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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Daily Overview

Session

TomoSAR Methods
Location: Red Hall
Session Chair: Matteo Pardini, German Aerospace Center (DLR)
Session Chair: Stefano Tebaldini, Politecnico di Milano

Presentation 4

10:00am - 10:20am

Forest Structure Characterization Using Multi-Baseline SAR Tomography

Chumbitha Leena Nalla¹, Unmesh Khati¹, Shashi Kumar²

1: Indian Institute of Technology Indore, India; 2: Indian Institute of Remote Sensing, Dehradun

This study aims to characterize forest structure using multi-baseline Synthetic Aperture Radar (SAR) tomography, leveraging ESA’s Biomass Tomography Mission P-band SAR products for calibration and validation (Cal/Val). The study focuses on retrieving 3D forest structure, estimating forest height, and analyzing biomass distribution using advanced SAR tomographic techniques. The Biomass Tomography Mission provides P-band SAR data specifically designed for forest parameter estimation, offering deep penetration capabilities to extract vertical structure information.

Materials:

For this study, we have chosen two forest sites over Gabon which is taken in descending pass and over Amazon forest which is taken in both ascending and descending passes from the 32 datasets that are provided. We will use Level 1A - SCS products for this study. We intended to use only June GEDI sample points, but currently, it is not published for June 2025. Hence, GEDI LiDAR data from Jan 01 2025 till 02 May 2025 over the two sites is considered.

Methodology:

We will employ multi-baseline SAR tomography techniques, including spectral estimation methods such as Beamformer, Capon, MUSIC, and Compressive Sensing. These techniques enable the separation of different scattering contributions within forested areas, leading to a more accurate representation of vertical forest structure. The processing will include interferometric phase calibration, coherent combination of SAR acquisitions, and tomographic inversion for reconstructing vertical reflectivity profiles.

The Biomass Tomography Mission's P-band SAR products, particularly tomographic forest height and biomass estimates, will be used as reference datasets to validate our reconstructions. The calibration and validation process will involve comparison with ground truth data, including GEDI LiDAR-derived forest height measurements, in-situ biomass inventories, and other independent datasets. Additionally, error estimation and uncertainty quantification will be performed to assess the robustness of the tomographic inversion results.

Expected Outcomes:

High-resolution 3D forest structure maps: Using multi-baseline SAR tomography, we will generate spatially detailed representations of forest height and biomass distribution. Improved biomass estimation models: By incorporating validated tomographic inversion results, we aim to refine biomass retrieval algorithms and enhance their accuracy.

Comparative assessment with Biomass Tomography Mission products: A detailed evaluation of our tomographic retrievals against ESA’s Biomass Mission P-band SAR products and also GEDI LiDAR retrievals will be conducted to assess the consistency and accuracy.

Uncertainty analysis: A comprehensive error assessment will be carried out to quantify uncertainties in tomographic height and biomass estimates.

Datasets and reports: The results of this study, including tomographic forest structure datasets, will be available for further research and applications in global biomass mapping.