Search

The purpose of this paper is to study the feasibility of real-time monitoring soil total nitrogen(TN), total phosphorus(TP) and total potassium(TK) in large area by using Hyperspectral Remote Sensing technology. Based on the combined methods of field investigation and indoor data from hyperspectral measurement(350-2 500 nm), the soils in four counties(zhaoyuan county, zhaozhou county, dumeng county, and lindian county), and daqing urban area, Heilongjiang province were studied and analyzed for the characteristics of soil spectrum and soil nutrient index. The variation in soil spectral reflectance was calculated in the form of first-order differential(R)′, reciprocal(1/R), reciprocal first-order differential(1/R)′, logarithm(log R) and so on. Then the estimating models of TN, TP and TK were established by unary linear regression(ULR), multivariate linear regression(MLR) and partial least squares(PLSR), and calibration model is verified by independent samples. The results showed that the optimum absorption bands of TN, TP and TK were TN(802 nm, 1 108 nm), TP(784 nm, 1 085 nm), TK(1 079 nm, 1 578 nm), respectively, the precision of partial least squares(PLSR) was higher than that of Multivariate linear regression(MLR) model and unary linear regression model(ULR), which were TN(R2 = 0.831, RMSE = 2.506 g/kg), TP( R2 = 0.687, RMSE = 0.844 g/kg), TK(R2 = 0.832, RMSE = 0.097 g/kg). The prediction accuracy of TN and TK was higher, while the prediction result of TP was relatively lower, but it can also be used for rough estimation. Meanwhile, MODIS images were used to map the concentrations of TN, TP and TK in soil. This study confirmed that hyperspectral technology combined with specific algorithms can better predict the concentrations of TN, TP and TK in soils with larger differences, and the visualization of predictive information can be realized. It is of great practical significance for real-time and rapidly monitoring large-scale changes in soil environment, predicting the trend of soil information changes, monitoring ecological environment, establishing soil nutrient database in China and reducing the monitoring cost of soil composition. [ABSTRACT FROM AUTHOR]