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Early lessons on combining lidar and multi-baseline SAR measurements for forest structure characterization

Pardini, Matteo and Armston, John and Qi, Wenlu and Lee, Seung-Kuk and Tello, Marivi and Cazcarra-Bes, Victor and Choi, Changhyun and Papathanassiou, Konstantinos and Dubayah, Ralph and Fatoyinbo, Lola (2020) Early lessons on combining lidar and multi-baseline SAR measurements for forest structure characterization. In: Forest Properties and Carbon Cycle Studies from Earth Observations Space Sciences Series of ISSI, 71. Springer International Publishing. ISBN 978-3-030-32838-2. ISSN 1385-7525.

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Official URL: https://www.springer.com/gp/book/9783030328382


The estimation and monitoring of 3D forest structure at large scales strongly relies on the use of remote sensing techniques. Today, two of them are capable to provide 3D forest structure estimates: lidar and Synthetic Aperture Radar (SAR) configurations. The differences in wavelength, imaging geometry, and technical implementation make the measurements provided by the two configurations different and, when it comes to the sensitivity to individual 3D forest structure components, complementary. Accordingly, the potential of combining lidar and SAR measure-ments towards an improved 3D forest structure estimation has been recognized from the very beginning. However, until today there is no established framework for this combination. This paper attempts to review differences, commonalities and complementarities of lidar and SAR measurements. First, lidar reflectance and SAR reflectivity profiles at different wavelengths are compared in different forest types. Second, current perspectives on their com-bination for the generation of enhanced structure products are discussed. Two promising frameworks for combining lidar and SAR measurements are reviewed based on their actual stage of development. The first one is a model-based framework where lidar-derived parameters are used to initialize SAR scattering models, and relies on both the validity of the models and on the physical equivalence of the used lidar and SAR parameters. The second one is a structure-based framework based on the ability of lidar and SAR measurements to express physical forest structure by means of appropriate indices. These indices can then be used to establish a link between the two measurements. The review is supported by experimental results achieved using space- and airborne data acquired in the frame of recent relevant campaigns.

Item URL in elib:https://elib.dlr.de/140450/
Document Type:Book Section
Title:Early lessons on combining lidar and multi-baseline SAR measurements for forest structure characterization
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Pardini, MatteoUNSPECIFIEDhttps://orcid.org/0000-0003-2018-7514UNSPECIFIED
Armston, JohnUniversity of MarylandUNSPECIFIEDUNSPECIFIED
Qi, WenluUniversity of MarylandUNSPECIFIEDUNSPECIFIED
Lee, Seung-KukNASA Goddard Space Flight CenterUNSPECIFIEDUNSPECIFIED
Cazcarra-Bes, VictorUNSPECIFIEDhttps://orcid.org/0000-0002-6776-4553UNSPECIFIED
Dubayah, RalphUniversity of MarylandUNSPECIFIEDUNSPECIFIED
Fatoyinbo, LolaNASA Goddard Space Flight CenterUNSPECIFIEDUNSPECIFIED
Date:25 November 2020
Journal or Publication Title:Forest Properties and Carbon Cycle Studies from Earth Observations
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
EditorsEmailEditor's ORCID iDORCID Put Code
Publisher:Springer International Publishing
Series Name:Space Sciences Series of ISSI
Keywords:Forest, structure, height, lidar, synthetic aperture radar (SAR), full waveforms, polarimetric SAR interferometry (Pol-InSAR), SAR Tomography (TomoSAR).
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 - Projekt TanDEM-X (old), R - Vorhaben Tandem-L Vorstudien (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > Radar Concepts
Deposited By: Pardini, Dr.-Ing. Matteo
Deposited On:14 Jan 2021 15:33
Last Modified:28 Feb 2024 15:31

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