Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

Sensors

Lixin Lin¹  Yunjia Wang¹  Jiyao Teng¹  Xiuxiu Xi¹ 

[1] School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China; E-Mails:

关键词: hyperspectral reflectance;    ASD FieldSpec spectroradiometers;    local correlation maximization-complementary superiority;    soil total nitrogen;    subsided land;   

DOI  :  10.3390/s150817990

来源: mdpi

【 摘 要 】

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]′), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.