A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5

被引：2
作者：
Yang, Jingyi [1 ,2 ,3 ]
Wang, Qinjun [1 ,2 ,3 ,4 ,5 ]
Chang, Dingkun [1 ,2 ,3 ]
Xu, Wentao [1 ,2 ,3 ]
Yuan, Boqi [1 ,2 ,3 ]
机构：
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Int Res Ctr Big Data Sustainable Dev Goals, Beijing, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[4] Kashi Aerosp Informat Res Inst, Kashi 844199, Peoples R China
[5] Hainan Aerosp Informat Res Inst, Key Lab Earth Observat Hainan Prov, Sanya 572029, Peoples R China
来源：
SENSORS | 2023年 / 23卷 / 22期
基金：
海南省自然科学基金; 中国国家自然科学基金; 国家重点研发计划;
关键词：
desertification; land classification; fine classification; deep learning; influencing factors; GANSU PROVINCE; MINQIN DESERT; WATER; OASIS; RESOURCES;
D O I：
10.3390/s23229173
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Land desertification is one of the serious ecological and environmental problems facing mankind today, which threatens the survival and development of human society. China is one of the countries with the most serious land desertification problems in the world. Therefore, it is of great theoretical value and practical significance to carry out accurate identification and monitoring of land desertification and its influencing factors in ecologically fragile areas of China. This is conducive to curbing land desertification and ensuring regional ecological security. Minqin County, Gansu Province, located in northwestern China, is one of the most serious areas of land desertification, which is also one of the four sandstorm sources in China. Based on ENVINet5, this paper constructs a high-precision land desertification identification method with an accuracy of 93.71%, which analyzes the trend and reasons of land desertification in this area, provides suggestions for disaster prevention in Minqin County. and provides a reference for other similar areas to make corresponding desertification control policies.
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页数：18
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