Estimating and mapping of soil organic matter content in a typical river basin of the Qinghai-Tibet Plateau

被引:3
作者
Yu, Qing [1 ,2 ]
Lu, Hongwei [1 ]
Feng, Wei [1 ,2 ]
Yao, Tianci [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China
关键词
Soil organic matter; land parameters; spatial mapping; reflectance spectroscopy; content estimation; GEOGRAPHICALLY WEIGHTED REGRESSION; INFRARED REFLECTANCE SPECTROSCOPY; ARTIFICIAL NEURAL-NETWORK; LAND-USE CHANGE; NIR SPECTROSCOPY; IN-SITU; CARBON; PREDICTION; VARIABILITY; INDICATORS;
D O I
10.1080/10106049.2021.1871667
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Spectroscopy is a fast, non-destructive, and cheap method, which has been widely used in the estimation of soil organic matter (SOM) concentration. This study presented a methodology to estimate and map SOM content by crop canopy reflectance spectra combining with land parameters in the Yarlung Zangbo River (YZR) basin. The reflectance spectra of the oat canopy were collected in the field, and then were processed by savitzky-golay filtering (S-G), continuous removal (CR), and first derivative of reflectivity (FDR). The principal components were extracted from the processed spectral data. Land parameters such as elevation, slope, NDVI, and land surface temperature (LST) were selected to establish 18 models to estimate SOM content. The results showed that the estimation accuracy of SOM content could be improved by combining crop canopy reflectance spectra with land parameters. FDR-BPNN model with land parameters had the best estimation effect (R-2 = 0.973, MAE = 0.847 g.kg(-1)).
引用
收藏
页码:4088 / 4107
页数:20
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