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Logo: Institut für Photogrammetrie und Geoinformatik/Leibniz Universität Hannover
Logo Leibniz Universität Hannover
Logo: Institut für Photogrammetrie und Geoinformatik/Leibniz Universität Hannover
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Multi-sensor technologies for analyzing sinkholes

Bearbeitung:S. Vajedian

Motivation

Sinkhole formation causes the surface to subside or collapse suddenly without any prior warning, and therefore can lead to extensive damage and even loss of life and property. Delineating sinkholes is important for understanding hydrological processes and mitigating geological hazards in karst areas. 

The recent availability of high-resolution digital elevation models (DEM) from TanDEM-X (TDX) mission enables us to delineate and analyze geomorphologic features and landscape structures at an unprecedented level of details, in comparison to previous missions such as c-band and x-band Shuttle Radar Topography Mission (SRTM). Using high-resolution TDX data from different geometries and time periods enables us to effectively distinguish sinkholes from other depression features of the basin.

The formation of the sinkhole can be preceded by a long-term gradual subsidence in the periods ranging from a few days to years. It’s possible to determine the factors controlling the precursory subsidence. The Interferometric Synthetic Aperture Radar (InSAR) observations enable us to measure the magnitude and duration of the precursory subsidence.

Goal

The purpose is to develop an adaptive sinkhole-delineating method based on photogrammetry techniques to detect karst sinkholes in Hamedan, west Iran, using TDX- derived DEMs. We apply automatic feature extraction using watershed algorithm in order to detect depression areas.

Fig. 1: Background: High resolution DEM generated by Tandem-X data, foreground: Extracted Sinkholes resulted from watershed algorithm.

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