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Characterization of Tropical Rainforest for X-Band Spaceborne SAR Calibration Using TanDEM-X Data

Dell Amore, Luca und Bueso Bello, Jose Luis und Klenk, Patrick und Reimann, Jens und Rizzoli, Paola (2023) Characterization of Tropical Rainforest for X-Band Spaceborne SAR Calibration Using TanDEM-X Data. In: International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2023-07-16 - 2023-07-21, Pasadena, USA. doi: 10.1109/IGARSS52108.2023.10282710.

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Kurzfassung

The radiometric calibration of spaceborne SAR products plays a key role for assuring a good performance of the whole end-to-end system and requires a precise knowledge of both the radar system and the illuminated target. For example, the shape of the antenna pattern in elevation can be directly estimated by analysing SAR detected images in presence of a homogeneous backscatter profile in the slant range dimension. To this aim, tropical rainforests have been established by the SAR community as well-known calibration sites for performing such an activity. Here, according to the hypothesis of isotropic scattering, the backscattering coefficient in terms of unit area perpendicular to the antenna, called gamma nought, is assumed to remain constant with respect to the incidence angle. Nevertheless, several studies using X- and C-band sensors have shown a slight dependency of the backscatter on the incidence angle, as well as on ground target properties and meteorological conditions. In this work, we present a detailed statistical characterization of radar backscatter at X-band over the Amazon rainforest using TanDEM-X high-resolution data, and we provide insights on how to best utilize radar backscatter data in this region for SAR calibration and modelling purposes. In particular, we concentrate on the dependence of the Amazon rainforest backscatter on the day-time of acquisition, which is directly related to the orbit direction of TanDEM-X. Furthermore, we analyse the seasonal variation of the radar backscatter, as well as possible variations with respect to different latitudes, characterized by different climate conditions and biomes. Finally, we provide a series of backscatter models for different scenarios, which can be used, e.g., for X-band spaceborne SAR system design and theoretical modelling.

elib-URL des Eintrags:https://elib.dlr.de/194844/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Characterization of Tropical Rainforest for X-Band Spaceborne SAR Calibration Using TanDEM-X Data
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Dell Amore, LucaLuca.DellAmore (at) dlr.dehttps://orcid.org/0000-0002-6731-1300146516645
Bueso Bello, Jose LuisJose-Luis.Bueso-Bello (at) dlr.dehttps://orcid.org/0000-0003-3464-2186NICHT SPEZIFIZIERT
Klenk, PatrickPatrick.Klenk (at) dlr.dehttps://orcid.org/0000-0002-8284-2265NICHT SPEZIFIZIERT
Reimann, Jensjens.reimann (at) dlr.dehttps://orcid.org/0000-0002-0650-9073NICHT SPEZIFIZIERT
Rizzoli, PaolaPaola.Rizzoli (at) dlr.dehttps://orcid.org/0000-0001-9118-2732NICHT SPEZIFIZIERT
Datum:2023
Erschienen in:International Geoscience and Remote Sensing Symposium (IGARSS)
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
DOI:10.1109/IGARSS52108.2023.10282710
Status:veröffentlicht
Stichwörter:Synthetic Aperture Radar (SAR), SAR Calibration, Amazon Rainforest, TanDEM-X
Veranstaltungstitel:IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Veranstaltungsort:Pasadena, USA
Veranstaltungsart:internationale Konferenz
Veranstaltungsdatum:2023-07-16 - 2023-07-21
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - AI4SAR
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Hochfrequenztechnik und Radarsysteme > Satelliten-SAR-Systeme
Hinterlegt von: Dell Amore, Luca
Hinterlegt am:02 Mai 2023 10:44
Letzte Änderung:07 Mär 2024 11:35

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