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International Journal of Innovation and Scientific Research
ISSN: 2351-8014
 
 
Thursday 15 November 2018

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Forest degradation, a methodological approach using remote sensing techniques: A review


Volume 24, Issue 1, June 2016, Pages 161–178

 Forest degradation, a methodological approach using remote sensing techniques:
A review

Jean-fiston Mikwa, Rudi Gossens, and Pierre Defourny

Original language: English

Received 28 December 2015

Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


Measuring all carbon stock changes caused by forest degradation within a country at the same level of detail and accuracy will likely not be efficient. In particular the considerations of IPCC source category analysis, and the fact that many degradation activities are focused on specific areas within the country help to make the monitoring more targeted and efficient to capture the most important components with priority. To estimate forest degradation, countries need to assess carbon stock changes and the total area undergoing degradation, ideally for different types of degradation (i.e. fire, logging, and fuel wood harvesting). The assessment of changes in carbon stocks requires consistent ground data while the evaluation of the total area undergoing degradation is more reliably measured through remote sensing for the major degradation processes, in particular for developing countries. The particular problem of measuring forest degradation is the lack of field based forest data for developing countries.

Author Keywords: Forest degradation, remote sensing techniques.


How to Cite this Article


Jean-fiston Mikwa, Rudi Gossens, and Pierre Defourny, “Forest degradation, a methodological approach using remote sensing techniques: A review,” International Journal of Innovation and Scientific Research, vol. 24, no. 1, pp. 161–178, June 2016.