Evaluating ERS-1 SAR data for the discrimination of tropical forest from other tropical vegetation types in Papua New Guinea

Abstract

ERS-1 Synthetic Aperture Radar (SAR) data over a study area located in Papua New Guinea, where there is a high probability of cloud cover, are evaluated on their information content for mapping tropical forest ecosystems. The feasibility of forest/non-forest discrimination using mono- and multi-temporal ERS-1 SAR data at 100m pixel size is investigated using two different classification methodologies. An assessment of the optimal acquisition period and number of acquisitions is undertaken. The automatic classification results are compared quantitatively with the aid of field observations in a comparative accuracy assessment methodology, and a comparison is made with Landsat Thematic Mapper (TM) data. Finally, the potential of ERS-1 SAR data for the discrimination of tropical forest types is investigated. The results showed that multi-temporal ERS-1 SAR data acquired at the appropriate times were found to have a high potential for forest/nonforest discrimination and achieved similar classification accuracies to the TM data. The discrimination of forest types proved difficult. However, discrimination was possible between dense and open forest types having different canopy structures.