A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing
Soil moisture is essential parameter in the Earth’s surface. The information provided by soil moisture plays a vital role in agricultural production, eco-environmental protection, water and land resources management, etc. Meanwhile, the accurate monitoring of the spatial and temporal distribution of...
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| Format: | Article |
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MDPI AG
2023-10-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/21/3757 |
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| author | Yuxuan Wang Hongli Zhao Jinghui Fan Chuan Wang Xinyang Ji Dingjian Jin Jianping Chen |
| author_facet | Yuxuan Wang Hongli Zhao Jinghui Fan Chuan Wang Xinyang Ji Dingjian Jin Jianping Chen |
| author_sort | Yuxuan Wang |
| collection | DOAJ |
| description | Soil moisture is essential parameter in the Earth’s surface. The information provided by soil moisture plays a vital role in agricultural production, eco-environmental protection, water and land resources management, etc. Meanwhile, the accurate monitoring of the spatial and temporal distribution of soil moisture is of great significance for the engineering geological assessment and geological disaster prevention. Monitoring and retrieving soil moisture via remote sensing data and mathematical models are the main research methods at present and the crucial issue is how to eliminate the influence of other surface and soil parameters like roughness and soil bulk density, and the interference of vegetated areas to electromagnetic waves. Nowadays, many branches of retrieval methods have been developed, and researchers are integrating multiple models to improve the retrieval accuracy. This paper summarizes the present research status and progress of soil moisture retrieval via remote sensing based on four kinds of models: empirical model, semi-empirical model, physical model, and machine learning. The soil moisture products are summarized and listed at the same time. The difficulties and issues in the present research are discussed and the future outlook is explored. |
| first_indexed | 2024-03-11T11:19:13Z |
| format | Article |
| id | doaj.art-320c5b56f28945e382e6fafbba18ce7c |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T11:19:13Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-320c5b56f28945e382e6fafbba18ce7c2023-11-10T15:15:14ZengMDPI AGWater2073-44412023-10-011521375710.3390/w15213757A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote SensingYuxuan Wang0Hongli Zhao1Jinghui Fan2Chuan Wang3Xinyang Ji4Dingjian Jin5Jianping Chen6China Aero Geophysical Survey and Remote Sensing Center for Natural Resources (AGRS), Beijing 100083, ChinaChina Aero Geophysical Survey and Remote Sensing Center for Natural Resources (AGRS), Beijing 100083, ChinaSchool of Earth Science and Resources, China University of Geoscience (CUGB), Beijing 100083, ChinaTwenty First Century Aerospace Technology Co., Ltd., Beijing 100096, ChinaSchool of Earth Science and Resources, China University of Geoscience (CUGB), Beijing 100083, ChinaSchool of Earth Science and Resources, China University of Geoscience (CUGB), Beijing 100083, ChinaSchool of Earth Science and Resources, China University of Geoscience (CUGB), Beijing 100083, ChinaSoil moisture is essential parameter in the Earth’s surface. The information provided by soil moisture plays a vital role in agricultural production, eco-environmental protection, water and land resources management, etc. Meanwhile, the accurate monitoring of the spatial and temporal distribution of soil moisture is of great significance for the engineering geological assessment and geological disaster prevention. Monitoring and retrieving soil moisture via remote sensing data and mathematical models are the main research methods at present and the crucial issue is how to eliminate the influence of other surface and soil parameters like roughness and soil bulk density, and the interference of vegetated areas to electromagnetic waves. Nowadays, many branches of retrieval methods have been developed, and researchers are integrating multiple models to improve the retrieval accuracy. This paper summarizes the present research status and progress of soil moisture retrieval via remote sensing based on four kinds of models: empirical model, semi-empirical model, physical model, and machine learning. The soil moisture products are summarized and listed at the same time. The difficulties and issues in the present research are discussed and the future outlook is explored.https://www.mdpi.com/2073-4441/15/21/3757soil moistureremote sensingmodelretrieval methods |
| spellingShingle | Yuxuan Wang Hongli Zhao Jinghui Fan Chuan Wang Xinyang Ji Dingjian Jin Jianping Chen A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing Water soil moisture remote sensing model retrieval methods |
| title | A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing |
| title_full | A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing |
| title_fullStr | A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing |
| title_full_unstemmed | A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing |
| title_short | A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing |
| title_sort | review of earth s surface soil moisture retrieval models via remote sensing |
| topic | soil moisture remote sensing model retrieval methods |
| url | https://www.mdpi.com/2073-4441/15/21/3757 |
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