Improving soil organic carbon mapping in farmlands using machine learning models and complex cropping system information
Jianxiong Ou,
Zihao Wu,
Qingwu Yan
et al.
Abstract:Obtaining accurate spatial maps of soil organic carbon (SOC) in farmlands is crucial for assessing soil quality and achieving precision agriculture. The cropping system is an important factor that affects the soil carbon cycle in farmlands, and different agricultural managements under different cropping systems lead to spatial heterogeneity of SOC. However, current research often ignores differences in the main controlling factors of SOC under different cropping systems, especially when the cropping pattern is… Show more
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