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Proceedings Paper

Forestry prediction using cellular automata in satellite images
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Paper 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.

Paper Details

Date Published: 24 February 2004
PDF: 11 pages
Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); doi: 10.1117/12.509693
Show Author Affiliations
Rodrigo Mikosz Goncalves, Ctr. Federal de Educacao Tecnologica do Parana (Brazil)
Tania Mezzadri Centeno, Ctr. Federal de Educacao Tecnologica do Parana (Brazil)
Gilles Selleron, Univ. Toulouse le Mirail (France)


Published in SPIE Proceedings Vol. 5232:
Remote Sensing for Agriculture, Ecosystems, and Hydrology V
Manfred Owe; Guido D'Urso; Jose F. Moreno; Alfonso Calera, Editor(s)

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