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 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.

Automated summary

Soil moisture plays a crucial role in agricultural production, eco-environmental protection, water and land resources management, etc. Remote sensing data and mathematical models are the main research methods for monitoring and retrieving soil moisture, but the interference from surface and soil parameters as well as vegetated areas needs to be addressed.