Mapping soil organic carbon stock by hyperspectral and time-series multispectral remote sensing images in low-relief agricultural areas

• Published in: Geoderma Vol. 398; p. 115118
• Main Authors: Guo, Long, Sun, Xiaoru, Fu, Peng, Shi, Tiezhu, Dang, Lina, Chen, Yiyun, Linderman, M., Zhang, Ganlin, Zhang, Yu, Jiang, Qinghu, Zhang, Haitao, Zeng, Chen
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.09.2021
• Subjects: agricultural land; agricultural management; Airborne hyperspectral imaging; carbon cycle; carbon sinks; Collaborative verification; Digital soil mapping; global carbon budget; hyperspectral imagery; Iowa; irrigation; land use; Landsat; landscapes; least squares; model validation; prediction; soil density; soil formation; soil organic carbon; Spatial distribution patterns; spatial variation; tillage; time series analysis; Time-series multispectral remote sensing images; Iowa; Airborne hyperspectral imaging; Digital soil mapping; Spatial distribution patterns; Time-series multispectral remote sensing images; Collaborative verification

[Display omitted] •One new collaborative verification strategy was used for verifying soil map.•The hyperspectral and time series multispectral images were used for soil mapping.•The semivariogram and percentage errors were used for collaborative verification.•The time series multispectral images we...