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Ground-Level Digital Terrain Model (DTM) Construction from Tandem-X InSAR Data and Worldview Stereo-Photogrammetric ImagesThe ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.
Document ID
20170003290
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Lee, Seung-Kuk
(Universities Space Research Association Greenbelt, MD, United States)
Fatoyinbo, Temilola
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Lagomasino, David
(Universities Space Research Association Greenbelt, MD, United States)
Osmanoglu, Batuhan
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Feliciano, Emanuelle
(Universities Space Research Association Greenbelt, MD, United States)
Date Acquired
April 7, 2017
Publication Date
July 15, 2016
Publication Information
Publication: 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Publisher: IEEE
e-ISSN: 2153-7003
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN41179
Funding Number(s)
CONTRACT_GRANT: NNH15CO48B
CONTRACT_GRANT: NNG11HP16A
Distribution Limits
Public
Copyright
Other

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