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3 November 2008 An improved cellular automata forecasting model for urban land use spatial structure changes
Yan Wang, Peilin Wu, Zhenbai Song, Junru Cao
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Proceedings Volume 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments; 714310 (2008) https://doi.org/10.1117/12.812560
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
Though the urban land use spatial dynamic simulation and forecasting based on cellular automata (CA) model have achieved remarkable progress, the CA model still has some problems and drawbacks in forecasting urban land use changes. In view of the deficiencies of traditional urban CA, an improved CA model based on spatial dynamic data mining and random forecast is proposed in this paper, which establishes an operable CA method to forecast and simulate the discrete status attribute. This improved CA model is examined in analyzing the urban land use structure changes in Jinan 2002-2006 and testified both feasible and effective. Based on the remote sensing images in Jinan 2002 and 2006, the urban land use spatial structures are classified into five types, commercial land, residential land, education facility, industrial land and the other. With the improved CA model, the urban land use framework in Jinan in 2010 was calculated, the result of which can be used as a reliable reference information for the following urban land use planning.
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Yan Wang, Peilin Wu, Zhenbai Song, and Junru Cao "An improved cellular automata forecasting model for urban land use spatial structure changes", Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 714310 (3 November 2008); https://doi.org/10.1117/12.812560
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KEYWORDS
Mining
Data mining
Geographic information systems
Data modeling
Remote sensing
Calcium
Data processing
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