Robust Method for Deforestation Analysis of Satellite Images

Ioan Ispas; Eduard Franti; Florin Lazo; Elteto Zoltan

doi:doi:10.11648/j.ijema.20150306.16

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Robust Method for Deforestation Analysis of Satellite Images

Ioan Ispas, Eduard Franti, Florin Lazo, Elteto Zoltan

Published in International Journal of Environmental Monitoring and Analysis (Volume 3, Issue 6)

Received: 25 November 2015 Accepted: 4 December 2015 Published: 25 December 2015

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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%).

Published in	International Journal of Environmental Monitoring and Analysis (Volume 3, Issue 6)
DOI	10.11648/j.ijema.20150306.16
Page(s)	420-424
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Satellite Images, Digital Image Processing Deforestation, Forest Satellite Surveillance

References

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[4]	Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool, SURF: Speeded Up Robust Features", Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346--359, 2008.
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[7]	O. Chum and J. Matas. Optimal randomized RANSAC, IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(8) Ș1472-1482, 2008.
[8]	Gregory P. Asner, David E. Knapp, Aravindh Balaji, Guayana Páez-Acosta. Automated mapping of tropical deforestation and forest degradation: CLASlite, Journal of Applied Remote Sensing, Vol. 3, 033543, 2009.
[9]	Ben DeVries, Jan Verbesselt, Lammert Kooistra and Martin Herold, Detecting Tropical Deforestation and Degradation Using Landsat Time Series, papers submitted to Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International.
[10]	J. G. Masek, E. F. Vermote, N. E. Saleous, R. Wolfe, F. G. Hall, K. F. Huemmrich, F. Gao, J. Kutler, and T.-k. Lim, \A Landsat Surface Reectance Dataset," Geoscience and Remote Sensing Letters, vol. 3, no. 1, pp. 68-72, 2006.
[11]	C. Huang, N. Thomas, S. N. Goward, J. G. Masek, Z. Zhu, J. R. G. Townshend, and J. E. Vogelmann, Automated masking of cloud and cloud shadow for forest change analysis using Landsat images," International Journal of Remote Sensing, vol. 31, no. 20, pp. 5449-5464, Oct. 2010.
[12]	A. K. Sah, B. P. Sah, K. Honji, N. Kubo, S. Senthil. Semi-automated cloud/shadow removal and land cover change detection using satellite imagery, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, Melbourne, Australia.
[13]	M. A. Wulder, J. A. Dechka, M. A. Gillis, J.E. Luther3, R. J. Hall, A. Beaudoin, S. E. Franklin. Operational mapping of the land cover of the forested area of Canada with Landsat data: EOSD land cover program, NOVEMBER/DECEMBER 2003, VOL. 79, NO. 6 pp. 2075-1083, THE FORESTRY CHRONICLE.
[14]	Land.copernicus.eu - Copernicus Global Land Service.
[15]	www.eea.europa.eu - European Environment Agency; GIO Land Service; CORINE Land Cover.
[16]	cce.nasa.gov - NASA Carbon Cycle & Ecosystems - LCLUC Program.
[17]	www.ospo.noaa.gov – NOAA (National Oceanic and Atmospheric Administration) Office of Satellite and Product Operations; Hazard Mapping System Fire and Smoke Product.

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APA Style

Ioan Ispas, Eduard Franti, Florin Lazo, Elteto Zoltan. (2015). Robust Method for Deforestation Analysis of Satellite Images. International Journal of Environmental Monitoring and Analysis, 3(6), 420-424. https://doi.org/10.11648/j.ijema.20150306.16

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ACS Style

Ioan Ispas; Eduard Franti; Florin Lazo; Elteto Zoltan. Robust Method for Deforestation Analysis of Satellite Images. Int. J. Environ. Monit. Anal. 2015, 3(6), 420-424. doi: 10.11648/j.ijema.20150306.16

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AMA Style

Ioan Ispas, Eduard Franti, Florin Lazo, Elteto Zoltan. Robust Method for Deforestation Analysis of Satellite Images. Int J Environ Monit Anal. 2015;3(6):420-424. doi: 10.11648/j.ijema.20150306.16

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@article{10.11648/j.ijema.20150306.16,
  author = {Ioan Ispas and Eduard Franti and Florin Lazo and Elteto Zoltan},
  title = {Robust Method for Deforestation Analysis of Satellite Images},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {3},
  number = {6},
  pages = {420-424},
  doi = {10.11648/j.ijema.20150306.16},
  url = {https://doi.org/10.11648/j.ijema.20150306.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20150306.16},
  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%).},
 year = {2015}
}

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TY  - JOUR
T1  - Robust Method for Deforestation Analysis of Satellite Images
AU  - Ioan Ispas
AU  - Eduard Franti
AU  - Florin Lazo
AU  - Elteto Zoltan
Y1  - 2015/12/25
PY  - 2015
N1  - https://doi.org/10.11648/j.ijema.20150306.16
DO  - 10.11648/j.ijema.20150306.16
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 420
EP  - 424
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20150306.16
AB  - 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%).
VL  - 3
IS  - 6
ER  -

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Author Information

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
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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Plain Text BibTeX RIS

APA Style

Ioan Ispas, Eduard Franti, Florin Lazo, Elteto Zoltan. (2015). Robust Method for Deforestation Analysis of Satellite Images. International Journal of Environmental Monitoring and Analysis, 3(6), 420-424. https://doi.org/10.11648/j.ijema.20150306.16

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ACS Style

Ioan Ispas; Eduard Franti; Florin Lazo; Elteto Zoltan. Robust Method for Deforestation Analysis of Satellite Images. Int. J. Environ. Monit. Anal. 2015, 3(6), 420-424. doi: 10.11648/j.ijema.20150306.16

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AMA Style

Ioan Ispas, Eduard Franti, Florin Lazo, Elteto Zoltan. Robust Method for Deforestation Analysis of Satellite Images. Int J Environ Monit Anal. 2015;3(6):420-424. doi: 10.11648/j.ijema.20150306.16

Copy | Download

@article{10.11648/j.ijema.20150306.16,
  author = {Ioan Ispas and Eduard Franti and Florin Lazo and Elteto Zoltan},
  title = {Robust Method for Deforestation Analysis of Satellite Images},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {3},
  number = {6},
  pages = {420-424},
  doi = {10.11648/j.ijema.20150306.16},
  url = {https://doi.org/10.11648/j.ijema.20150306.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20150306.16},
  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%).},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Robust Method for Deforestation Analysis of Satellite Images
AU  - Ioan Ispas
AU  - Eduard Franti
AU  - Florin Lazo
AU  - Elteto Zoltan
Y1  - 2015/12/25
PY  - 2015
N1  - https://doi.org/10.11648/j.ijema.20150306.16
DO  - 10.11648/j.ijema.20150306.16
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 420
EP  - 424
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20150306.16
AB  - 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%).
VL  - 3
IS  - 6
ER  -

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