SLEUTH is a modified cellular automata (CA) model which consists of an urban growth sub model and a land cover change transition sub model. The urban growth model is the main component of SLEUTH, which is tightly coupled with the land cover change transition model. This model was chosen to calibrate urban growth in two Asian cities, Chiang Mai (Thailand) and Taipei (Taiwan). These cities are undergoing rapid land use/land cover change as a result of robust economic and population growth. SLEUTH cellular automata model contains characteristics that offer advantages for modelling physical dynamics. Because of its cellular data structure, it can be integrated with raster-based remote sensing data. Calibration of the SLEUTH model requires gridded inputs of topographic slope, land use, zones excluded from growth, urban spatial extents, transportation networks and terrain hillshading. These data were developed from remote sensing and from topographic maps using GIS, and were prepared at three different resolutions.
[1]
Stacy Hoppen,et al.
Methods And Techniques for Rigorous Calibration of a Cellular Automaton Model of Urban Growth
,
1996
.
[2]
Huei-Min Tsai,et al.
Sustainable development for island societies : Taiwan and the world
,
2002
.
[3]
Xiaojun Yang,et al.
Drivers of Land-Use/Land-Cover Changes and Dynamic Modeling for the Atlanta, Georgia Metropolitan Area
,
2002
.
[4]
S. Goetz,et al.
Using the Sleuth Urban Growth Model to Simulate the Impacts of Future Policy Scenarios on Urban Land Use in the Baltimore-Washington Metropolitan Area
,
2004
.
[5]
Louis Lebel,et al.
Views of Chiang Mai: The Contributions of Remote-Sensing to Urban Governance and Sustainability
,
2007
.