湖北农业科学 ›› 2023, Vol. 62 ›› Issue (5): 14-21.doi: 10.14088/j.cnki.issn0439-8114.2023.05.004

• 资源·环境 • 上一篇    下一篇

基于地理探测器的耕地破碎化影响因素分析——以广州市为例

陈俊韬, 林锦耀   

  1. 广州大学地理科学与遥感学院,广州 510006
  • 收稿日期:2022-04-27 出版日期:2023-05-25 发布日期:2023-06-12
  • 通讯作者: 林锦耀(1989-),男,副教授,博士,主要从事土地资源管理研究,(电子信箱)ljy2012@gzhu.edu.cn。
  • 作者简介:陈俊韬(1998-),男,广东湛江人,在读硕士研究生,研究方向为土地利用空间分析,(电话)15768627423(电子信箱)1273294765@qq.com。
  • 基金资助:
    广东省基础与应用基础研究基金自然科学基金项目(2023A1515030300); 国家自然科学基金项目(41801307); 广州市科技计划项目(202201010289)

Analysis of influencing factors of farmland fragmentation based on geographical detector: A case study of Guangzhou City

CHEN Jun-tao, LIN Jin-yao   

  1. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
  • Received:2022-04-27 Online:2023-05-25 Published:2023-06-12

摘要: 以广州市作为研究区,采用景观格局指数法、综合指数法以及主成分分析法来构建耕地破碎化程度评价体系,计算出区域内各街道/镇单位的耕地破碎化程度综合指数,选取10个可量化的自然条件及人类社会活动因子,利用地理探测器模型探测10个因子对耕地破碎化的影响程度。结果表明,10个因子均为广州市耕地破碎化的影响因子,其单个因子对耕地破碎化影响由强到弱为市区行政中心距离因子、气温因子、 GDP因子、坡度因子和海拔因子、降水量因子、建设用地距离因子、道路距离因子、水体距离因子、人口密度因子;10种因子中任意2种因子的交互作用均表现为双因子增强或非线性增强。基于研究结果,提出针对性建议,以期为降低广州市耕地破碎化程度提供有价值的决策参考。

关键词: 耕地破碎化, 地理探测器, 景观格局指数, 主成分分析法, 广州市

Abstract: Guangzhou was selected as the research area. The landscape pattern index method, comprehensive index method and principal component analysis method were used to construct the evaluation system of farmland fragmentation degree, and the comprehensive index of farmland fragmentation degree of each town and street unit in the region was calculated. Ten quantifiable factors of natural conditions and human social activity were selected, and the geographical detector model was used to detect the impact of 10 factors on farmland fragmentation. The results showed that all 10 factors were the influencing factors of farmland fragmentation in Guangzhou City. The influence of the single factor on farmland fragmentation from strong to weak was urban administrative center distance factor, temperature factor, GDP factor, slope factor and altitude factor, precipitation factor, construction land distance factor, road distance factor, water body distance factor and population density factor. The interaction of any two of the 10 factors showed two-factor enhancement or nonlinear enhancement. Based on the research conclusions, some suggestions were put forward to provide valuable decision-making reference for reducing the level of farmland fragmentation in Guangzhou City.

Key words: farmland fragmentation, geographical detector, landscape pattern index, principal component analysis, Guangzhou City

中图分类号: