Characterisation and Monitoring of Mangroves Using ALOS PALSAR Data

Methods for classifying mangrove communities from remote sensing data has primarily focused on extent, structure, biomass and/or dominant/species or genus. However, many algorithms have been developed on and applied to local regions but are not applicable at regional levels. For the tropical and subtropics, data from the Japanese Space Exploration Agency’s (JAXA) Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) have been acquired routinely since 2006. As part of the JAXA Kyoto and Carbon (K&C) Initiative, regional mosaics of L-band HH and HV data have been generated for insular and mainland Southeast Asia, northern Australia, Belize and the Amazon-influenced coastline of South America. By using these data in conjunction with Shuttle Radar Topography Mission (SRTM)-derived estimates of mangrove canopy height, a classification of forest structural types was developed which could be applied regionally and potentially across the range of mangroves. Across the tropics and subtropics, mangroves are also subject to change in response to natural or anthropogenic drivers. Identifying such change requires, in many cases, the establishment of baseline datasets of mangrove extent although spatial information on the distribution of dominant species and both structure and biomass as a function of growth stage is desirable. For the same regions, comparison with existing baseline datasets established areas of significant change in French Guiana, Southeast Asia and northern Australia, with each attributable to different causes. The study highlighted the benefits of ALOS PALSAR for detecting change, particularly given the prevalence of cloudcover in many regions. The utility of and requirements for the inclusion of PALSAR data within a global mangrove mapping and monitoring system are highlighted.