Mangrove Canopy Height and Biomass Estimations by means of Pol-InSAR Techniques
Abstract:Mangrove forests cover only about 1% of the Earth’s terrestrial surface, but they are amongst the highest carbon-storing and carbon-exporting ecosystems globally. Estimating 3-D mangrove forest parameters has been challenging due to the complex physical environment of the forests. In previous works, remote sensing techniques have proven an excellent tool for the estimation of mangrove forests. Recent experiments have successfully demonstrated the global scale estimation of mangrove structure using spaceborne remote sensing data: SRTM (InSAR), ICESat/GLAS (lidar), Landsat ETM+ (passive optical). However, those systems had relatively low spatial and temporal resolutions.
Polarimetric SAR Interferometry (Pol-InSAR) is a Synthetic Aperture Radar (SAR) remote sensing technique based on the coherent combination of both Polarimetric and interferometric observables. The Pol-InSAR has provided a step forward in quantitative 3D forest structure parameter estimation (e.g. forest canopy height and biomass) over a variety of forests. Recent developments of Pol-InSAR technique with TanDEM-X (TDX) data in mangroves have proven that TDX data can be used to produce global-scale mangrove canopy height and biomass maps at accuracies comparable to airborne lidar measurements.
In this study we propose to generate 12m-resolution mangrove canopy height and biomass estimates for the coastline of Mozambique using Pol-InSAR techniques from single-/dual-pol TDX data and validated with commercial airborne lidar. To cover all of the mangroves in the costal area of Mozambique, which is about 3000 km, about 200 TDX data sets are selected and processed. The TDX height data are calibrated with commercial airborne lidar data acquired over 150 km2 of mangroves in the Zambezi delta of Mozambique while height and Biomass estimates are validated using in-situ forest inventory measurements and biomass. The results from the study will be the first country-wide, wall-to-wall estimate of mangrove structure and biomass at 12 m resolution.