基于粗集的知识发现与地理模拟——以深圳市土地利用变化为例

doi:10.11821/xb200608011

Abstract

Abstract:

This paper presents a new method to simulate complex land use systems by integrating rough sets (RS), cellular automata, and GIS. Recently, cellular automata (CA) have been increasingly used to simulate urban growth and land use dynamics. Traditional CA models simulate urban development with static transition rules in large areas. Most of them are expressed by mathematical formulas and the transition rules are fixed. These models have limitations to simulate complex land use change. The transition rules should be subject to uncertainties and they should vary spatially. In this study, a CA model based on rough sets is developed using Visual Basic and ArcObjects of GIS. The GIS provides both data and spatial analysis functions for constructing RS-CA model. Training data are conveniently retrieved from remote sensing and GIS database for calibrating and testing the model. The rough sets method is used to obtain the uncertainty and dynamic transition rules. The RS-CA model can be applied to the simulation of urban development. Complex global patterns can be generated from the local interactions with the RS-CA model. This paper demonstrates that the proposed model can overcome some of the shortcomings of the existing CA models in simulating complex urban systems by using the rough set method. The model has been successfully applied to the simulation of urban development in Shenzhen city of the Pearl River Delta.

Key words: cellular automata, rough sets, uncertainty, urban simulation, Shenzhen city

YANG Qingsheng, LI Xia. Mining Transition Rules for Geo-simulation Using Rough Sets[J].Acta Geographica Sinica, 2006, 61(8): 882-894.

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Mining Transition Rules for Geo-simulation Using Rough Sets

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