Abstract: 【Objective】 Crop pattern is a key element in agricultural land systems other than land use and land cover. Crop pattern dynamics take place very frequently, but they are not always easily observable, making many difficulties for analysis. In this paper the authors are trying to conceptualize an agent-based model to simulate crop pattern dynamics at a regional scale (CroPaDy). 【Method】Both of the conceptual model and the computational model of CroPaDy are designed strictly following the ODD Protocol proposed by Grimm et al. (2010) and the Generalized Framework for Parameterization of ABM proposed by Smajgl et al., (2011). 【Result】 The conceptual model of CroPaDy is designed as a closed-loop comprised by driving forces, decision making processes, and consequences. In driving force analysis, the authors focus on the internal and external factors that influencing farmer’s decision-making instead of the macro level biophysical–socioeconomic drivers for land use and land cover change. The state variables are set to be updated annually, incorporating feedbacks in any decision-making circle. The computational model links three sub-models named agents generating module, agent simplifying and classifying module, and agent decision-making module, respectively. Common methods including Monte Carlo and Utility Function are used in model parameterization. In addition, factor analysis is applied for replacing cluster analysis in forming farmer typologies. 【Conclusion】 The authors conceptualize the framework of CroPaDy model to present the interactions between human actors and their environment in agricultural land systems. Crop pattern dynamics, therefore, can be modeled by capturing farmer’s crop choice. However, due to the limited page space, model validation and the scenarios-based application are subjected to a series of companion papers that are about to be submitted independently.

Key words: agent-based modeling , crop choice , crop pattern , model framework