Modeling the spatial distribution of crop cultivated areas at a large regional scale combining system dynamics and a modified Dyna-CLUE: A case from Iran

Abstract

Agricultural land use pattern is affected by many factors at different scales and effects that are separated by time and space. This will lead to simulation models that optimize or project the cropping pattern changes and incorporate complexities in terms of details and dynamics. Combining System Dynamics (SD) and a modified Conversion of Land Use and its Effects (CLUE) modelling framework, this paper suggests a new dynamic approach for assessing the demand of different crops at country-level and for predicting the spatial distribution of cultivated areas at provincial scale. As example, a case study is presented for Iran, where we have simulated a scenario of future cropping pattern changes during 2015-2040. The results indicated a change in the spatial distribution of cultivated areas during the next years. An increase in the proportion of rice is expected in northern Iran, whereas the proportion of wheat is increasing in the mountainous western areas. Wheat and barley crops are expected to become dominant within the cropping system throughout the country regions.

Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian

“…In order to reveal the evolution of urban land use, scholars have proposed many models. At present, mature models include the CLUE-S model [9], SD (system dynamics) model [10], CA (cellular automata) model [11][12][13], and geocellular automata model [14][15][16][17]. Among them, the CA model follows a bottom-up approach, which is very consistent with human understanding of the dynamic variation process of urban land use.…”