Monitoring regional soil organic matter content using a spatiotemporal model with time-series synthetic Landsat images

• Published in: Geoderma Regional Vol. 34; p. e00702
• Main Authors: Zhang, Mei-Wei, Wang, Xiao-Qing, Ding, Xiao-Gang, Yang, Hua-Lei, Guo, Qian, Zeng, Ling-Tao, Cui, Yu-Pei, Sun, Xiao-Lin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2023
• Subjects: China; differential equation; Digital soil mapping; Google Earth Engine; Internet; Landsat; soil; Soil organic matter; soil surveys; spatial data; Spatiotemporal dynamics; Synthetic Landsat imagery; time series analysis; China; Soil organic matter; Digital soil mapping; Spatiotemporal dynamics; Synthetic Landsat imagery; Google Earth Engine

Accurately monitoring soil organic matter (SOM) content is crucial for food and soil security. Current methods of monitoring are expensive and existing sparse data cannot provide detailed spatial information about SOM content changes in an area. This study proposes using a spatiotemporal model with...