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A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675757/ https://www.ncbi.nlm.nih.gov/pubmed/38005560 http://dx.doi.org/10.3390/s23229173 |
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author | Yang, Jingyi Wang, Qinjun Chang, Dingkun Xu, Wentao Yuan, Boqi |
author_facet | Yang, Jingyi Wang, Qinjun Chang, Dingkun Xu, Wentao Yuan, Boqi |
author_sort | Yang, Jingyi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10675757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106757572023-11-14 A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 Yang, Jingyi Wang, Qinjun Chang, Dingkun Xu, Wentao Yuan, Boqi Sensors (Basel) Article 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. MDPI 2023-11-14 /pmc/articles/PMC10675757/ /pubmed/38005560 http://dx.doi.org/10.3390/s23229173 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yang, Jingyi Wang, Qinjun Chang, Dingkun Xu, Wentao Yuan, Boqi A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 |
title | A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 |
title_full | A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 |
title_fullStr | A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 |
title_full_unstemmed | A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 |
title_short | A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5 |
title_sort | high-precision remote sensing identification method for land desertification based on envinet5 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675757/ https://www.ncbi.nlm.nih.gov/pubmed/38005560 http://dx.doi.org/10.3390/s23229173 |
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