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Detection and visualisation of terrain edges in slope failures Cover

Detection and visualisation of terrain edges in slope failures

Open Access
|Jun 2025

Abstract

Our aim was to develop a pixel-based methodology employing multiple terrain parameters for the semi-automatic identification of terrain edges. The procedure was applied to landform features associated with slope failures, operating on different resolutions of a digital terrain model (DTM). We intended to produce two outputs – grid maps base on: discrete data allowing precise identification and revealing a higher incidence of terrain edges than a hillshade map; floating point data visually highlighting terrain edges more sharply than a hillshade grid. The results showed that the grid maps generated by the new method: Binary Terrain Edges – BinT and Quality Terrain – QT exhibited more terrain edges than the hillshade map. The method demonstrated its robustness when used across three different resolutions of DTM. It was applied within the protection buffer zone of the overhead transmission powerline (OHL). Slightly more than half of the total of identified and manually digitised slope failures using the hillshade map supplemented with failures observed in QT may not necessarily be subject to field confirmation. OHL is a long-distance construction passing a variety of environments. Therefore, the detection of slope failures requires semi-automatic or automatic procedures to be costless and time-saving.

DOI: https://doi.org/10.2478/mgr-2025-0006 | Journal eISSN: 2199-6202 | Journal ISSN: 1210-8812
Language: English
Page range: 70 - 90
Submitted on: Feb 13, 2024
Accepted on: Mar 26, 2025
Published on: Jun 30, 2025
Published by: Czech Academy of Sciences, Institute of Geonics
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Martina Slámová, Roman Sitko, Roman Kadlečík, Ľuboš Skurčák, František Chudý, published by Czech Academy of Sciences, Institute of Geonics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.