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Remote Sens. 2014, 6(1), 756-775; doi:10.3390/rs6010756
Article

Mapping Forest Degradation due to Selective Logging by Means of Time Series Analysis: Case Studies in Central Africa

* ,
,
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Remote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, A-8010 Graz, Austria
* Author to whom correspondence should be addressed.
Received: 20 November 2013 / Revised: 23 December 2013 / Accepted: 30 December 2013 / Published: 9 January 2014
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Abstract

Detecting and monitoring forest degradation in the tropics has implications for various fields of interest (biodiversity, emission calculations, self-sustenance of indigenous communities, timber exploitation). However, remote-sensing-based detection of forest degradation is difficult, as these subtle degradation signals are not easy to detect in the first place and quickly lost over time due to fast re-vegetation. To overcome these shortcomings, a time series analysis has been developed to map and monitor forest degradation over a longer period of time, with frequent updates based on Landsat data. This time series approach helps to reduce both the commission and the omission errors compared to, e.g., bi- or tri-temporal assessments. The approach involves a series of pre-processing steps, such as geometric and radiometric adjustments, followed by spectral mixture analysis and classification of spectral curves. The resulting pixel-based classification is then aggregated to degradation areas. The method was developed on a study site in Cameroon and applied to a second site in Central African Republic. For both areas, the results were finally evaluated against visual interpretation of very high-resolution optical imagery. Results show overall accuracies in both study sites above 85% for mapping degradation areas with the presented methods.
Keywords: forest degradation; time series analysis; REDD+ monitoring system; SMA; gap detection forest degradation; time series analysis; REDD+ monitoring system; SMA; gap detection
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Hirschmugl, M.; Steinegger, M.; Gallaun, H.; Schardt, M. Mapping Forest Degradation due to Selective Logging by Means of Time Series Analysis: Case Studies in Central Africa. Remote Sens. 2014, 6, 756-775.

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