Retrieval of Organic Matter Content in Black Soil Based on Airborne Hyperspectral Remote Sensing Data: Taking Jiansanjiang District in Heilongjiang Province as an Example

The retrieval of organic matter content in black soil is of great significance for the utilization and conservation of black soil resources. However, the lack of hyperspectral satellite images has restricted the development of soil organic matter retrieval at the regional scale. In this paper, a typical black soil area of Heilongjiang Province was selected as the study area. Then, the CASI/SASI airborne hyperspectral data, ASD(analytical spectral devices) surface spectral data, and the soil organic matter content data are used to establish the optimal regression model based on the correlation and quantitative relationship between organic matter content and spectral reflectance values of soil samples. Finally, the retrieval of soil organic matter content of the study area is carried out. The results show that the partial least square regression model is more stable than the multivariate stepwise regression model (with determination coefficients of 0.885 and 0.653, respectively), and the accuracy is higher (with root mean square error of 0.424 and 0.744, respectively). The retrieval result derived from partial least square regression is basically consistent with the result of geochemical exploration on the ground.