Modeling the Spatial Formation Mechanism of Poverty-Stricken Counties in China by Using Geographical Detector

Abstract

The poverty-stricken counties in China follow a spatial pattern of regional poverty. Examining the influential factors of this spatial pattern can provide an important reference that can guide China in its implementation of a poverty alleviation policy. By applying a geographical detector and using a sample of poverty-stricken counties in China, this study explores the spatial relationship of county distribution with spatial influential factors, including terrain relief, cultivated land quality, water resource abundance, road network density, and the locational index. These poverty-stricken counties are then classified, and the main factors that restrict their economic development are determined. The results highlight that the selected poverty-stricken counties suffer a severe condition in each of the spatial factors mentioned above. Most of these counties are classified under the location index, terrain relief, and road network density constraint types. Each of the aforementioned spatial influential factors has unique controlling mechanisms on the distribution of these poverty-stricken counties. Most of these counties are constrained by two or multiple spatial influential factors, except for some counties located in South and Central China, which are mainly constrained by a single spatial influential factor. Therefore, these single factor-constrained poverty-stricken counties warrant more attention when a developmental policy for poverty alleviation is to be implemented. The various aspects of poverty-stricken counties constrained by multiple factors must be comprehensively considered with a special focus on their development. The differentiated policies must be designed for these poverty-stricken counties on the basis of their spatial influential factors.

[Retracted] Spatial Pattern Evaluation of Rural Tourism via the Multifactor‐Weighted Neural Network Model in the Big Data Era

“…The whole region is located in the continental arid and semiarid climate zone [ 17 ]. Ningxia Hui Autonomous Region administrates 5 prefecture-level cities (9 municipal districts, 2 county-level cities, and 11 counties), with two national AAAAA-level tourist attractions of the China Western Film Studio in Zhenbeibu and the Sand Lake, several 4A-level tourist attractions (including 96 A-level scenic spots), and numerous rural scenic spots [ 18 ]. There are mainly seven tourism plates in Ningxia: Great Sand Lake Holiday and Leisure Area, Xixia Cultural Tourism District, Saishang Hui Township Cultural Experience Plate, Frontier Cultural Tourism Plate, Great Shapotou Resort and Leisure Plate, Weizhou Historical and Cultural Tourism Plate, and Great Liupan Red Ecological Resort Plate [ 19 ].…”

Exploring the Impact of Rural Development Programs on Poverty Reduction in Chinese Counties: A Panel Data Analysis

“…Typically, researchers concentrate on the following areas: ( i )Factors determining the distribution of these counties. For instance, Lei Zhou's team categorizes national poverty-stricken counties based on constraints such as terrain, cultivated land resources, water abundance, traffic conditions, and location indices, indicating the natural challenges faced by these counties [6]. (ii) The allocation and efficiency of poverty alleviation funds in these counties.…”

Analysis of the Evolution of Foreign Trade Patterns and Influencing Factors in Henan Province from 2002 to 2021

“…Combined with the evaluation indicators proposed by previous scholars, the internal influencing factor indicators of foreign trade in Henan Province were created [28,[42][43][44][45][46][47]58,59]. The interpretation of the geographical detector indicators is shown in Table 3: Data discretization was performed using the ArcGIS natural breakpoint method.…”

“…Therefore, adopting a suitable and reliable methodology for this study is essential. The geographical detector model is a powerful tool for driver and factor analysis [42][43][44][45][46][47], and trade gravity models are mainly used to analyze specific commodities' evolution and influencing factors [48][49][50][51]. Therefore, this study analyzes the trade scale, pattern, and characteristics of spatial and temporal changes in Henan Province by using various statistical data and combining foreign trade dependence, RCA (revealed comparative advantage index), HM (hubness measurement index), and TII (trade intensity index).…”