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GeoCA

Geographical Simulation Application via Cellular Automata (GeoCA)

GeoCA is a free software for the simulation and prediction of a large-scale pixel-based urban development process.

GeoCA has been well applied in the fields of urban development process analysis, urban ecological environment analysis and urban planning.

GeoCA supports multi-rule mining models, multi-spatial variable processing, geographic location alignment, and automatic memory control for large-scale urban development simulation.

Important Notes:

Please download all GeoCA_V2.4.z01 ~ GeoCA_V2.4.z04 and GeoCA_V2.4.zip files before decompressing them, there are test data and executable files inside.

Please unzip the program to the full English file path. Double-click “GeoCA_UI.exe” in the program directory to start the GeoCA program.

If you encounter a program error, please install Microsoft Visual C++ 2015 Redistributable.

GeoCA is developed by the following laboratory:

High-Performance Spatial Computational Intelligence Laboratory,

School of Geography and Information Engineering,

China University of Geosciences, Wuhan, China.

Urban simulation algorithm developers:

Yao Yao, China University of Geosciences, Wuhan, China.

Guangzhao Chen, Sun Yat-sen University, Guangzhou, China.

Jinbao Zhang, Sun Yat-sen University, Guangzhou, China.

Xun Liang, China University of Geosciences, Wuhan, China.

Dongsheng Chen, Wuhan University, Wuhan, China.

Dachuan Zhang, Sun Yat-sen University, Guangzhou, China.

Hongzhi Cui, Chinese Academy of Sciences, Beijing, China.

High-performance computing platform developers:

Qingfeng Guan, China University of Geosciences, Wuhan, China.

Xiang Liu, China Aerospace Science and Technology Corporation, Beijing.

Yao Yao, China University of Geosciences, Wuhan, China.

Jinbao Zhang, Sun Yat-sen University, Guangzhou, China.

Penghua Liu, Alibaba Group, Hangzhou, China.

Zhewei Liang, China University of Geosciences, Wuhan, China.

User interface developers:

Yao Yao, China University of Geosciences, Wuhan, China.

Zhenhui Sun, China University of Geosciences, Wuhan, China.

Related references:

[1] Chen, D., Zhang, Y., Yao, Y., Hong, Y., Guan, Q., & Tu, W. (2019). Exploring the spatial differentiation of urbanization on two sides of the Hu Huanyong Line–based on nighttime light data and cellular automata. Applied Geography, 112, 102081.

[2] Zhang, D., Liu, X., Wu, X., Yao, Y., Wu, X., & Chen, Y. (2019). Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng, China. GIScience & Remote Sensing, 56(2), 282-308.

[3] Yao, Y., Liu, X., Zhang, D., Liang, Z., & Zhang, Y. (2017). Simulation of Urban Expansion and Farmland Loss in China by Integrating Cellular Automata and Random Forest. arXiv preprint arXiv:1705.05651.

[4] He, Y., Ai, B., Yao, Y., & Zhong, F. (2015). Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images. International Journal of Applied Earth Observation and Geoinformation, 38, 164-174.

[5] Li, X., & Yeh, A. G. O. (2002). Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 16(4), 323-343.

geoca's People

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