A modeling approach for accurately predicting land use changes brought by human decisions

到目前为止，该项目取得了三项主要成果。第一，成功实施了Ifugao水稻梯田世界遗产景观的实地考察工作。农民、政府官员和学术专家就导致农业废弃的因素进行了采访。其次，建立了农业废弃统计模型。所开发的统计模型根据解释变量的过去趋势确定了农业废弃的空间和非空间驱动因素。第三，开发了一个基于智能体的模型，基于政策情景模拟了Ifugao水稻梯田的未来状况。该模型综合了实地调查和统计模型中收集到的社会环境驱动因素。

So far, the project has three main achievements. First, fieldwork in the world heritage landscape of Ifugao rice terraces was successfully implemented. Farmers, government officials, and academic experts were interviewed regarding the factors that lead to agricultural abandonment. Second, a statistical model of agricultural abandonment was developed. The developed statistical model identified the spatial and non-spatial driving factors of agricultural abandonment based on past trends of explanatory variables. Third, an agent-based model was developed that simulates the future status of the Ifugao rice terraces based on policy scenarios. The social-environment driving factors that were gathered from the fieldwork and the statistical model were incorporated in this model.