Improving landslide susceptibility mapping using integration of ResU-Net technique and optimized machine learning algorithms

Author:

Rezaie Fatemeh,Panahi MahdiORCID,Bateni Sayed M.,Kalantari Zahra,Rahmati Omid,Lee Saro,Syaripudin Nur Arip

Publisher

Elsevier

Reference92 articles.

1. Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia;Aditian;Geomorphology,2018

2. Earthquake-induced landslide mapping for the 2018 Hokkaido Eastern Iburi earthquake using PALSAR-2 data;Aimaiti;Remote Sens,2019

3. GIS-based landslide susceptibility modeling: a comparison between fuzzy multi-criteria and machine learning algorithms;Ali;Geosci. Front.,2021

4. Landslide mapping using object-based image analysis and open source tools;Amatya;Eng. Geol.,2021

5. Landslide hazard zonation by using AHP (Analytical hierarchy process) model in GIS (geographic information system) environment (case study: Kordan Watershed);Amir Yazdadi;Int. J. Progress. Sci. Technol. (IJPSAT),2016

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