Towards a pan-European burnt scar mapping methodology based on single date medium resolution optical remote sensing data

A two stage approach for burnt scar detection from single date multispectral medium spatial resolution optical remote sensing data (AWIFS) has been developed. The approach includes first an identification of burnt scar seeds based on a learning algorithm followed by a region growing process. An Artificial Neural Network (ANN) and a Classification tree (CT) were tested as learning algorithms. Both learning algorithms were coupled with a bootstrap aggregation. Training data for the classifiers were obtained from MODIS-based polygons generated by the Rapid Damage Assessment (RDA) module of the European Forest Fire Information System (EFFIS), to which different levels of filtering were applied. The outcomes