作者姓名:葛咏  刘梦晓  胡姗  任周鹏
作者单位:1.中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 1001012.中国科学院大学,北京 100049
摘    要:消除贫困是人类社会的共同目标.贫困分布具有明显的空间特征,同时呈现出空间异质性和空间相关性.时空统计学以时空分析为优势,在贫困的时空分布及形成机制研究中发挥了重要作用.本文综述了不同时期我国贫困分布的空间特征、贫困数据的空间类型和特征以及贫困时空分布的影响因素,并总结了时空统计学方法在贫困空间研究中的4类应用,包括:探...

关 键 词:贫困  时空数据  时空统计  空间自相关  空间异质性  空间贫困陷阱  时空格局  时空变化
收稿时间:2020-10-21

The Application and Prospect of Spatiotemporal Statistics in Poverty Research
GE Yong,LIU Mengxiao,HU Shan,REN Zhoupeng. The Application and Prospect of Spatiotemporal Statistics in Poverty Research[J]. Geo-information Science, 2021, 23(1): 58-74. DOI: 10.12082/dqxxkx.2021.200628
Authors:GE Yong  LIU Mengxiao  HU Shan  REN Zhoupeng
Affiliation:1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China2. University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:Eliminating poverty is a common goal of human society. Poverty has the characteristics of spatial heterogeneity and spatial autocorrelation. Spatiotemporal statistical methods dealing with georeferenced or spatiotemporal data have been widely employed for analyzing spatiotemporal poverty data. This paper reviews the applications of spatiotemporal statistical methods in spatiotemporal poverty analysis and classifies the applications into four categories:(1) exploratory analysis of poverty, mainly to identify and quantitatively analyze the spatiotemporal distribution pattern of poverty;(2) identification of spatial determinants of poverty, to analyze the influencing factors of poverty by constructing a model of the relationship between poverty and various geographical elements;(3) spatial mapping of poverty, to obtain the distribution of poverty in the entire region using sampling data;and(4) spatiotemporal analysis of poverty, to reveal the spatiotemporal changes of poverty and their driving factors. On the basis of explaining the principles of these methods, we give examples of recent applications to illustrate how specific spatiotemporal statistical methods are applied to spatial poverty research. On this basis, the shortcomings of current spatiotemporal poverty research and potential development on future poverty research are also summarized.
Keywords:poverty  spatiotemporal data  spatiotemporal statistics  spatial autocorrelation  spatial heterogeneity  spatial poverty traps  spatiotemporal pattern  spatiotemporal change
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