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Potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection

Schmitt, Michael and Baier, Gerald and Zhu, Xiao Xiang (2019) Potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection. ISPRS Journal of Photogrammetry and Remote Sensing (148), pp. 130-141. Elsevier. DOI: 10.1016/j.isprsjprs.2018.12.007 ISSN 0924-2716

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Official URL: https://www.sciencedirect.com/science/article/abs/pii/S092427161830340X?via%3Dihub

Abstract

This article investigates the potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection in comparison to conventional TanDEM-X data, i.e. image pairs acquired in repeat-pass or bistatic mode. For this task, an unsupervised coastline detection procedure based on scale-space representations and K-medians clustering as well as morphological image post-processing is proposed. Since this procedure exploits a clear discriminability of “dark” and “bright” appearances of water and land surfaces, respectively, in both SAR amplitude and coherence imagery, TanDEM-X InSAR data acquired in pursuit monostatic mode is expected to provide a promising benefit. In addition, we investigate the benefit introduced by a utilization of a non-local InSAR filter for amplitude denoising and coherence estimation instead of a conventional box-car filter. Experiments carried out on real TanDEM-X pursuit monostatic data confirm our expectations and illustrate the advantage of the employed data configuration over conventional TanDEM-X products for automatic coastline detection.

Item URL in elib:https://elib.dlr.de/134084/
Document Type:Article
Title:Potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schmitt, Michaelm.schmitt (at) tum.deUNSPECIFIED
Baier, GeraldGeoinformatics Unit, RIKEN Center for Advanced Intelligence Project, Tokyo, JapanUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:February 2019
Journal or Publication Title:ISPRS Journal of Photogrammetry and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1016/j.isprsjprs.2018.12.007
Page Range:pp. 130-141
Publisher:Elsevier
ISSN:0924-2716
Status:Published
Keywords:Coastline detection Pursuit monostatic mode TanDEM-X Synthetic aperture radar (SAR) Coherence
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 Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute
Deposited By: Rösel, Anja
Deposited On:13 Feb 2020 10:03
Last Modified:13 Feb 2020 10:03

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