Regional landslide susceptibility zonation utilizing bivariate statistical techniques in the northwestern Himalayas, Jammu and Kashmir, India
Author:
Funder
Institute of Eminence-Banaras Hindu University
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12040-024-02367-3.pdf
Reference159 articles.
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2. Ahmadi H and Pekkan E 2021 Fault-based geological lineaments extraction using remote sensing and GIS – A review; Geosciences 11 183.
3. Akgun A, Dag S and Bulut F 2008 Landslide susceptibility mapping for a landslide-prone area (Findikli NE of Turkey) by likelihood-frequency ratio and weighted linear combination models; Environ. Geol. 54 1127–1143, https://doi.org/10.1007/s00254-007-0882-8.
4. Al-Najjar H A H, Pradhan B, Kalantar B, Sameen M I, Santosh M and Alamri A 2021 Landslide susceptibility modeling: An integrated novel method based on machine learning feature transformation; Remote Sens. 13 3281, https://doi.org/10.3390/rs13163281.
5. Aslam B, Maqsoom A, Khalil U, Ghorbanzadeh O, Blaschke T and Farooq D 2022 Evaluation of different landslide susceptibility models for a local scale in the Chitral district, northern Pakistan; Sensors 22 3107, https://doi.org/10.3390/s22093107.
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