A Structure-Based Framework for the Combination of GEDI and Tandem-X Measurements Over Forest Scenarios

Choi, Changhyun; Pardini, Matteo; Papathanassiou, Konstantinos

doi:10.1109/igarss.2019.8898130

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…The necessity of combining forest parameters in order to describe the complexity of forest scenario highlighted in the present study agrees also with other SAR studies, where reference information is integrated into the backscatter inversion at P-band [12][13][14] or where multiple forest parameters estimated from single pass interferometry at X-band are combined for AGB regression [10,11]. An interesting option for future studies is represented by the synergy between LiDAR and ground/volume decomposition as the 3D structure from LiDAR can be used as a-priori information for inversion [38].…”

Section: Discussionsupporting

confidence: 82%

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

Banda¹,

d’Alessandro

Tebaldini

2020

Remote Sensing

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In this work, the role of volume scattering obtained from ground and volume decomposition of P-band synthetic aperture radar (SAR) data as a proxy for biomass is investigated. The analysis here presented originates from the BIOMASS L2 activities, part of which were focused on strengthening the physical foundations of the SAR-based retrieval of forest above-ground biomass (AGB). A critical analysis of the observed strong correlation between tomographic intensity and AGB is done in order to propose simplified AGB proxies to be used during the interferometric phase of BIOMASS. In particular, the aim is to discuss whether, and to what extent, volume scattering obtained from ground/volume decomposition can provide a reasonable alternative to tomography. To do this, both are tested on P-band data collected at Paracou during the TropiSAR campaign and cross-validated against in-situ AGB measurements. Results indicate that volume backscattered power as obtained by ground/volume decomposition is weakly correlated to AGB, notwithstanding different solutions for volume scattering are tested, and support the conclusion that forest structure actually plays a non-negligible role in AGB retrieval in dense tropical forests.

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Section: Discussionsupporting

confidence: 82%

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

Banda¹,

d’Alessandro

Tebaldini

2020

Remote Sensing

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“…Other approaches are currently being tested to produce 1-km or finer scale wall-towall maps of 3D vegetation structure. These include a spatially interpolated GEDI-derived level 3 gridded canopy vegetation metrics [10], the fusion of GEDI with interferometric SAR [31,58,74,75], and the fusion of GEDI and ICESAT-2 data with moderate (10-30 m) resolution optical remote sensing data [9,68,72]. While Sentinel-1/2 and Landsat data were utilized to derive tree height and tree cover products at much finer spatial detail [9,68,72] than the VIIRS-derived products, they can be subject to data gaps in cloudy regions and in regions with sparse Landsat/Sentinel-2 data record.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data

2021

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Accurate information on the global distribution and the three-dimensional (3D) structure of Earth’s forests is needed to assess forest biomass stocks and to project the future of the terrestrial Carbon sink. In spite of its importance, the 3D structure of forests continues to be the most crucial information gap in the observational archive. The Global Ecosystem Dynamics Investigation (GEDI) Light Detection and Ranging (LiDAR) sensor is providing an unprecedented near-global sampling of tropical and temperate forest structural properties. The integration of GEDI measurements with spatially-contiguous observations from polar orbiting optical satellite data therefore provides a unique opportunity to produce wall-to-wall maps of forests’ 3D structure. Here, we utilized Visible Infrared Imaging Radiometer Suite (VIIRS) annual metrics data to extrapolate GEDI-derived forest structure attributes into 1-km resolution contiguous maps of tree height (TH), canopy fraction cover (CFC), plant area index (PAI), and foliage height diversity (FHD) for the conterminous US (CONUS). The maps were validated using an independent subset of GEDI data. Validation results for TH (r2 = 0.8; RMSE = 3.35 m), CFC (r2 = 0.79; RMSE = 0.09), PAI (r2 = 0.76; RMSE = 0.41), and FHD (r2 = 0.83; RMSE = 0.25) demonstrated the robustness of VIIRS data for extrapolating GEDI measurements across the nation or even over larger areas. The methodology developed through this study may allow multi-decadal monitoring of changes in multiple forest structural attributes using consistent satellite observations acquired by orbiting and forthcoming VIIRS instruments.

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“…The fusion approach from GEDI and TanDEM-X indicates a great possibility for generating global-scale forest maps and biomass maps (where the GEDI data will be available) with unprecedented spatial resolution [41]. In this sense, GEDI data are combined with TanDEM-X measurements in Choi, et al [42], Lee, et al [41]and Lee, et al [43] to express physical forest structure. This approach was also used for forest structure modeling before the GEDI launch [44] with simulated GEDI data.…”

Section: Introductionmentioning

confidence: 99%

GEDI Elevation Accuracy Assessment: A Case Study of Southwest Spain

Quiros

Polo

Fragoso-Campon

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Information about forest structures is becoming crucial to Earth's global carbon cycle, forest habitats and biodiversity. The Global Ecosystem Dynamics Investigation (GEDI) provides 25-m diameter footprints of the surface for 3D structure measurements. The main goal of this study is to compare 12 031 footprints of GEDI data with other airborne and spaceborne Digital Elevation Models (DEMs) for Southwest Spain. Ground elevation differences (ELM) are analyzed by comparing GEDI measurements with ALS LiDAR-and TanDEM-X-derived DEMs. The vertical structure (RH100) is compared to the ALS LiDAR measurement. Ten zones are analyzed, considering different degrees of coverage and slopes. We achieved an RMSE of 6.13 m for the ELM when comparing GEDI and LiDAR data and an RMSE of 7.14 m when comparing GEDI and TanDEM-X data. For some of the studied areas, these values were considerably smaller, with RMSE values even lower than 1 m. For the RH100 metric, an RMSE of 3.56 m was achieved when comparing GEDI and LiDAR data, but again with a minimum value of 2.09 m for one zone. The results show a clear relation to coverage and slope, especially for the latter. This work also evaluates the positional uncertainty of GEDI footprints, shifting them ±10 and ±5 m along and across the track of the satellite orbit and their intermediate angular positions. The outcomes reveal a strong tendency to obtain better results in the ELM when setting the footprint to 270° and displacing it within 10 m of its positional uncertainty in comparison with the LiDAR and TanDEM-X data.

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A Structure-Based Framework for the Combination of GEDI and Tandem-X Measurements Over Forest Scenarios

Cited by 4 publications

References 7 publications

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data

GEDI Elevation Accuracy Assessment: A Case Study of Southwest Spain

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