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Tree Height Estimation with Global TanDEM-X Products: Digital Elevation Model (DEM) and Forest/Non-Forest Map

Ranade, Maitreya (2018) Tree Height Estimation with Global TanDEM-X Products: Digital Elevation Model (DEM) and Forest/Non-Forest Map. Masterarbeit, University of Würzburg.

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Kurzfassung

The TanDEM-X mission represents a unique source of interferometric Synthetic Aperture Radar (InSAR) products on a global scale. Out of many TanDEM-X global products, Digital Elevation Model (DEM) and Forest/Non-Forest (FNF) Map were exploited to estimate the tree height. The elevation provided by the DEM was combined with the information provided by the Forest/Non-Forest Map, where areas with and without forest are well identified. Different approaches were invented, implemented, tested and validated in order to estimate the tree height. Along with the two products, different SAR Parameters were used to improve the classification provided by the Forest/Non Forest (FNF) Map. Elevation information in the separated forested and non-forested areas, is used separately for estimating tree height. Different approaches of the tree height estimation, suggested by the author include interpolation methods to generate Digital Terrain Mode (DTM), line by line approach, dilation approach and separation of the frequency components in various domains. The idea is to exploit and combine the information provided by both global products to estimate the tree height for different types of forests. Upon validation over multiple test-sites, high performing approaches can be implemented on a larger scale to obtain another global product: Global Tree Height. This will open a new path of possible applications, ranging from biomass research to forest degradations detection.

elib-URL des Eintrags:https://elib.dlr.de/118708/
Dokumentart:Hochschulschrift (Masterarbeit)
Titel:Tree Height Estimation with Global TanDEM-X Products: Digital Elevation Model (DEM) and Forest/Non-Forest Map
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Ranade, MaitreyaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Juli 2018
Referierte Publikation:Ja
Open Access:Nein
Seitenanzahl:73
Status:veröffentlicht
Stichwörter:Forestry, interferometric SAR (InSAR), land use classification, Synthetic Aperture Radar (SAR).
Institution:University of Würzburg
Abteilung:Institute for Informatics
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 - Projekt TanDEM-X (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Hochfrequenztechnik und Radarsysteme > Satelliten-SAR-Systeme
Hinterlegt von: Bueso Bello, Jose Luis
Hinterlegt am:02 Feb 2018 10:49
Letzte Änderung:22 Okt 2018 14:35

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