Research on Soil Moisture Retrieval Methods Based on Remote Sensing Data

Soil moisture is an important basic information in agricultural production, as it directly affects the growth and development of crops and can also reflect the soil water status, playing an important role in preventing natural disasters such as droughts and floods. The retrieval of soil moisture involves a variety of algorithms, among which change detection algorithms based on time series data do not require prior information such as surface soil roughness. Methods such as neural networks and support vector machines also offer the advantages of not relying on parameters and having high precision. Therefore, this paper focuses on the retrieval of soil moisture using change detection algorithms as well as machine learning and neural network algorithms. The study analyzes the retrieval accuracy of different algorithms to identify suitable retrieval methods.