Soil erosion potential hotspot zone identification using machine learning and statistical approaches in eastern India
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s11069-020-04213-3.pdf
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2. Akgun A, Sezer EA, Nefeslioglu HA et al (2012) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci. https://doi.org/10.1016/j.cageo.2011.04.012
3. Ambroise B, Beven K, Freer J (1996) Toward a generalization of the TOPMODEL concepts: topographic indices of hydrological similarity. Water Resour Res
4. Arabameri A, Pourghasemi HR, Yamani M (2017) Applying different scenarios for landslide spatial modeling using computational intelligence methods. Environ Earth Sci. https://doi.org/10.1007/s12665-017-7177-5
5. Arabameri A, Pradhan B, Rezaei K (2019) Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS. J Environ Manage. https://doi.org/10.1016/j.jenvman.2018.11.110
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