环境科学
土壤科学
含水量
Pedotransfer函数
土壤水分
土壤碳
土壤有机质
作物残渣
遥感
水文学(农业)
地质学
地理
导水率
农业
考古
岩土工程
作者
Xin Dou,Xiang Wang,Huanjun Liu,Xinle Zhang,Linghua Meng,Yue Pan,Ziyang Yu,Yubo Cui
出处
期刊:Geoderma
[Elsevier]
日期:2019-12-01
卷期号:356: 113896-113896
被引量:60
标识
DOI:10.1016/j.geoderma.2019.113896
摘要
Due to confounding factors such as crop residue and soil moisture, soil organic matter (SOM) is usually estimated from soil samples in a laboratory or in the field at a local scale. In this study, laboratory and field data of crop residue, soil moisture, crop management practices, and SOM content were used in concert with multi-temporal MODIS images captured during bare soil periods over three years to construct spectral indices, which were then used as input variables to build a regional-scale SOM prediction model. Results showed that: (1) multi-temporal satellite images can be used to predict SOM content at a regional scale; (2) crop residue cover and time interval between snow melt, rainfall, and ploughing determined the optimal input variables for SOM prediction; (3) compared to a SOM model based on a single image, a multi-temporal model reduced the influence of soil moisture and improved both the stability and the accuracy of SOM prediction; (4) the best models generally used the ratio of MODIS Band 6 and Band 1 (R61) as an input variable, as R61 showed good correlation with SOM and less correlation with moisture; and (5) comparing different models in different years showed that models performed better in years with less crop residue. The study results can be used to improve the accuracy of quantitative estimates of the soil organic carbon pool and provide assistance in digital soil mapping.
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