A Comprehensive Assessment of XGBoost Algorithm for Landslide Susceptibility Mapping in the Upper Basin of Ataturk Dam, Turkey
نویسندگان
چکیده
The success rate in landslide susceptibility mapping efforts increased with the advancements machine learning algorithms and availability of geospatial data high spatial temporal resolutions. Existing data-driven models are not globally applicable due to variability conditioning parameters limitations up-to-date accurate data. Among numerous applications, maps essential for site selection health monitoring engineering structures, such as dams, increasing their lifetime prevent from disastrous events caused by damages. In this study, performance XGBoost algorithm was evaluated a landslide-prone area upper basin Ataturk Dam, which is prime investment located southeast Turkey. study has size 2718.7 km2 an elevation difference ca. 2000 m contains 27 lithological units. EU-DEM v1.1 Copernicus Programme used derive geomorphological features. High classification accuracy under curve value 0.96 could be obtained algorithm. According results, main factors controlling landslides lithology, altitude topographic wetness index.
منابع مشابه
Assessment of landslide susceptibility, semi-quantitative risk and management in the Ilam dam basin, Ilam, Iran
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2021
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app11114993