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DOI | 10.1016/j.ecolind.2021.107908 |
Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020 | |
Meng, Xiaoyu; Gao, Xin; Li, Sen; Li, Shengyu; Lei, Jiaqiang | |
通讯作者 | Gao, X (通讯作者),Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, 818 South Beijing Rd, Urumqi 830011, Xinjiang, Peoples R China. |
发表日期 | 2021 |
ISSN | 1470-160X |
EISSN | 1872-7034 |
卷号 | 129 |
英文摘要 | Desertification is one of the most serious ecological and environmental problems in arid regions. Low-cost, wideranging, and high-precision methods are essential for the formulation of appropriate strategies for quantitatively monitoring desertification. In this study, based on Google Earth Engine and Landsat images, six machine learning methods were used to monitor desertification dynamics in 1990-2020 in Mongolia. The spatiotemporal distributions and changes in desertification at different stages were analyzed using gravity center change and intensity analysis models. Subsequently, we quantitatively investigated the factors driving desertification in Mongolia. The results indicate that the maximum entropy method can obtain the most accurate assessment of the degree of desertification in comparison with the other five methods, with an accuracy of 96%. In 1990-2005, the area of desertified land increased significantly, afterward, a decreasing trend was observed. Lightly and moderately desertified lands had the highest change intensities and were most sensitive to environmental factors. Although the desertification dynamics are under the influence of both natural and anthropogenic factors, precipitation plays a dominant role in Mongolia. This study provides a comprehensive analysis of the desertification status and trends in Mongolia, and presents desertification maps that can be used to formulate preventive measures and guide desertification prevention and control. |
关键词 | HORQIN SANDY LANDAEOLIAN DESERTIFICATIONRANDOM FORESTNORTHERN SHAANXIMODISCLASSIFICATIONDYNAMICSAREASDEGRADATIONALGORITHM |
英文关键词 | GEE; Machine learning methods; Desertification dynamics; Gravity center change; Intensity analysis; Desertification maps; Mongolia |
语种 | 英语 |
WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
WOS类目 | Biodiversity Conservation ; Environmental Sciences |
WOS记录号 | WOS:000685516500004 |
来源期刊 | ECOLOGICAL INDICATORS
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来源机构 | 中国科学院西北生态环境资源研究院 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/255031 |
作者单位 | [Meng, Xiaoyu; Gao, Xin; Li, Shengyu; Lei, Jiaqiang] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, 818 South Beijing Rd, Urumqi 830011, Xinjiang, Peoples R China; [Meng, Xiaoyu; Gao, Xin; Li, Shengyu; Lei, Jiaqiang] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Li, Sen] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Desert & Desertificat, 260 West Donggang Rd, Lanzhou 730000, Gansu, Peoples R China |
推荐引用方式 GB/T 7714 | Meng, Xiaoyu,Gao, Xin,Li, Sen,et al. Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020[J]. 中国科学院西北生态环境资源研究院,2021,129. |
APA | Meng, Xiaoyu,Gao, Xin,Li, Sen,Li, Shengyu,&Lei, Jiaqiang.(2021).Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020.ECOLOGICAL INDICATORS,129. |
MLA | Meng, Xiaoyu,et al."Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020".ECOLOGICAL INDICATORS 129(2021). |
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