A Method of Soil Moisture Content Estimation at Various Soil Organic Matter Conditions Based on Soil Reflectance

Soil moisture is one of the most important components of all the soil properties affecting the global hydrologic cycle. Optical remote sensing technology is one of the main parts of soil moisture estimation. In this study, we promote a soil moisture-estimating method with applications regarding various soil organic matters. The results indicate that the soil organic matter had a significant spectral feature at wavelengths larger than 900 nm. The existence of soil organic matter would lead to darker soil, and this feature was similar to the soil moisture. Meanwhile, the effect of the soil organic matter on its reflectance overlaps with the effect of soil moisture on its reflected spectrum. This can lead to the underestimation of the soil moisture content, with an MRE of 21.87%. To reduce this effect, the absorption of the soil organic matter was considered based on the Lambert-Beer law. Then, we established an SMCg-estimating model based on the radiative transform theory while considering the effect of the soil organic matter. The results showed that the effect of the soil organic matter can be effectively reduced and the accuracy of the soil moisture estimation was increased, while MRE decreased from 21.87% to 6.53%.

Automated summary

Soil moisture is an important factor in the global hydrologic cycle, and optical remote sensing technology is widely used for estimating soil moisture. This study focused on the estimation of soil moisture considering the presence of soil organic matter. The results showed that soil organic matter has a significant impact on the spectral features of soil, which can lead to underestimation of soil moisture. By considering the absorption characteristics of soil organic matter and using the radiative transform theory, an improved soil moisture estimation model was proposed, which effectively reduced the influence of soil organic matter and improved the accuracy of soil moisture estimation.