Characterization of mangrove forest types based on ALOS-PALSAR in overall Indonesian archipelago

Abstract

Indonesia has largest mangrove forest in the world, total area around 3.5 million ha or 17% – 23% from mangrove forest in the world. Mangrove forest provides products and services, such as carbon balance of the coastal zone. Mapping and monitoring biomass of mangrove is very important but field survey of mangrove biomass and productivity in overall Indonesia is very difficult. Global-scale mosaics with HH and HV backscatter of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) which is 50-m spatial resolution has been generated. This image available for identification and monitoring mangrove forest. The Objective of this research to investigate characterization of mangrove forest types based on ALOS-PALSAR in overall Indonesian archipelago. Methodology consists of collecting ALOS-PALSAR image for overall Indonesian archipelago, preprocessing and mosaicking, collecting region of interest of mangrove forest, plotting, ground survey, characterization and classification. The result of this research has showed characterization of mangrove forest types based on ALOS-PALSAR. Indonesian mangrove forest types has HH value around -10 dB until -7 dB and HV value around -17 dB until -13 dB. Higher of HH and HV backscatters value indicated higher of level biomass. Based on scatter plot of HH and HV, Indonesian mangrove forest can be classified in three level biomass. Generally level biomass of mangrove forest in Indonesia archipelago is moderate.