Use of Anomalous Topographic Features for Landslide Inventory Mapping of Gilgit Area, Gilgit-Baltistan, Pakistan


Landslide inventory mapping is vital for hazard vulnerability and mitigation in mountainous terrain. The present study seeks to tentatively identify large bedrock landslides and related features across the Gilgit area in the Gilgit-Baltistan Province of Pakistan using the expert-driven knowledge of anomalous topographic features. For this, a topographic map with 40m contours was overlaid onto hillshade map generated from 30 m spatial resolution digital elevation model (DEM). The DEM was extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data. The hillshaded topographic map was utilized for the visual delineation of likely bedrock landslide features by observing the anomalous topographic signatures, including isolated topographic benches, divergent contours, isolated knobs, crenulated contours, and abnormal drainage patterns. This mapping exercise recognized hundreds of existing landslide features, including a few complex landslides (most likely bedrock landslides), earth flows, rotational slumps, and scree deposits. After these delineations were made on maps of the Gilgit area, these same areas were field checked to validate the inventory, especially along the main river channels. A comparison was then made between this study and historically documented landslides in the region. Overall, 82% of mapped landslides correlated well with the field observations. This highlights the significance of remote sensing and GIS tools for undertaking reconnaissance-level regional studies. This type of study is intended to serve as a preliminary investigation that could meet minimal requirements for emergency planning, which could be improved by detailed site-specific studies preparatory to planning of critical infrastructure.


Geosciences and Geological and Petroleum Engineering


This research work was funded by the Higher Education Commission (HEC), Pakistan, under the National Research Program for Universities (NRPU Project ID 9538).

Keywords and Phrases

ASTER DEM; Bedrock; Hillshade; Landslide inventory; Topographic keys

Geographic Coverage


International Standard Serial Number (ISSN)

1866-7538; 1866-7511

Document Type

Article - Journal

Document Version


File Type





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Publication Date

11 Nov 2021