生态与农村环境学报 ›› 2016, Vol. 32 ›› Issue (3): 361-366.doi: 10.11934/j.issn.1673-4831.2016.03.004

• 西部重点矿区土地退化因素调查专题 • 上一篇    下一篇

基于GIS的乌海矿区土地退化因素分析

黄园园,闫庆武,雷少刚,李俊刚   

  1. 中国矿业大学环境与测绘学院, 江苏 徐州 221116
  • 收稿日期:2015-11-11 出版日期:2016-05-25 发布日期:2016-05-27
  • 通讯作者: 闫庆武,E-mail:3403175@163.com E-mail:3403175@163.com
  • 作者简介:黄园园(1993—),女,河南商丘人,硕士生,主要从事GIS应用研究。E-mail:979894964@qq.com
  • 基金资助:

    国家科技基础性工作专项(2014FY110800)

Factors of Land Degradation in Wuhai Mining Area Based on GIS.

HUANG Yuan-yuan, YAN Qing-wu, LEI Shao-gang, LI Jun-gang   

  1. College of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
  • Received:2015-11-11 Online:2016-05-25 Published:2016-05-27

摘要:

为定量研究矿区土地退化特征及其驱动因素,利用遥感和GIS技术分析1990—2010年内蒙古乌海矿区土地利用类型转化特征,在此基础上选取多个经济社会以及空间距离因子,利用Logistic模型对研究区域1990—2000和2000—2010年2个不同时间段土地退化的驱动因素进行探究。结果表明,乌海矿区近20 a的土地利用变化集中表现在草地大面积减少,建设用地和荒漠面积大幅度增加;荒漠和建设用地增长最快,主要源于草地和耕地的转化,土地退化主要表现在沙地等荒漠面积的增长;对土地退化的Logistic回归模型分析表明,土地退化在第1阶段(1990—2000年)的主要驱动因素是到最近采矿点距离、到最近乡镇距离和坡度Ⅱ(5~15°);第2阶段(2000—2010年)的主要驱动因素是到最近水域距离、高程和到最近道路距离。

关键词: 乌海矿区, 土地退化, 遥感, 驱动因素, Logistic回归模型

Abstract:

In order to study characteristics and driving factors of the land degradation in mining areas quantitatively, remote sensing and GIS technology were used to characterize changes in land use in area and type in the Wuhai mining area, Inner Mongolia from 1990 to 2010. On such a basis, some economic, social and spatial factors were selected for exploration of factors driving changes in land use in the studied zone during the 2 different periods of 1990-2000 and 2000-2010. Results show that the changes in land use in the study area in the recent 20 years were manifested mainly in drastic decrease of grassland in area and rapid expansion of construction land and wasteland, which were used to be grassland and farmland, while land degradation was mainly in growth of sandy land and wasteland in area. Aanalysis using the Logistic regression model reveals that land degradation during the first period (1990-2000) was driven mainly by factors, like “distance to the nearest mining site”, “distance to the nearest village and town” and slope Ⅱ (5-15°), while during the second period (2000-2010) it was by factors like “distance to the nearest water source”, “elevation”, and “distance to the nearest road”.

Key words: Wuhai mining area, land degradation, remote sensing, driving factor, Logistic regression model

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