Spatial Autocorrelation Patterns and Influencing Factors of Soil and Water Loss and Socio-economic Development in Jilin Province

Zhai Yukun; Li Yonghong; Shen Haiou; Che Xiaocui

doi:10.13961/j.cnki.stbctb.2024.05.016

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Spatial Autocorrelation Patterns and Influencing Factors of Soil and Water Loss and Socio-economic Development in Jilin Province

- Spatial Autocorrelation Patterns and Influencing Factors of Soil and Water Loss and Socio-economic Development in Jilin Province
- Bulletin of Soiland Water Conservation Vol. 43, Issue 5, Pages: 144-151(2024)
- 作者机构：
  
  1. 内蒙古大学生态与环境学院,内蒙古,呼和浩特,010021
  2. 吉林农业大学资源与环境学院,吉林,长春,130118
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2024.05.016
  CLC： S157.1
- Published：2024
- 稿件说明：
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Zhai Yukun, Li Yonghong, Shen Haiou, et al. Spatial Autocorrelation Patterns and Influencing Factors of Soil and Water Loss and Socio-economic Development in Jilin Province[J]. Bulletin of Soiland Water Conservation, 2024, 43(5): 144-151.
DOI：

Zhai Yukun, Li Yonghong, Shen Haiou, et al. Spatial Autocorrelation Patterns and Influencing Factors of Soil and Water Loss and Socio-economic Development in Jilin Province[J]. Bulletin of Soiland Water Conservation, 2024, 43(5): 144-151. DOI： 10.13961/j.cnki.stbctb.2024.05.016.

摘要

[目的] 研究吉林省水土流失与社会经济空间自相关性特征及其影响因素，为该省水土保持与绿色协调发展提供科学依据。[方法] 基于吉林省各县市水土流失面积，结合相应年份社会、经济统计资料，采用GIS，GeoDa与OLS等技术与方法，对吉林省2017—2021年水土流失与社会经济空间自相关性进行系统研究，并辨识了关键影响因素。[结果] ①吉林省水土流失的Morans’I指数均为正数且最小值为0.254 6，水土流失在部分地区存在一定的集聚效应，高—高集聚区主要集中于吉林省西北地区，低—低集聚区主要分布在南部地区。②吉林省社会经济指标中，城市化率、建设用地比例、植被覆盖面积以及农业经济增长率的Moran’s I值相对较高，在空间上存在一定集聚特征。③水土流失与社会经济局部双变量空间自相关性中，城市化率和林地面积的Moran’s I值较大，社会类型数据较人口类型数据和经济类型数据空间分布更集中。④农业GDP、农业用地比例、植被覆盖比例和水土流失的相关性较高，5 a平均Robust_Pr值分别为0.038，0.003和0.154。[结论] 吉林省水土流失、社会经济及水土流失与社会经济双变量在空间上均具有较强自相关性，城市化率和植被覆盖面积是引起水土流失的关键影响因素。

Abstract

[Objective] The spatial autocorrelation patterns and influencing factors of soil and water loss and socio-economic development in Jilin Province were analyzed to provide a scientific basis for soil and water conservation and the green coordinated development in Jilin Province. [Methods] The analysis was based on the area of soil and water loss in various counties and cities in Jilin Province

combined with the social and economic statistics in the corresponding period. Tools including geographic information system (GIS)

GeoDa

and ordinary least squares (OLS)linear regression models were used to analyze the spatial autocorrelation patterns of soil and water loss and socio-economic development and to identify the key influencing factors in Jilin Province from 2017 to 2021. [Results] ① The index of Moran’s I of soil and water loss in Jilin Province was positive with a minimum value of 0.254 6. Soil and water loss had an agglomeration effect in certain areas. The high-high agglomeration areas were primarily concentrated in the northwest of Jilin Province

and the low-low agglomeration areas were primarily concentrated in the southern region. ② The values of Moran’s I of urbanization rate

proportion of construction land

vegetation coverage area

and agricultural economic growth rate from the socio-economic indicators system of Jilin Province were relatively higher

and there were certain agglomeration characteristics in spatial. ③ The spatial autocorrelation analysis of soil and water loss and socio-economic reflected that Moran’s I values of “urbanization rate” and “forest area” were relatively large

and the spatial distribution of social type data was more concentrated compared to population and economic type data. ④ A high correlation was observed between the agricultural GDP

agricultural land use ratio

vegetation coverage ratio

and soil and water loss. The five-year average results of the correlation were 0.038

0.003

and 0.154

respectively. [Conclusion] The soil and water loss

socio-economic development

and the double variables of soil and water loss and socio-economic development in Jilin Province have strong autocorrelation in space

respectively. Urbanization rate and vegetation coverage area were determined to have the most significant impact on soil and water loss among all the influencing factors.

关键词

Keywords

references

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