Spectral Response of Different Eroded Soils in Subtropical China: A Case Study in Changting County, China Spectral Response of Different Eroded Soils in Subtropical China: A Case Study in Changting County, China

最小化 最大化

Vol11 No.3: 697-707

Title】Spectral Response of Different Eroded Soils in Subtropical China: A Case Study in Changting County, China

Author】LIN Chen1, ZHOU Sheng-lu2*, WU Shao-hua2, ZHU Qing1, DANG Qi3

Addresses】1 State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; 2 Department of Land Resources and Tourism Sciences School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China ; 3 State Key Laboratory of Soil and Sustainable Agriculture, Nanjing Insti-tute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China

Corresponding author】zhousl@nju.edu.cn; Tel: +86-25-86882169; First author, e-mail: clin@niglas.ac.cn

Citation】Lin C, Zhou SL, Wu SH et al. (2014) Spectral response of different eroded soils of subtropical in China: a case study in Changting County, China. Journal of Mountain Science 11(3). DOI: 10.1007/s11629-013-2780-8


Abstract】Hyper-spectral data is widely used to determine soil properties. However, few studies have explored the soil spectral characteristics as response to soil erosion. This study analysed the spectral response of different eroded soils in subtropical China, and then identify the spectral characteristics and soil properties that better discriminate soils with different erosion degrees. Two methods were compared: direct identification by inherent spectral characteristics and indirect identification by predictions of critical soil properties. Results showed that the spectral curves for different degrees of erosion were similar in morphology, while overall reflectance and characteristics of specific absorption peaks were different. When the first method is applied, some differences among different eroded groups were found by integration of associated indicators. However, the index of such indicators showed apparent mixing and crossover among different groups, which reduced the accuracy of identification. For the second method, the correlation between critical soil properties, such as soil organic matter (SOM), iron and aluminium oxides and reflectance spectra, was analysed. The correlation coefficients for the moderate eroded group were primarily between −0.3 to −0.5, which were worse than the other two groups. However, the maximum value of R2 was obtained as 0.86 and 0.94 for the non-apparent eroded and the severe group. Furthermore, these two groups also showed some differences in the spectral response of iron complex state (Fep), Aluminium amorphous state (Alo) and the modelling results for soil organic matter (SOM). The study proved that it is feasible to identify different degrees of soil erosion by hyper-spectral data, and that indirect identification by modelling critical soil properties and reflectance spectra is much better than direct identification. These results indicate that hyper-spectral data may represent a promising tool in monitoring and modelling soil erosion.

Keywords】Soil erosion; Erosion degree; Hyper-spectral; Aluminium oxides; Iron oxide; SOM