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Fusion of Urban Tandem-X Raw Dems Using Variational Models

Bagheri, Hossein and Schmitt, Michael and Zhu, Xiao Xiang (2018) Fusion of Urban Tandem-X Raw Dems Using Variational Models. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11 (12), pp. 4761-4774. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/JSTARS.2018.2878608 ISSN 1939-1404

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Official URL: https://ieeexplore.ieee.org/document/8540396

Abstract

Recently, a new global Digital Elevation Model (DEM) with pixel spacing of 0.4 arcseconds and relative height accuracy finer than 2m for flat areas (slopes <20%) and better than 4m for rugged terrain (slopes >20%) was created trough the TanDEM-X mission. One important step of the chain of global DEM generation is to mosaic and fuse multiple raw DEM tiles to reach the target height accuracy. Currently, Weighted Averaging (WA) is applied as a fast and simple method for TanDEM-X raw DEM fusion in which the weights are computed from height error maps delivered from the Interferometric TanDEM-X Processor (ITP). However, evaluations show that WA is not the perfect DEM fusion method for urban areas especially in confrontation with edges such as building outlines. The main focus of this paper is to investigate more advanced variational approaches such as TV-L1 and Huber models. Furthermore, we also assess the performance of variational models for fusing raw DEMs produced from data takes with different baseline configurations and height of ambiguities. The results illustrate the high efficiency of variational models for TanDEM-X raw DEM fusion in comparison to WA. Using variational models could improve the DEM quality by up to 2m particularly in inner city subsets.

Item URL in elib:https://elib.dlr.de/122435/
Document Type:Article
Title:Fusion of Urban Tandem-X Raw Dems Using Variational Models
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bagheri, HosseinTU MünchenUNSPECIFIED
Schmitt, Michaelm.schmitt (at) tum.deUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIED
Date:2018
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:11
DOI :10.1109/JSTARS.2018.2878608
Page Range:pp. 4761-4774
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:Tandem-X, Fusion
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Häberle, Matthias
Deposited On:23 Oct 2018 14:01
Last Modified:31 Jul 2019 20:20

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