Identification of rural regional poverty type based on spatial multi-criteria decision-making—taking Gansu Province, an underdeveloped area in China, as an example
2022
Dou, Haojian | Ma, Llibang | Liu, Shichun | Fang, Fang
The accurate identification of poverty types in rural areas is a national strategic need for poverty targeting and overall poverty alleviation. In this study, we took Gansu Province, a key area for poverty alleviation in China, as an example. With the multidimensional comprehensive measurement model of poverty, multi-criteria decision analysis method and ArcGIS spatial analysis method, we explored the poverty-reducing factors of each evaluation unit and classified the poverty type. Results: (1) The evaluation unit of 60.49% in Gansu Province is at the median level of poverty and below, and the phenomenon of extreme poverty is rare. Multidimensional poverty index presents a pattern of “high at both ends, and low in the middle” in space. (2) The proportion of highway entrances and exits, the proportion of rural water-saving irrigation area, the number of health staff in institutions per 1000 people, the number of beds in health institutions per 1,000 people, the water supply per capita water conservancy project, and the number of full-time secondary school teachers per thousand people are the main poverty factors. (3) Poverty in Gansu Province is mainly dominated by single factor and associated with dual-factor, which account for 54.32% of all evaluation units. (4) Economic poverty (income poverty) is relatively poor. It is a result of multi-dimensional poverty. This research can provide guidance and support to facilitate the precise targeting and policy implementation of poverty alleviation targets, and also provide a reference basis for the improvement of the national poverty reduction strategy and the study of poverty geography-related issues.
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