Large-scale forest mapping based on ERS-1/2 and Envisat ASAR data.

In this paper, two kinds of forest map over Northeast China were produced by use of archived ERS-1/2 tandem data (1995-2000) and Envisat ASAR data (2005). As far as ERS-1/2 coherence model was concerned, a new approach was introduced, that allowed model training using the MODIS Vegetation Continuous Fields canopy cover product without further need for ground data. On basis of this method, the largescale forest stem volume map (four classes: 0-20, 20-50, 50-80 and 80 m3/hm2) was generated. As regards the Envisat ASAR data, the object-based classifier was applied to map the forest/nonforest areas automatically. The crosscomparisons were performed for these two kinds of map based on the land use map from Landsat TM-5 data acquired in 2005. The results show that these two satellite SAR data can be used for the largescale forest mapping and their maps in current case will provide supports for the further analysis of forest change detection and the map updating.