Measuring Landslide Susceptibility in Jakholi Region of Garhwal Himalaya Using Landsat Images and Ensembles of Statistical and Machine Learning Algorithms
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7707-9_13
Reference83 articles.
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2. Aditian A, Kubota T, Shinohara Y (2018) Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon. Indonesia. Geomorphology 318:101–111
3. Ahmed B, Dewan A (2017) Application of bivariate and multivariate statistical techniques in landslide susceptibility modeling in Chittagong City corporation. Bangladesh. Remote Sens 9(4):304
4. Bamisaiye OA (2019) Landslide in parts of south-western Nigeria. SN Appl Sci 1(7):745
5. Basharat M, Shah HR, Hameed N (2016) Landslide susceptibility mapping using GIS and weighted overlay method: a case study from NW Himalayas, Pakistan. Arab J Geosci 9:1–19. https://doi.org/10.1007/s12517-016-2308-y5
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