Robust Method for Deforestation Analysis of Satellite Images
International Journal of Environmental Monitoring and Analysis
Volume 3, Issue 6, December 2015, Pages: 420-424
Received: Nov. 25, 2015; Accepted: Dec. 4, 2015; Published: Dec. 25, 2015
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Authors
Ioan Ispas, Centre for New Electronic Architecture, Research Institute for Artificial Intelligence, Bucharest, Romania
Eduard Franti, Centre for New Electronic Architecture, Research Institute for Artificial Intelligence, Bucharest, Romania; National Institute for Research and Development in Microtechnologies, Micromachined Structures, Microwave Circuits and Devices Laboratory, Bucharest, Romania
Florin Lazo, Centre for New Electronic Architecture, Research Institute for Artificial Intelligence, Bucharest, Romania
Elteto Zoltan, Centre for New Electronic Architecture, Research Institute for Artificial Intelligence, Bucharest, Romania
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Abstract
The aim is to design a robust method for tracking real time deforestation in a local area under satellite observation. Deforested areas are obtained by a procedure of differentiating between two successive images (temporal). The resulting method proves to be robust, the analyzed satellite image having multiple alterations: cutting (minus 3-10%), translation (5-10%), rotation (2-10 degrees), parasite random noise (5-15%), different brightness and contrast (5-10%) and cloudy areas (15-20%).
Keywords
Satellite Images, Digital Image Processing Deforestation, Forest Satellite Surveillance
To cite this article
Ioan Ispas, Eduard Franti, Florin Lazo, Elteto Zoltan, Robust Method for Deforestation Analysis of Satellite Images, International Journal of Environmental Monitoring and Analysis. Vol. 3, No. 6, 2015, pp. 420-424. doi: 10.11648/j.ijema.20150306.16
Copyright
Copyright © 2015 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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