This paper is rouse hyperspectral data to conduct quantitative estimation of saline-alkali soil salinity spectrum on Yellow River Delta, providing a quick, real-time and accurate estimation method for soil salt content.In the Yellow River delta area for research area, based on the change regular analysis of soil spectrum curve, by means of related analysis on the content of soil salt and the transformation of first order differential and the logarithm reciprocal of spectral reflectance, screening sensitivewavelength, it uses principal component regression analysis method to set up the soil salt estimating model, and verifies the model accuracy.The results shown that first order differential transform can expand the difference of spectrum characteristics between samples and improve the correlation; According to the correlation analysis it selects 388nm, 515nm,962nm 1164nm 1623nm and 2150nm as sensitive wavelength; Using principal component regression analysistoestablishthesoilaltestimatingmodely=4.389-798x388”-632x515”-151x862”-184x1164”-138x1623”-217x2150” , by way of the model accuracy verification, the model (R” =0.8405, RMSE=1.152) is good.Principal component regression analysis method is suitable for the estimation soil salt content of the Yellow River delta, providing theoretical basis and technical support to realize the soil salt quantitative estimation.
Saline-alkali soil Hyperspectral data Salinity content Yellow River delta Principal component analysis
Wang Lina Zhu Xicun Liu Qing Zhao Gengxing Li Haiyan Wang Ling Zhang Shengwu
Key Laboratory of Eco-Environmental Science for Yellow River Delta of Shandong Province,Binzhou Univ College of Resources and Environment, Shandong Agricultural University, Tai”an 271018,Shandong, Chin Key Laboratory of Eco-Environmental Science for Yellow River Delta of Shandong Province,Binzhou Univ College of Resources and Environment, Shandong Agricultural University, Tai”an 271018,Shandong, Chin Municipal Bureau of Land Resource of Tai”an City, Tai”an, 271000, Shandong, China