Abstract:The quantitative inversion of soil organic carbon (Corg) in the study area is conducted by using multiple stepwise regression analysis method in combination with Landsat8 OLI remote sensing data. For the test, 164 soil samples are collected. Singular points are removed and data sets are divided by tripled standard deviation. Among the total, 120 samples are chosen as the training set and the other 44 as the validation set to establish the multiple stepwise regression prediction model for Corg. The results show that the organic carbon is significantly correlated with the reflectivity of Landsat8 bands. The optimal model for the prediction of black soil organic carbon spectrum is the one that takes the reciprocal as the independent variable, with the determination coefficient R2=0.180, and root-mean-square error(RMSE)=0.558. Hailun area is suitable for remote sensing inversion of Corg content, with a stable prediction model, which can be used to reveal the spatial distribution of Corg content in typical black soil areas. Meanwhile, it is believed that without ground spectral test for the soil, the fitting degree of prediction model by simply using the method of associating chemical analysis data with remote sensing satellite is limited and the interpretation of Corg by spectrum is poor.
杨佳佳, 林楠, 于秀秀, 吴梦红, 王洋. 东北典型黑土区有机碳遥感定量反演研究[J]. 地质与资源, 2020, 29(4): 357-362.
YANG Jia-jia, LIN Nan, YU Xiu-xiu, WU Meng-hong, WANG Yang. STUDY ON QUANTITATIVE INVERSION OF REMOTE SENSING FOR ORGANIC CARBON IN THE TYPICAL BLACK SOIL AREAS OF NORTHEAST CHINA. GEOLOGY AND RESOURCES, 2020, 29(4): 357-362.
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