GC11B-1046
Mangrove Blue Carbon stocks and change estimation from PolInSAR, Lidar and High Resolution Stereo Imagery combined with Forest Cover change mapping

Monday, 14 December 2015
Poster Hall (Moscone South)
Temilola E Fatoyinbo1, Marc Simard2, David Lagomasino1, Seung-Kuk Lee1, Carl Trettin3, Emanuelle A Feliciano1, Matthew Hansen4 and Poulsen John5, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)US Forest Service Cordesville, Cordesville, SC, United States, (4)University of Maryland, College Park, MD, United States, (5)Duke University, Durham, NC, United States
Abstract:
Mangroves and tidal wetlands have the highest carbon density among terrestrial ecosystems. Although they only represent 3 % of the total forest area (or 0.01 % of land area), C emissions from mangrove destruction alone at current rates could be equivalent to 10 % of carbon emissions from deforestation.

One of the main challenges to implementing carbon mitigation projects is measuring carbon, efficiently, effectively, and safely. In mangroves especially, the extreme difficulty of the terrain has hindered the establishment of sufficient field plots needed to accurately measure carbon on the scale necessary to relate remotely sensed measurements with field measurements at accuracies required for REDD and other C trading mechanisms. In this presentation we will showcase the methodologies for, and the remote sensing products necessary to implement MRV (monitoring, reporting and verification) systems in Coastal Blue Carbon ecosystems. Specifically, we will present new methods to estimate aboveground biomass stocks and change in mangrove ecosystems using remotely sensed data from Interferometric SAR from the TanDEM-X mission, commercial airborne Lidar, High Resolution Stereo-imagery, and timeseries analysis of Landsat imagery in combination with intensive field measurements of above and belowground carbon stocks. Our research is based on the hypothesis that by combining field measurements, commercial airborne Lidar, optical and Pol-InSAR data, we are able to estimate Mangrove blue carbon storage with an error under 20% at the project level and permit the evaluation of UNFCCC mechanisms for the mitigation of carbon emissions from coastal ecosystems.