Soil erosion often leads to land degradation, agricultural production reduction, and environmental deterioration, which seriously restricts the sustainable development of regions. Clarifying the driving factors of soil erosion is the premise of preventing soil erosion. Given the lack of current research on the driving factors/force changes of soil erosion in different regions or under different erosion intensity grades, this paper pioneered to use machine learning methods to address this problem.

Whereas most contemporary frameworks evaluating land management aspects focus on institutional settings at a national level, the 8R framework of responsible land management aims at evaluating individual land management projects or interventions. This 8R framework is, however, still under development and needs testing, validation and further detailing, such that specific operational characteristics and internal and external effects can be included in the evaluation.

Global environmental governance (GEG) is one of the world’s major attempts to address climate change issues through mitigation and adaptation strategies. Despite a significant improvement in GEG’s structural, human, and financial capital, the global commons are decaying at an unprecedented pace. Among the global commons, land has the largest share in GEG. Land use change, which is rooted in increasing populations and urbanization, has a significant role in greenhouse gas (GHG) emissions.