Forest/non-forest mapping using ENVISAT ASAR data in Northeast China

Large scale forest mapping and change detection plays a significant role in the study of global change, particularly in the research of carbon source and sink. This paper presents results from forest/non-forest classification using ENVISAT-ASAR data. Both pixel-based and object-based classification method were developed for ASAR HH/HV images acquired on a single date. For the object-based classification, two different strategies were proposed: rule-set and threshold-ratio. Using as reference a land use map derived from Landsat TM images acquired in 2000, the accuracy of the forest/non-forest map from ASAR AP data has been found to meet the requirements of mapping the Northeast Chinese forests at large scale.