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It is of great significance to dynamically simulate and forecast the development and evolutionary of soil erosion process.Traditionally, most of soil erosion models are essentially steady-state models...
A Cellular Automata model based on Partial Least Squares Approaches is proposed for simulating complex urban systems. The core part of Geo-CA model is the transition rules and a mass of independent sp...
Cellular automata (CA) are individual-based spatial models increasingly used to simulate the dynamics of natural and human systems and forecast their evolution. Despite their simplicity, they can ex...
Cellular automata have been used as a simulation technique in the study of an impressively wide range of urban phenomena, including regional growth, urban sprawl, gentrification, residential growth, p...
Spatially explicit land use / land cover (LUCC) models aim at simulating the patterns of change on the landscape. In order to simulate landscape structure, the simulation procedures of most computatio...
This paper describes an on-going work on the development and implementation of cellular automata based urban growth modeling using multitemporal satellite imagery. The algorithm is designed to simula...
The modelling of land features dynamics is an important factor to take into account when it is necessary to quantify or estimate the environmental changes produce by a given phenomena. It is interest...
When classifying an image, there might be several pixels having near among probability, spectral angle or mahalanobis distance which are normally regarded as unclassified or misclassified. These pixe...
Dynamics in nature are multi-faceted and difficult to follow. Computerized simulations offer new ways for investigating dynamic systems by incorporating their principle aspects . These simulations mi...
Urban growth is dynamic and complex spatial process that has severe environmental and social impacts. High population growth results in the transformations of forested areas or high quality agricultu...
URBAN SIMULATION USING NEURAL NETWORKS AND CELLULAR AUTOMATA FOR LAND USE PLANNING.

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