[1]LI Juan,CHEN Chao,WANG Zhao.Inversion of High Spectral Characteristics of Soil Salt in Arid Area Based on Different Transform Forms[J].Research of Soil and Water Conservation,2018,25(01):197-201.
Copy
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
25
Number of periods:
2018 01
Page number:
197-201
Column:
Public date:
2018-02-28
- Title:
-
Inversion of High Spectral Characteristics of Soil Salt in Arid Area Based on Different Transform Forms
- Author(s):
-
LI Juan1,2,3, CHEN Chao1,2, WANG Zhao1,2
-
1. Shaanxi Province Land Engineering Construction Group, Xi’an 710075, China;
2. College of Forestry, Northwest A & F University, Yangling, Shaanxi 712100, China;
3. Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Land and Resources, Xi’an 710075, China
-
- Keywords:
-
electrical conductivity; soil salt content; hyperspectral; inversion accuracy; soil
- CLC:
-
TP701;S127
- DOI:
-
-
- Abstract:
-
Studying on the high spectral features of soil salinization in arid areas, analyzing and illuminating the impact factors and transform model of the precision of high spectral is of great significance to the prediction of the degree of soil salinization. The study was conducted in the saline-alkali soil in Dingbian of Shaanxi Province. Hyperspectral data of soils were obtained. The total salt content (St) and electrical conductivity (EC1:5) of soil were measured with a soil:solution ratio of 1:5 (EC1:5). Relationships between St and EC1:5 were studied under the same tillage pattern, fertilization and irrigation. Correlations between hyperspectral indices and St and EC1:5, were analyzed. The inversion accuracy of St using hyperspectral technique was compared with that of EC1:5. The results showed that the significant positive relationship was found between St and EC1:5 (R2=0.96). The correlation between EC1:5 and continuum removal was better than St, especially in the sensitive bands (λ between 350 nm and 1 000 nm). The coefficient and mean square root of the partial least squares regression model which was determined by EC1:5 were better than those determined by St. Therefore, the responses of high spectral information to St were more sensitive than those of high spectral information to EC1:5. Accuracy of St predicted by high spectral was higher than EC1:5. The results of this study can provide a theoretical basis for improving hyperspectral remote sensing monitoring accuracy of soil salinization.