doi:10.12202/j.0476-0301.2020017潘玉豪¹,
陈云皓¹,
张旭晨¹,
曹飞²,
孙中平²,
杜晓铮¹,
赵祥^1,,
1.遥感科学国家重点实验室，北京市陆表遥感数据产品工程技术研究中心，北京师范大学地理科学学部， 100875，北京
2.生态环境部卫星环境应用中心， 100094，北京
基金项目:国家重点研发计划资助项目（2017YFB0503904）；2019年北京高等学校高水平人才交叉培育“实培计划”资助项目

详细信息

通讯作者:赵祥（1971—），博士，教授，博士生导师。研究方向：从事定量遥感应用研究。e-mail：zhaoxiang@bnu.edu.cn

中图分类号:X87

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出版历程

收稿日期:2020-01-15
网络出版日期:2020-09-08
刊出日期:2020-08-25

Spatiotemporal changes analysis of land desertification sensitivity in Ningxia, China

Yuhao PAN¹,
Yunhao CHEN¹,
Xuchen ZHANG¹,
Fei CAO²,
Zhongping SUN²,
Xiaozheng DU¹,
Xiang ZHAO^1,,
1. State Key Laboratory of Remote Sensing Science, Beijing Engineering Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, 100875, Beijing, China
2. Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, 100094, Beijing, China



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摘要
摘要:选取土壤、地形、自然环境和社会经济4个方面的数据，采用Logistic回归模型分别对2001和2017年宁夏土地荒漠化敏感度进行了建模分析. 基于模型得到2001和2017年宁夏荒漠化敏感度等级数据。主要结论有：1）采用Logistic回归模型可以有效检测宁夏荒漠化敏感度，2001和2017年的模型准确度分别达到85%和78%；2）宁夏各区域按荒漠化风险等级由低到高排序，依次为北部引黄溉区、南部黄土丘陵区、中部干旱区；3）相比于2001年，2017年宁夏土地荒漠化风险级别总体呈下降趋势，大约有39%的高风险和极高风险区域转化为低风险和中等风险区域，得益于防沙治沙、禁牧封育与生态修复等政策的施行. 研究通过监测宁夏荒漠化易发生区域的动态变化趋势，及时为宁夏荒漠化防治工作布局提供参考信息.
关键词:荒漠化敏感度/
Logistic回归模型/
时空变化
Abstract:Desertification has posed a huge threat to the natural ecological environment and human society, and has been one of the most serious global environmental and socio-economic problems in the world. Ningxia is located in the arid and semi-arid transition zone of China, which is a highly ecologically sensitive area. In order to monitor the characteristics of desertification sensitivity and its spatiotemporal changes in Ningxia, four factors, such as soil, topography, natural environment, and socio-economic predictive factors, were selected to model and analyze land desertification sensitivity of Ningxia using logistic regression model in this study. Based on the desertification sensitivity of Ningxia in 2001 and 2017, the following conclusions were obtained in this study: 1) The logistic regression model could be used to detect the desertification sensitivity of Ningxia. The accuracy of the model in 2001 reached 85%, and the accuracy of the model in 2017 reached 78%; 2) The regions of Ningxia were ranked according to the desertification sensitivity from low to high, which were the northern Yellow River irrigation area, the southern loess hilly area, and the central arid area; 3) Compared with 2001, the risk level of desertification in Ningxia in 2017 showed a general decreasing trend. Approximately 39 percent of high-risk and extremely high-risk zones were converted into low-risk and medium-risk-grade zones, because of prohibition of grazing and implementation of artificial ecological restoration methods. This study could provide timely reference information for the implementation of desertification prevention and control work in Ningxia by monitoring the dynamic changes of desertification-prone areas in Ningxia.
Key words:desertification sensitivity/
logistic regression/
spatiotemporal change