摘要
Identification and monitoring of species composition and richness isneeded to formulate effective mangrove management and conservationpriorities. Prior studies have used commercial satellite images which arecost prohibitive for national and global applications. Here, we usedfreely available Landsat satellite data and new indices to discriminatemangrove species in Maros Regency, South Sulawesi, Indonesia andSegara Anakan, West Java, Indonesia. We use sensitive algorithm of theprincipal polar spectral (PPS) indices to discriminate mangroves species.PPS Indices were produced from a set of 3-dimensional Landsat 8Operational Land Imager (OLI) spectral indices (PPS Brightness, PPSGreenness, and PPS Wetness) determined by a polar change of theprincipal component axes of a spectral image of reference scene. Wequalitatively compare this set of PPS indices with the set of conventionalRGB multi-bands image composition and conventional NormalizedDifference Vegetation Indices (NDVI) for mangroves speciesdiscrimination. The comparisons indicate that the set of PPS indiceshave the potential for regional and possibly global applications inmangroves species mapping and monitoring.
