GIS-based landslide susceptibility mapping of the Meghalaya-Shillong Plateau region using machine learning algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geology,Geotechnical Engineering and Engineering Geology
Link
https://link.springer.com/content/pdf/10.1007/s10064-023-03188-2.pdf
Reference89 articles.
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2. Adnan MSG, Rahman MS, Ahmed N, Ahmed B, Rabbi MF, Rahman RM (2020) Improving spatial agreement in machine learning-based landslide susceptibility mapping. Remote Sensing 12(20):3347
3. Agrawal N, Dixit J (2022a) Assessment of landslide susceptibility for Meghalaya (India) using bivariate (frequency ratio and Shannon entropy) and multi-criteria decision analysis (AHP and fuzzy-AHP) models. All Earth 34(1):179–201
4. Agrawal N, Dixit J (2022b) Topographic classification of North Eastern Region of India using geospatial technique and following seismic code provisions. Environmental Earth Sciences 81:436
5. Agrawal N, Gupta L, Dixit J (2022) Geospatial assessment of active tectonics using SRTM DEM-based morphometric approach for Meghalaya. India All Earth 34(1):39–54
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