利用多源空间数据识别中国农村贫困复杂性的空间识别与分布格局

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-04-30 DOI:10.1155/2024/7012402
Zhenyu Qi, Jinghu Pan, Yaya Feng
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引用次数: 0

摘要

地区贫困是当今世界面临的最严峻挑战之一。贫困、反贫困、扶贫是学者和公众关注的焦点。本文以中国县域为研究单元,从自然因素和社会经济因素中选取贫困的影响因素,建立评价指标体系,模拟各县的自然贫困指数和社会经济脱贫指数,并利用 GIS 空间分析和 BP 人工神经网络阐明空间贫困的分布特征。结果表明,自然因素是中国县域贫困的主要原因,自然贫困指数较高的县有 710 个,占全国县域总数的近 30%。全国县级自然贫困指数沿经纬度呈明显的带状分布格局,由北向南、由西向东呈带状分布;社会经济因素在扶贫中发挥了一定的作用,社会经济扶贫指数较低的县多达 1521 个,约占全国县级总数的 64%。县级社会经济扶贫指数的空间分布较为分散。通过空间扫描统计,达到统计显著性水平的县域贫困压力指数风险群共有 44 个,涉及 243 个县区。在扶贫实践中,连片贫困地区内部县区应加强合作交流。在扶贫开发过程中,应根据县域的贫困类型和自我发展能力,有针对性地开展扶贫开发和经济建设,提高扶贫效率。相对富裕、率先脱贫的地区应发挥引领示范作用,增强区域中心城市的辐射力。本研究的突出特点是多源数据的综合利用和新型空间分析方法的运用(灵活的空间扫描方法在传染病防控研究领域得到广泛应用)。通过构建包括自然因素和社会因素在内的多维贫困测量体系,区分区域贫困中致贫因素和脱贫因素的差异。同时,采用灵活的空间扫描检测方法,检测贫困空间模式的分化机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data

Regional poverty is one of the most serious challenges facing the world today. Poverty, antipoverty, and poverty alleviation are the focus of the attention of scholars and the public. This paper takes China’s counties as the research unit, selects the influencing factors of poverty from natural and socio-economic factors, establishes an evaluation index system, simulates the natural poverty index and socio-economic poverty eradication index of each county, and clarifies the distribution characteristics of spatial poverty using GIS spatial analysis and BP artificial neural network. The results indicate that natural factors are the main cause of poverty in Chinese counties, with 710 counties having a high natural poverty index, accounting for nearly 30% of the total number of counties in the country. The national county-level natural poverty index shows a clear strip distribution pattern along latitude and longitude, with a strip distribution from north to south and from west to east; socio-economic factors have played a certain role in poverty alleviation, with as many as 1521 counties with low socio-economic poverty alleviation indices, accounting for approximately 64% of the total number of counties in the country. The spatial distribution of the county-level socio-economic poverty alleviation index is relatively fragmented. Through spatial scanning statistics, a total of 44 county poverty pressure index risk clusters reached a statistical significance level, involving 243 counties and districts. In poverty reduction practice, the internal counties and districts of contiguous poverty-stricken areas should strengthen cooperation and exchange. In the process of poverty alleviation and development, targeted poverty alleviation and economic development should be carried out based on the poverty-dominant type and self-development ability of the county, in order to improve efficiency. Regions that are relatively prosperous and have taken the lead in poverty reduction should play a leading and exemplary role in strengthening the radiation power of regional central cities. The prominent feature of this study is the comprehensive utilization of multisource data and the use of new spatial analysis methods (flexible spatial scanning method is widely used in the field of infectious disease prevention and control research). By constructing a multidimensional poverty measurement system that includes natural and social factors, it distinguishes the differences between the factors that cause poverty and the factors that eliminate poverty in regional poverty. At the same time, the flexible spatial scanning detection method was used to detect the differentiation mechanism of poverty spatial patterns.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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