Soil Organic Matter Content Retrieval from Hyperspectral Remote Sensing in Western Jilin, China

The analysis and forecast of the distribution and dynamics of soil organic matter (SOM) content is an essential requirement for sustainable land management, especially in Western Jilin, where the saline-alkalized land increased at a very fast rate per year and is in desperate need of improving soil. Compared to conventional analytical methods, hyperspectral remote sensing is faster, cheaper, non-destructive and has the potential to analyze various soil properties simultaneously, such as soil carbon, soil organic matter, and various other soil properties . A number of linear and nonlinear models have been developed for determining the soil properties on soil spectra with different accuracy . In this study, more interest was laid in detecting the sensitive bands position of SOM and a particular algorithm spectroscopists had been using was introduced and adapted to remote sensing spectral analysis successfully. Finally, a simple stepwise multiple linear regression analysis was used to produce the prediction model.