基于Google Earth Engine(GEE)的毛乌素沙地风蚀荒漠化过程监测  

Monitoring of wind erosion desertification process in the Mu Us Desert based on Google Earth Engine(GEE)

作　　者：刘永杰 杜鹤强 范亚伟 杨胜飞 Liu Yongjie;Du Heqiang;Fan Yawei;Yang Shengfei(Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院西北生态环境资源研究院干旱区生态安全与可持续发展重点实验室,甘肃兰州730000 [2]中国科学院大学,北京100049

出　　处：《中国沙漠》2025年第2期262-274,共13页Journal of Desert Research

基　　金：国家自然科学基金项目(42271016)。

摘　　要：荒漠化发展使毛乌素沙地生态环境面临严峻挑战。当前荒漠化监测存在目视解译主观性强、数据更新慢等问题。因此,亟待发展客观、快速的荒漠化定量监测手段。随着遥感云计算的出现与发展,Google Earth Engine(GEE)平台不仅提供多源遥感信息数据,还具备高效的计算性能,为荒漠化快速监测创造了条件。基于GEE平台和Landsat影像,构建毛乌素沙地2000—2022年Albedo-NDVI特征空间模型,并利用地理探测器模型定量分析影响其荒漠化演变的驱动力因素。结果表明:(1)2000—2022年,毛乌素沙地荒漠化趋势整体逆转,轻度荒漠化和非荒漠化面积逐年增加,且恢复区域面积大于退化区域。空间分布呈现明显的异质性,西北部荒漠化程度较重,东南部荒漠化程度较轻且逆转较快。(2)毛乌素沙地荒漠化演变是多种因素共同作用的结果,降水量和GDP因子解释力排名位居前列,q值平均值均较高于其他因子,分别为0.078和0.105,是影响毛乌素沙地荒漠化的主要驱动因子。Desertification poses a severe challenge to the ecological environment of the Mu Us Desert. However, current desertification monitoring is subject to the limitations of strong subjectivity in visual interpretation and slow data updates. Therefore, there is an urgent needing to develop objective and rapid quantitative monitoring methods for desertification. With the emergence and development of remote sensing cloud computing, such as Google Earth Engine(GEE) not only provide multi-source remote sensing data but also has efficient computational performance, which creates conditions for rapid desertification monitoring. Therefore, based on the GEE platform and Landsat imagery, this study constructs an Albedo-NDVI feature space model for the Mu Us Desert from 2000 to 2022 and uses the Geographic Detector Model to quantitatively analyze the driving factors affecting desertification evolution. The conclusions are as follows:(1) The overall trend of desertification in the study area has improved, with an annual increase in the area of light desertification and non-desertification, and the area of recovery is larger than that of degradation. The spatial distribution shows obvious heterogeneity, with the northwestern area being more heavily desertified, and the southeastern area being lightly desertified and with a faster rate of reversal.(2) The evolution of desertification in the Mu Us Desert is the result of the combined action of multiple factors, among which precipitation and GDP factors have the highest explanatory power over the 22 years, with average q values of 0.078 and 0.105, respectively, which indicated that they are the main driving factors affecting desertification in the study area.

关 键 词：GEE 荒漠化 Albedo-NDVI特征空间 地理探测器 毛乌素沙地 

分 类 号：P931.3[天文地球—自然地理学]