Paper
24 February 2004 Forestry prediction using cellular automata in satellite images
Author Affiliations +
Abstract
This work approaches the study of Cellular Automata to the simulation of Satellite Remote Sensing images applied to modeling environment landscape dynamics. The images were collected by SPOT and Landsat-MSS from one forest in different times. After the geometric correction and images treatment a binary map will be formed by pixels that contain information about the forest existence. The main purpose is to predict in a geographic map what will happen with the landscape forest in the future. The simulation is done through the analysis of the temporal maps in accordance with their progression, regression or stability in time and with rules that describes how CA do the simulation. The results achieved are predict maps very useful for a environmental analysis. The experimental tests have showed promising results for studies related to forestry modeling.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rodrigo Mikosz Goncalves, Tania Mezzadri Centeno, and Gilles Selleron "Forestry prediction using cellular automata in satellite images", Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); https://doi.org/10.1117/12.509693
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Earth observing sensors

Satellite imaging

Satellites

Forestry

Geographic information systems

Remote sensing

Landsat

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