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Aiming to research the data mining technology in remote sensing monitoring. The LM algorithm was used in the soil surface layer (about 1cm) of soil moisture measurement (soil moisture content, SMC). Three kinds of soil, including yellow spongy, loess and red clay were selected. The soil water content samples of 0, 6%, 10%, 14%, 18% and 22% were prepared respectively. Visible light images were taken during 09:00—10:00 and 15:00—16:00, and image brightness was gradiently processed for simulating the change of light throughout the day. LM algorithm was compared with back propagation (BP) algorithm and classification and regression trees (CART) algorithm to verify the practical effect of LM. It was showed that the LM algorithm had a good application effect for the data mining based on the RGB color moment of soil pictures. The determination coefficient of the regression model for yellow spongy, loess and red clay was 0.958, 0.943 and 0.949, root mean square error (RMSE) was 1.6%, 2.0% and 1.9%, and the relative analysis error (RPD) was 4.873, 4.183 and 4.440, respectively. By the study of pictures at different intensities, LM algorithm can be used for monitoring soil moisture content of samples. It can be used for the soil surface (about 1cm) moisture content measurement.