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Fusing Next-generation Active Remote Sensing Data for Improved Forest Height and Structure Mapping

Wenlu Qi, University of Maryland, wqi@umd.edu (Presenter)
Ralph Dubayah, University of Maryland, dubayah@umd.edu

There is a great uncertainty in our current understanding of global carbon stocks and their spatial distribution. Globally consistent and spatially resolved data on forest structural properties and above-ground biomass (AGB) will be very useful to address this issue. NASA’s future spaceborne Lidar mission - Global Ecosystem Dynamics Investigation (GEDI) to be deployed on the International Space Station in 2019 is designed to better characterize the Earth’s ecosystem structure. This mission will help to generate the first fine-resolution global maps of forest vertical structure and above-ground biomass (AGB). However, GEDI is an intrinsically sampling system (25-m footprint, 60-m space along-track and ~500-m space cross-track) and leaves large areas of unmeasured forests between its tracks.

In order to better quantify the Earth’s forest structure and AGB, this research has developed fusion algorithms between simulated GEDI (using LVIS) metrics with high-resolution (3m) InSAR images. The InSAR images were acquired from a recently launched (2011) mission - TanDEM-X which forms with its twin satellite TerraSAR-X the first polarimetric interferometer in space. Therefore, data from this mission has no temporal deccorelation, making it superior to other SAR missions for height estimation. In the fusion process, simulation of GEDI measurements were applied to constrain TanDEM-X scattering model by providing ground elevation data, whereas TanDEM-X variables (interferometric coherence, scattering phase height and inversion results from the scattering model, etc.) were used to spatially extend the scattered GEDI metrics over the landscape based on their correlations. The proposed method was tested over a temperate forest - Hubbard Brook Experimental Forest. Results demonstrated that by fusing GEDI with TanDEM-X data, canopy height can be derived at an RMSE of ~4m and r2 of 0.8 at 90m resolution. The proposed algorithm thus could make contributions to an improved estimation of the Earth’s forest structure.

Presentation Type:  Poster

Session:  Carbon Monitoring System (CMS) Posters   (Mon 1:30 PM)

Associated Project(s): 

  • Dubayah, Ralph: High Resolution Carbon Monitoring and Modeling: A CMS Phase 2 Study ...details

Poster Location ID: 129

 


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