The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics

1997 ◽  
Vol 24 (3) ◽  
pp. 323-343 ◽  
Author(s):  
R White ◽  
G Engelen ◽  
I Uljee
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Cellular Automata ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Dynamics

Using neural networks and cellular automata for modelling intra‐urban land‐use dynamics

2008 ◽  
Vol 22 (9) ◽  
pp. 943-963 ◽  
Author(s):  
C. M. Almeida ◽  
J. M. Gleriani ◽  
E. F. Castejon ◽  
B. S. Soares‐Filho
Keyword(s):  
Neural Networks ◽  
Land Use ◽  
Cellular Automata ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Dynamics

scholarly journals Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation

2003 ◽  
Vol 27 (5) ◽  
pp. 481-509 ◽  
Author(s):  
Cláudia Maria de Almeida ◽  
Michael Batty ◽  
Antonio Miguel Vieira Monteiro ◽  
Gilberto Câmara ◽  
Britaldo Silveira Soares-Filho ◽  
...  
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Urban Land ◽  
Urban Land Use ◽  
Stochastic Cellular Automata ◽  
Land Use Dynamics

scholarly journals Multi-Scenario Prediction of Intra-Urban Land Use Change Using a Cellular Automata-Random Forest Model

2021 ◽  
Vol 10 (8) ◽  
pp. 503
Author(s):  
Hang Liu ◽  
Riken Homma ◽  
Qiang Liu ◽  
Congying Fang
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Land ◽  
Urban Land Use ◽  
Random Forest Model ◽  
Growth Trend ◽  
Related Factors ◽  
Forest Model

The simulation of future land use can provide decision support for urban planners and decision makers, which is important for sustainable urban development. Using a cellular automata-random forest model, we considered two scenarios to predict intra-land use changes in Kumamoto City from 2018 to 2030: an unconstrained development scenario, and a planning-constrained development scenario that considers disaster-related factors. The random forest was used to calculate the transition probabilities and the importance of driving factors, and cellular automata were used for future land use prediction. The results show that disaster-related factors greatly influence land vacancy, while urban planning factors are more important for medium high-rise residential, commercial, and public facilities. Under the unconstrained development scenario, urban land use tends towards spatially disordered growth in the total amount of steady growth, with the largest increase in low-rise residential areas. Under the planning-constrained development scenario that considers disaster-related factors, the urban land area will continue to grow, albeit slowly and with a compact growth trend. This study provides planners with information on the relevant trends in different scenarios of land use change in Kumamoto City. Furthermore, it provides a reference for Kumamoto City’s future post-disaster recovery and reconstruction planning.

scholarly journals Applications of GIS and Very High-Resolution RS Data for Urban Land Use Change Studies in Mongolia

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
D. Amarsaikhan ◽  
V. Battsengel ◽  
E. Egshiglen ◽  
R. Gantuya ◽  
D. Enkhjargal
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Large Scale ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Capital City ◽  
Geographical Information ◽  
Topographic Map

The aim of this study is to analyze the urban land use changes occurred in the central part of Ulaanbaatar, the capital city of Mongolia, from 1930 to 2008 with a 10-year interval using geographical information system (GIS) and very high-resolution remote sensing (RS) data sets. As data sources, a large-scale topographic map, panchromatic and multispectral Quickbird images, and TerraSAR synthetic aperture radar (SAR) data are used. The primary urban land use database is developed using the topographic map of the study area and historical data about buildings. To extract updated land use information from the RS images, Quickbird and TerraSAR images are fused. For the fusion, ordinary and special image fusion techniques are used and the results are compared. For the final land use change analysis and RS image processing, ArcGIS and Erdas imagine systems installed in a PC environment are used. Overall, the study demonstrates that within the last few decades the central part of Ulaanbaatar city is urbanized very rapidly and became very dense.

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