%0 Journal Article
%T Mapping Forest Degradation due to Selective Logging by Means of Time Series Analysis: Case Studies in Central Africa
%A Manuela Hirschmugl
%A Martin Steinegger
%A Heinz Gallaun
%A Mathias Schardt
%J Remote Sensing
%D 2014
%I MDPI AG
%R 10.3390/rs6010756
%X 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.
%K forest degradation
%K time series analysis
%K REDD+ monitoring system
%K SMA
%K gap detection
%U http://www.mdpi.com/2072-4292/6/1/756