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Assessment of TanDEM-X DEM 2020 Data in Temperate and Boreal Forests and Their Application to Canopy Height Change

Schlund, Michael and von Poncet, Felicitas and Wessel, Birgit and Schweißhelm, Barbara and Kiefl, Nadine (2023) Assessment of TanDEM-X DEM 2020 Data in Temperate and Boreal Forests and Their Application to Canopy Height Change. PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 91, pp. 107-123. Springer. doi: 10.1007/s41064-023-00235-1. ISSN 2512-2789.

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Official URL: https://link.springer.com/article/10.1007/s41064-023-00235-1#article-info

Abstract

Space-borne digital elevation models (DEM) are considered as important proxy for canopy surface height and its changes in forests. Interferometric TanDEM-X DEMs were assessed regarding their accuracy in forests of Germany and Estonia. The interferometric synthetic aperture radar (InSAR) data for the new global TanDEM-X DEM 2020 coverage were acquired between 2017 and 2020. Each data acquisition was processed using the delta-phase approach for phase unwrapping and comprise an absolute height calibration. The results of the individual InSAR heights confirmed a substantial bias in forests. This was indicated by a mean error (ME) between -5.74 and -6.14 m associated with a root-mean-squared-error (RMSE) between 6.99 m and 7.40 m using airborne light detection and ranging (LiDAR) data as a reference. The bias was attributed to signal penetration, which was attempted to be compensated. The ME and RMSE improved substantially after the compensation to the range of -0.54 to 0.84 m and 3.55 m to 4.52 m. Higher errors of the penetration depth compensated DEMs compared to the original DEMs were found in non-forested areas. This suggests to use the penetration compensation only in forests. The potential of the DEMs for estimating height changes was further assessed in a case study in Estonia. The canopy height change analysis in Estonia indicated an overall accuracy in terms of RMSE of 4.17 m and ME of -0.93 m on pixel level comparing TanDEM-X and LiDAR height changes. The accuracy improved substantially at forest stand level to an RMSE of 2.84 m and an ME of -1.48 m. Selective penetration compensation further improved the height change estimates to an RMSE of 2.14 m and an ME of -0.83 m. Height loss induced by clearcutting was estimated with an ME of -0.85 m and an RMSE of 3.3 m. Substantial regrowth resulted in an ME of -0.46 m and an RMSE of 1.9 m. These results are relevant for exploiting multiple global acquisitions of TanDEM-X, in particular for estimating canopy height and its changes in European forests.

Item URL in elib:https://elib.dlr.de/195050/
Document Type:Article
Title:Assessment of TanDEM-X DEM 2020 Data in Temperate and Boreal Forests and Their Application to Canopy Height Change
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Schlund, MichaelUniversity of Twentehttps://orcid.org/0000-0001-6657-6713UNSPECIFIED
von Poncet, FelicitasIntelligence, Airbus Defence & SpaceUNSPECIFIEDUNSPECIFIED
Wessel, BirgitUNSPECIFIEDhttps://orcid.org/0000-0002-8673-2485137134351
Schweißhelm, BarbaraUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kiefl, NadineBayerische Staatsforsten AöRUNSPECIFIEDUNSPECIFIED
Date:1 March 2023
Journal or Publication Title:PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:91
DOI:10.1007/s41064-023-00235-1
Page Range:pp. 107-123
Publisher:Springer
ISSN:2512-2789
Status:Published
Keywords:InSAR, TanDEM-X, Canopy height changes, LiDAR, Forest
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research, R - Support TerraSAR-X/TanDEM-X operations
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Wessel, Dr.-Ing. Birgit
Deposited On:19 Jun 2023 10:07
Last Modified:19 Jun 2023 10:07

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