Agent-based modelling and assessment of human-environment interactions

更好地了解人与环境的相互作用，特别是土地使用者的决策过程，是探讨应对气候变化的可能战略和改进土地利用规划的关键必要条件。到目前为止，土地系统模型主要以土地面积为主要分析单位，并没有明确表示土地使用者的决策。因此，在第二代土地系统模型中，注意力将从像素转移到代理人。当建立所谓的多主体模型时，挑战变成了现实地代表个人的土地使用决定，特别是适应气候变化的决定。要考虑的因素是技术采用、学习和应对风险的选择，以及空间互动。另一个挑战是将多智能体模型与陆地-地表-大气模型，特别是在详细空间尺度上的作物生长模型相结合，这一点尚未实现。本项目的主要科学目标是为整个土地系统模型开发基于代理的模型组件。该项目在单个农场一级的微观经济模拟和景观一级的生物物理模拟之间发挥了联系作用。

A better understanding of human-environment interactions and especially of land users’ decision- making processes is a key requisite for exploring possible coping strategies to climate change and for improving land use planning. So far, land system models have focused on land areas as the main unit of analysis and have not represented the decision-making of land users explicitly. Within the second generation of land system models, attention will therefore shift from pixels to agents. When building so-called multi-agent models, the challenge becomes to realistically represent individual land-use decisions and especially the adaptation to climate change. Factors to be considered are options for technology adoption, learning and risk-coping, and spatial interaction. Another challenge is the integration of multi-agent models with land-surfaceatmosphere models and especially crop growth models at detailed spatial scales, which has not yet been achieved. The major scientific goal of this project is to develop the agent-based model component for the overall land system model. The project fulfills a linking role between the microeconomic modelling at the individual farm level and the biophysical modelling at the landscape level.