Mangrove ecosystems provide several ecosystem services ranging from shoreline protection against erosion, tsunamis and storms, as well as nutrient cycling, fisheries production, lumber and habitat. But as a result of their location and economic value, they are among the most rapidly changing landscapes on Earth. While the effects of sea-level rise and increased extreme climatic events may increase the vulnerability of this ecosystem, the greatest current threats derive from human activities such as aquaculture, freshwater diversions, overharvesting and urban and industrial development. The conversion of mangrove forests to aquaculture is one of the largest contributors to mangrove forest degradation, particularly in South East Asia.

This project aims to use radar remote sensing to generate science-ready baseline maps of mangrove canopy structure and develop algorithms for monitoring land-use change.  First, we generate baseline maps of mangrove canopy structure, including height and biomass, using SRTM, TanDEM-X, ICESAT-1/2 and GEDI data.   These products are used to indicate potential ecosystem services and to assess vulnerability to these same services.  Object-based change detection algorithms are developed to identify land cover and land use change (LCLUC) maps from time-series of ALOS-1, ALOS-2 and Sentinel-1.  The baseline maps of canopy structure, along with geometric indices describing the shape of detected changes, support identification of proximate driver of LCLUC.  The radar-derived LCLUC products combined with the baseline maps support evaluation of regional vulnerability as well as evaluation of damage to ecosystems in terms of forest extent and volume. We plan to use these algorithms to process the upcoming NISAR mission.