Please use this identifier to cite or link to this item: http://openlibrary.ge/handle/123456789/8668
Title: Landslide Susceptibility Mapping Using Gis-Based Weight-of- Evidence Modelling in Central Georgian Regions
Authors: Stankevich, S. A.
Titarenko, O. V.
Svideniuk, M. O.
Keywords: ბუნებრივი კატასტროფები საქართველოში;Natural Disasters in Georgia;landslide;weight-of-evidence;landslide hazard mapping;remote sensing;digital terrain elevation data
Issue Date: 2019
Citation: საერთაშორისო სამეცნიერო კონფერენცია “ბუნებრივი კატასტროფები საქართველოში: მონიტორინგი, პრევენცია, შედეგების შერბილება”. შრომები, ISBN 978-9941-13-899-7, ივ. ჯავახიშვილის სახ. თბილისის სახელმწიფო უნივერსიტეტის გამომცემლობა, თბილისი, საქართველო, 12–14 დეკემბერი, 2019 წ., გვ. 187-190.
International Scientific Conference “Natural Disasters in Georgia: Monitoring, Prevention, Mitigation”. Proceedings, ISBN 978-9941-13-899-7, Publish Hous of Iv. Javakhishvili Tbilisi State University, December 12-14, 2019, pp. 187-190.
Abstract: This paper explains the procedure for the generation of a landslide susceptibility map at regional level in Georgia. At the first place, this research presents the results of the weight-of-evidence model applied to estimate the probability of landslides manifestation. A spatial database, including causative factors associated with landslides was constructed from geological maps and satellite data products. The factors that influence landslide occurrence, such as terrain slope, aspect, curvature, elevation, flow accumulation and distance from drainages were calculated from a Sentinel-1 digital terrain elevation data (DTED). Lithology is derived from the Georgia’s geological map. Vegetation cover map is retrieved from Sentinel-2 multispectral satellite imagery.
URI: http://openlibrary.ge/handle/123456789/8668
Appears in Collections:საერთაშორისო სამეცნიერო კონფერენცია “ბუნებრივი კატასტროფები საქართველოში: მონიტორინგი, პრევენცია, შედეგების შერბილება” = International Scientific Conference “Natural Disasters in Georgia: Monitoring, Prevention, Mitigation ” (2019)

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