Deep learning-based landslide detection using Sentinel-1 SAR imagery in the Chilean Patagonia
Authors:
- 28 August 2026
- journal article
- research article
- Published by Springer Nature in Natural Hazards
- Vol. 122 (18) , 619
Abstract
No abstract availableKeywords
This publication has 33 references indexed in Scilit:
- Rock slides in paraglacial environments in South America: three-dimensional modeling of glacier retreat and landslide inducing the 2017 Santa Lucía disaster in the Chilean PatagoniaLandslides, 2024
- Understanding the failure mechanisms of the 2017 Santa Lucía landslide, Patagonian Andes, using remote sensing and 3D numerical modelling techniquesLandslides, 2024
- Landslide detection by deep learning of non-nadiral and crowdsourced optical imagesLandslides, 2020
- A review of statistically-based landslide susceptibility modelsEarth-Science Reviews, 2018
- U-Net: Convolutional Networks for Biomedical Image Segmentation2015
- Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)Natural Hazards, 2015
- Simulating SAR geometric distortions and predicting Persistent Scatterer densities for ERS-1/2 and ENVISAT C-band SAR and InSAR applications: Nationwide feasibility assessment to monitor the landmass of Great Britain with SAR imageryRemote Sensing of Environment, 2014
- Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite imagesRemote Sensing of Environment, 2011
- Landslides induced by the April 2007 Aysén Fjord earthquake, Chilean PatagoniaLandslides, 2010
- Present-day South American climatePalaeogeography, Palaeoclimatology, Palaeoecology, 2009