Remote sensing for assessing landslides and associated hazards
Multi-platform remote sensing using space-, airborne and ground-based sensors has
become essential tools for landslide assessment and disaster-risk prevention. Over the last …
become essential tools for landslide assessment and disaster-risk prevention. Over the last …
[HTML][HTML] Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review
R He, W Zhang, J Dou, N Jiang, H ** using XGBoost, gradient boosting machine, and random forest
EK Sahin - SN Applied Sciences, 2020 - Springer
Decision tree-based classifier ensemble methods are a machine learning (ML) technique
that combines several tree models to produce an effective or optimum predictive model, and …
that combines several tree models to produce an effective or optimum predictive model, and …
Landslide map** using object-based image analysis and open source tools
Availability of high-resolution optical imagery and advances in image processing
technologies have significantly improved our ability to map landslides. In recent years object …
technologies have significantly improved our ability to map landslides. In recent years object …
Comparative analysis of gradient boosting algorithms for landslide susceptibility map**
EK Sahin - Geocarto International, 2022 - Taylor & Francis
The aim of the study is to compare four recent gradient boosting algorithms named as
Gradient Boosting Machine (GBM), Categorical Boosting (CatBoost), Extreme Gradient …
Gradient Boosting Machine (GBM), Categorical Boosting (CatBoost), Extreme Gradient …
Apriori association rule and K-means clustering algorithms for interpretation of pre-event landslide areas and landslide inventory map**
In this paper, an inventory of the landslide that occurred in Karahacılı at the end of 2019 was
created and the pre-landslide conditions of the region were evaluated with traditional …
created and the pre-landslide conditions of the region were evaluated with traditional …
Rainfall-induced landslide susceptibility map** using machine learning algorithms and comparison of their performance in Hilly area of Fujian Province, China
P Ye, B Yu, W Chen, K Liu, L Ye - Natural Hazards, 2022 - Springer
The rainfall can contribute significantly to landslide events, especially in hilly areas. The
landslide susceptibility map (LSM) usually helps to mitigate disasters. However, how to …
landslide susceptibility map (LSM) usually helps to mitigate disasters. However, how to …
A semi-automated object-based gully networks detection using different machine learning models: a case study of Bowen catchment, Queensland, Australia
Gully erosion is a dominant source of sediment and particulates to the Great Barrier Reef
(GBR) World Heritage area. We selected the Bowen catchment, a tributary of the Burdekin …
(GBR) World Heritage area. We selected the Bowen catchment, a tributary of the Burdekin …
Geohazard recognition and inventory map** using airborne LiDAR data in complex mountainous areas
C Guo, Q Xu, X Dong, W Li, K Zhao, H Lu, Y Ju - Journal of Earth Science, 2021 - Springer
Geohazard recognition and inventory map** are absolutely the keys to the establishment
of reliable susceptibility and hazard maps. However, it has been challenging to implement …
of reliable susceptibility and hazard maps. However, it has been challenging to implement …
UAV, GNSS, and InSAR data analyses for landslide monitoring in a mountainous village in western Greece
Areas in Western Greece are particularly prone to landslides. Usually triggered by
earthquakes or intense rainfalls, they cause damage to infrastructure (roads, bridges, etc.) …
earthquakes or intense rainfalls, they cause damage to infrastructure (roads, bridges, etc.) …