Ji, Wenjun
- Zhejiang University
Research article2013Peer reviewed
Guo Yan; Ji Wen-jun; Wu Hong-hai; Shi Zhou
The results indicated that good model was modeling from the characteristic bands (CB, R-2 = 0. 91, RPD=3. 28) of correlation coefficient more than 0. 5, the spectral index (SI) of normalized difference index (NDI, R-2 = 0. 90,RPD=3. 08), CB integrating SI with which a correlation coefficient was more than 0. 5 (R-2 =0. 87,RPD=2. 67), and total bands (TA, 400 similar to 2 450 nm, R-2 = 0. 95,RPD=4. 36). While the digital mapping of SOM produced by kriging and cokriging interpolation methods implied a better prediction result, showing similar spatial distribution with the measured SOM, indicating that it is feasible and reliable to use these spectral indices to predict and map the spatial variability.
Visible-near infrared(Vis-NIR) reflectance spectroscopy; ASD FieldSpec Pro FR spectrometer; Soil organic matter (SOM); Prediction and mapping; Partial Least Squares Regression(PLSR); Geostatistics
Guangpuxue Yu Guangpu Fenxi/Spectroscopy and Spectral Analysis
2013, volume: 33, number: 4, pages: 1135-1140
Publisher: OFFICE SPECTROSCOPY & SPECTRAL ANALYSIS
Soil Science
https://res.slu.se/id/publ/83446