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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liang Pei Xin Ye Jiaqiang Ren |
| Copyright Year | 2010 |
| Description | Author affiliation: College of geomatics, Liaoning Technical University, Fuxin, China (Liang Pei; Xin Ye) || College of Land and Environment Science, Shenyang Agricultural University, Shenyang, P.R. China (Jiaqiang Ren) |
| Abstract | The analysis of Land-use change trends and its driving forces is one of the hot issues of global change research, the core of research is how to forecast the tendency of land-use change reasonably and accurately. The dynamic land-use change is very complicated, the traditional GIS method can solve part of the spatial correlation problem well, but it is hard to simulate complex dynamics in spatial and temporal change of geographical phenomena. Cellular automata (CA) is a kind of "bottom-up" dynamic simulation modeling framework, whose time, space, states are discrete, and it is a space time interaction and causal relationships for the local dynamic model of grid, and has an ability to simulate spatial and temporal evolution of complex systems. CA model that integrated with GIS will improve the environment of CA simulation and make the results of the simulation analysis more accurate. This paper take Jinzhou of Liaoning Province as an example, we study the land use status of the research region based on land use data and economic data and achieve the main direction of land use change in the last few years, which can provided a basis for establishing a CA model. Then taking the TM image data in the years of 00 and 07 as the basic and test data to debug, evaluate and test the parameters of the CA model. Finally the model could be predicted on the land use state of the research area in 2015. The results of experiment showed that the CA model can simulate complex land use structure accurately through simple local transition rules. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 332240 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424473014 |
| e-ISBN | 9781424473038 |
| DOI | 10.1109/GEOINFORMATICS.2010.5568050 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | GIS Analytical models Geographic Information Systems Biological system modeling CA model Automata Land use change Predictive models Data models Construction industry |
| Content Type | Text |
| Resource Type | Article |
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