Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression
The spatial pattern of rural poverty and its influencing factors are unique in regions located in the “double zone”, overlaying the Loess Plateau landform and interprovincial border socioeconomic zone. Using Huining County, located in the interprovincial border area of the Loess Plateau, as a case s...
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MDPI AG
2020-05-01
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author | Tao Li Xiaoshu Cao Menglong Qiu Yu Li |
author_facet | Tao Li Xiaoshu Cao Menglong Qiu Yu Li |
author_sort | Tao Li |
collection | DOAJ |
description | The spatial pattern of rural poverty and its influencing factors are unique in regions located in the “double zone”, overlaying the Loess Plateau landform and interprovincial border socioeconomic zone. Using Huining County, located in the interprovincial border area of the Loess Plateau, as a case study, this paper examines the spatial heterogeneity of rural poverty patterns and poverty-causing factors by using geographically weighted regression (GWR) modeling. The potential accessibility indicator is employed to identify the formative mechanism of rural poverty. The results show that rural poverty is significantly correlated with county-level accessibility, water resource accessibility, and town-level accessibility. County-level accessibility and town-level accessibility have significant border effects on rural poverty. The arid characteristics in certain areas of the Loess Plateau mean that the impact of water resource accessibility on the incidence of rural poverty is second only to that of county-level accessibility. Forestland resources have a positive correlation with the incidence of rural poverty in the region dominated by farming. Finally, targeted poverty reduction policies are proposed based on the results of the analysis of poverty-causing factors. The findings derived from this paper can help other developing countries in designing their own poverty reduction policies. |
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issn | 2220-9964 |
language | English |
last_indexed | 2024-03-10T19:34:45Z |
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spelling | doaj.art-723ae15ef06f4f2ebeef7ec4b6d9ed812023-11-20T01:48:04ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-05-019634510.3390/ijgi9060345Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted RegressionTao Li0Xiaoshu Cao1Menglong Qiu2Yu Li3Northwest Land and Resources Research Center, Shaanxi Normal University, Xi’an 710119, ChinaNorthwest Land and Resources Research Center, Shaanxi Normal University, Xi’an 710119, ChinaNorthwest Land and Resources Research Center, Shaanxi Normal University, Xi’an 710119, ChinaNorthwest Land and Resources Research Center, Shaanxi Normal University, Xi’an 710119, ChinaThe spatial pattern of rural poverty and its influencing factors are unique in regions located in the “double zone”, overlaying the Loess Plateau landform and interprovincial border socioeconomic zone. Using Huining County, located in the interprovincial border area of the Loess Plateau, as a case study, this paper examines the spatial heterogeneity of rural poverty patterns and poverty-causing factors by using geographically weighted regression (GWR) modeling. The potential accessibility indicator is employed to identify the formative mechanism of rural poverty. The results show that rural poverty is significantly correlated with county-level accessibility, water resource accessibility, and town-level accessibility. County-level accessibility and town-level accessibility have significant border effects on rural poverty. The arid characteristics in certain areas of the Loess Plateau mean that the impact of water resource accessibility on the incidence of rural poverty is second only to that of county-level accessibility. Forestland resources have a positive correlation with the incidence of rural poverty in the region dominated by farming. Finally, targeted poverty reduction policies are proposed based on the results of the analysis of poverty-causing factors. The findings derived from this paper can help other developing countries in designing their own poverty reduction policies.https://www.mdpi.com/2220-9964/9/6/345Loess Plateauinterprovincial border areasrural povertyvillagegeographically weighted regressionChina |
spellingShingle | Tao Li Xiaoshu Cao Menglong Qiu Yu Li Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression ISPRS International Journal of Geo-Information Loess Plateau interprovincial border areas rural poverty village geographically weighted regression China |
title | Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression |
title_full | Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression |
title_fullStr | Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression |
title_full_unstemmed | Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression |
title_short | Exploring the Spatial Determinants of Rural Poverty in the Interprovincial Border Areas of the Loess Plateau in China: A Village-Level Analysis Using Geographically Weighted Regression |
title_sort | exploring the spatial determinants of rural poverty in the interprovincial border areas of the loess plateau in china a village level analysis using geographically weighted regression |
topic | Loess Plateau interprovincial border areas rural poverty village geographically weighted regression China |
url | https://www.mdpi.com/2220-9964/9/6/345 |
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