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Fusion of TanDEM-X and Cartosat-1 elevation data supported by neural network-predicted weight maps

Bagheri, Hossein and Schmitt, Michael and Zhu, Xiao Xiang (2018) Fusion of TanDEM-X and Cartosat-1 elevation data supported by neural network-predicted weight maps. ISPRS Journal of Photogrammetry and Remote Sensing, 144, pp. 285-297. Elsevier. doi: 10.1016/j.isprsjprs.2018.07.007. ISSN 0924-2716.

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Official URL: https://www.sciencedirect.com/science/article/abs/pii/S0924271618301990


Recently, the bistatic SAR interferometry mission TanDEM-X provided a global terrain map with unprecedented accuracy. However, visual inspection and empirical as- sessment of TanDEM-X elevation data against high-resolution ground truth illustrates that the quality of the DEM decreases in urban areas because of SAR-inherent imaging properties. One possible solution for an enhancement of the TanDEM-X DEM quality is to fuse it with other elevation data derived from high- resolution optical stereoscopic imagery, such as that provided by the Cartosat-1 mission. This is usually done by Weighted Averaging (WA) of previously aligned DEM cells. The main contribution of this paper is to develop a method to efficiently predict weight maps in order to achieve optimized fusion results. The predic- tion is modeled using a fully connected Artificial Neural Network (ANN). The idea of this ANN is to extract suitable features from DEMs that relate to height residuals in training areas and then to automatically learn the pattern of the relationship between height errors and features. The results show the DEM fusion based on the ANN-predicted weights improves the qualities of the study DEMs. Apart from increasing the absolute accuracy of Cartosat-1 DEM by DEM fusion, the relative accuracy (respective to reference LiDAR data) of DEMs is improved by up to 50% in urban areas and 22% in non-urban areas while the improvement by the HEM-based method does not exceed 20% and 10% in urban and non-urban areas respectively.

Item URL in elib:https://elib.dlr.de/116067/
Document Type:Article
Title:Fusion of TanDEM-X and Cartosat-1 elevation data supported by neural network-predicted weight maps
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Bagheri, HosseinTU MünchenUNSPECIFIED
Schmitt, Michaelm.schmitt (at) tum.deUNSPECIFIED
Zhu, Xiao Xiangdlr-imf/tum-lmfUNSPECIFIED
Date:October 2018
Journal or Publication Title:ISPRS Journal of Photogrammetry and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1016/j.isprsjprs.2018.07.007
Page Range:pp. 285-297
Keywords:TanDEM-X, Cartosat-1, neural networks
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 - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Häberle, Matthias
Deposited On:05 Dec 2017 10:27
Last Modified:06 Sep 2019 15:28

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