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A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5.
Yang, Jingyi; Wang, Qinjun; Chang, Dingkun; Xu, Wentao; Yuan, Boqi.
  • Yang J; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), Beijing 100094, China.
  • Wang Q; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.
  • Chang D; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Xu W; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), Beijing 100094, China.
  • Yuan B; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.
Sensors (Basel) ; 23(22)2023 Nov 14.
Article en En | MEDLINE | ID: mdl-38005560
ABSTRACT
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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