基于Moran’s I的安徽省太湖县耕地质量时空格局分析

李子杰; 高沪宁; 丁琪洵; 费坤; 丁世伟; 马友华

doi:10.13961/j.cnki.stbctb.2021.03.045

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基于Moran’s I的安徽省太湖县耕地质量时空格局分析

试验研究

- 基于Moran’s I的安徽省太湖县耕地质量时空格局分析
- Analysis on Temporal and Spatial Patterns of Cultivated Land Quality Based on Moran's I in Taihu County, Anhui Province
- 水土保持通报 2021年41卷第3期页码：350-356
- 作者机构：
  
  安徽农业大学资源与环境学院,安徽,合肥,230036
- 作者简介：
- 基金信息：
  
  安徽省教育厅高校协同创新项目“国产高分辨率对地观测系统安徽区域综合应用示范—高分背景下安徽省耕地质量智慧管理与大数据应用”（GXXT-2019-047）
- DOI：10.13961/j.cnki.stbctb.2021.03.045
  中图分类号： F301.21
- 纸质出版：2021
- 稿件说明：
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李子杰, 高沪宁, 丁琪洵, 等. 基于Moran’s I的安徽省太湖县耕地质量时空格局分析[J]. 水土保持通报, 2021,41(3):350-356.

Li Zijie, Gao Huning, Ding Qixun, et al. Analysis on Temporal and Spatial Patterns of Cultivated Land Quality Based on Moran's I in Taihu County, Anhui Province[J]. Bulletin of Soiland Water Conservation, 2021, 41(3): 350-356.
李子杰, 高沪宁, 丁琪洵, 等. 基于Moran’s I的安徽省太湖县耕地质量时空格局分析[J]. 水土保持通报, 2021,41(3):350-356. DOI： 10.13961/j.cnki.stbctb.2021.03.045.

Li Zijie, Gao Huning, Ding Qixun, et al. Analysis on Temporal and Spatial Patterns of Cultivated Land Quality Based on Moran's I in Taihu County, Anhui Province[J]. Bulletin of Soiland Water Conservation, 2021, 41(3): 350-356. DOI： 10.13961/j.cnki.stbctb.2021.03.045.

摘要

[目的

]

探究耕地质量时空格局演变规律，为各级土地管理部门进行耕地分区利用与保护提供决策依据，为提升耕地质量和优化土地空间布局提供参考。[方法

]

基于安徽省太湖县2008年及2018年耕地质量等级评价成果，以ArcGIS和GeoDa为平台，利用时间序列法和空间自相关分析等研究方法，分别从全局自相关和局部自相关两方面分析太湖县10 a跨度的耕地质量时空格局变异情况，划分制定4类分区管理方案：限制建设区、综合改良区、适度改良区和重点整治区，并有针对地提出符合实际情况的耕地管护措施。[结果

]

①2008—2018年，太湖县总耕地面积增加6 474.45 hm

；②2008年及2018年全局自相关Moran’s I分别为：0.419 478，0.288 328，Z得分分别为：8.677 693，5.527 830；③在空间分布上太湖县耕地质量空间正相关类型多以“组团”聚类形式出现，负相关类型无明显集中区域。[结论

]

太湖县10 a时间跨度上耕地面积增加了6 474.45 hm

，耕地资源的10 a平均变化率P=1.65%，耕地质量平均等级提升1.68等；在空间分布上呈显著空间自相关特征和空间聚集特征。

Abstract

[Objective] The evolution of temporal and spatial patterns of cultivated land quality was explored in order to provide a basis for decision-making by land management departments at all levels to rationally use and protect cultivated land

and to provide a reference for improving the quality of cultivated land and optimizing the spatial layout of land. [Methods] Based on the evaluation results of arable land quality in Taihu County

Anhui Province in 2008 and 2018

research methods such as time series methods and spatial autocorrelation analysis with ArcGIS and GeoDa platforms were used to analyze the variation in temporal and spatial patterns of cultivated land quality in Taihu County over a ten-year period from global autocorrelation and local autocorrelation. Four types of zoning management plans: restricted construction areas

comprehensive improvement areas

moderate improvement areas

and key remediation areas were devised and formulated

as well as management and protection measures that would meet actual conditions for cultivated land. [Results] ① From 2008 to 2018

the total arable land area of Taihu County increased by 6 474.45 hectares; ② The coefficients of global autocorrelation Moran’s I in 2008 and 2018 were 0.419 478 and 0.288 328

respectively

and the Z scores were 8.677 693 and 5.527 830

respectively; ③ The positive correlation types of cultivated land quality in Taihu County mostly appeared in the form of cluster

while the negative correlation types had no obvious concentrated areas. [Conclusion] The area of cultivated land in Taihu County increased by 6 474.45 hectares over the ten-year period. The average annual change rate (P) of cultivated land resources was 1.65%

and the average grade of cultivated land quality increased by 1.68. The spatial distribution showed significant spatial autocorrelation characteristics and space gathering features.

关键词

Keywords

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