Estimation of Above Ground Biomass in the Everglades National Park using X-, C-, and L-band SAR data and Ground-based LiDAR

Emanuelle Feliciano, University of Miami - RSMAS, efeliciano@rsmas.miami.edu (Presenter)
Shimon Wdowinski, University of Miami - RSMAS, swdowinski@rsmas.miami.edu

Carbon content in wetlands is related to vegetation biomass. Carbon losses due to natural or human intervention affects global warming, thus it is vital to measure it. Anthropogenic activities disrupt bio-diverse wetland ecosystems including the South Florida Everglades. Quantifying these acute changes is difficult given the limited accessibility and the large extent of wetlands. For this purpose, remote sensing is widely used for successful ecosystem monitoring. Radar remote sensing sensors irradiate their own energy, overcoming optical satellite limitations. They retrieve amplitude and phase waveform, acquire data throughout day and night, and overcome cloud cover issues. We use space-based Synthetic Aperture Radar (SAR) observations over the Everglades National Park to estimate vegetation structure, above-ground biomass, and track their changes over time. We also conducted ground-based LiDAR a.k.a. 'Terrestrial Laser Scanning' (TLS) surveys in six vegetation communities to calibrate the SAR data. The upscaling approach includes SAR imagery acquisition at the three different wavelengths (X-, C-, L- bands). We use single- (HH or VV), dual- (HH/VV, HH/HV and VV/HV) and quad-polarization observations of the TerraSAR-X, RadarSAT-2, and ALOS satellites, acquired around same dates as the ground TLS surveys. Polarization data reflect radar signal interaction with various sections of the vegetation due to different scattering mechanisms. The processing of the SAR data included: Sigma Nought (SN) backscattering coefficient calibration, speckle noise suppression filtering and geocoding with the TLS data. SN is the conventional measure of the strength of radar signals reflected by a distributed scatterer, usually expressed in dB. The SN parameter is calibrated with the TLS calculated biomass for the upscaling approach. This project results will increase the chance that the Reducing Emissions from Deforestation and Forest Degradation (REDD+), in which large-scale biomass, carbon stock and vegetation structure monitoring, and mapping are needed, will be successful.

Presentation Type:  Poster

Session:  Other   (Mon 4:00 PM)

Associated Project(s): 

• Related Activity

Poster Location ID: 19