Contributions of ALOS PALSAR to Global Mangrove Mapping and Monitoring
(1) Aberystwyth University, Llandinam Tower, SY23 3DB Aberystwyth, United Kingdom
Worldwide, mangroves are experiencing changes in their extent and state as a consequence of anthropogenic disturbance (e.g., deforestation) but also natural extreme events including severe storms and tsunamis. Mangroves are also responding more subtly to changes in sea level and coastal processes, which themselves are partly induced by human activity, including climate change. However, the extent to which these changes can be quantified is variable within and between regions and also because of the lack of consistent historical baseline datasets.
Japan’s Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band SAR (PALSAR) provides a new and unique opportunity to generate or refine existing baseline maps of mangrove extent, establish areas of change (e.g., by comparing against historical datasets) and retrieve biophysical properties (e.g., biomass, structure and broad species types) that are indicative of the state of mangroves. The global consistency of the ALOS PALSAR data, which has been assured through a carefully designed observation strategy, also allows the development and implementation of classification schemes that are more globally applicable and which also consider the three-dimensional structure of mangroves.
Using JAXA Kyoto and Carbon (K&C) Initiative strip HH and HV mosaics and a combination of orthorectified fully polarimetric and fine beam single/dual polarisation data, this paper outlines the contribution of ALOS PALSAR to the characterisation, mapping and monitoring of mangroves at regional scales. Case studies are presented from South and Central America (e.g., Brazil, Belize, French Guiana), South East Asia (e.g., Malaysia) and Australia and focus on the use of single-date data for retrieving biomass classes, differentiating mangrove zones dominated by different species, and detecting exposed mudflats. Comparisons with historical datasets, including Japanese Earth Resources Satellite (JERS-1) SAR mosaics from the mid 1990s, indicate also the potential of multi-temporal data for the detection of natural and anthropogenically-induced change. The benefits of integrating data from optical or other radar (e.g., ENVISAT, Advanced SAR) are highlighted but limitations, including the differentiation of mangroves from other forest types, are also demonstrated. Options for updating existing global datasets of mangrove extent and dynamics using ALOS PALSAR data and based on the current study are presented.