Hyperspectral Detection Model for Soil Dispersion in Zhouqu Debris Flow Source Region

• Published in: Guang pu xue yu guang pu fen xi Vol. 36; no. 2; p. 502
• Main Authors: Wang, Qin-jun, Wei, Yong-ming, Chen, Yu, Chen, Jia-ge, Lin, Qi-zhong
• Format: Journal Article
• Language: Chinese
• Published: China 01.02.2016
• ISSN: 1000-0593
• DOI: 10.3964/j.issn.1000-0593(2016)02-0502-09

Sensitive band positions, models and the principles of soil dispersion detected by hyperspectral remote sensing were firstly discussed according to the results of soil dispersive hyperspectral remote sensing experiment. Results showed that, (1) signals and noises could be separated by Fourier transformation. A finely mineral identification system was developed to remove spectral noises and provide highly accurate data for establishing soil dispersive model; (2) Soil dispersive hyperspectral remote sensing model established by the multiple linear regression method was good at soil dispersion forecasting for the high correlation between sensitive bands and the soil dispersions. (3) According to mineral spectra, soil minerals and their absorbed irons were reflected by sensitive bands which revealed reasons causing soils to be dispersive. Sodium was the closest iron correlated with soil dispersion. The secondary was calcite, montmorillonite and illite. However, the correlation between soil dispersion and chlorite