[HTML][HTML] Landslide susceptibility map** using machine learning: A literature survey

M Ado, K Amitab, AK Maji, E Jasińska, R Gono… - Remote Sensing, 2022‏ - mdpi.com
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …

BIM–GIS integrated utilization in urban disaster management: The contributions, challenges, and future directions

Y Cao, C Xu, NM Aziz, SN Kamaruzzaman - Remote Sensing, 2023‏ - mdpi.com
In the 21st Century, disasters have severe negative impacts on cities worldwide. Given the
significant casualties and property damage caused by disasters, it is necessary for disaster …

Predictive performances of ensemble machine learning algorithms in landslide susceptibility map** using random forest, extreme gradient boosting (XGBoost) and …

T Kavzoglu, A Teke - Arabian Journal for Science and Engineering, 2022‏ - Springer
Across the globe, landslides have been recognized as one of the most detrimental
geological calamities, especially in hilly terrains. However, the correct determination of …

An interpretable model for the susceptibility of rainfall-induced shallow landslides based on SHAP and XGBoost

X Zhou, H Wen, Z Li, H Zhang, W Zhang - Geocarto International, 2022‏ - Taylor & Francis
The machine-learning “black box” models, which lack interpretability, have limited
application in landslide susceptibility map**. To interpret the black-box models, some …

Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility map** in Icheon, South Korea

WL Hakim, F Rezaie, AS Nur, M Panahi… - Journal of environmental …, 2022‏ - Elsevier
Landslides are a geological hazard that can pose a serious threat to human health and the
environment of highlands or mountain slopes. Landslide susceptibility map** is an …

[HTML][HTML] Machine-learning based landslide susceptibility modelling with emphasis on uncertainty analysis

AL Achu, CD Aju, M Di Napoli, P Prakash… - Geoscience …, 2023‏ - Elsevier
Landslide susceptibility maps are vital tools used by decision-makers to adopt mitigation
strategies for future calamities. In this context, research on landslide susceptibility modelling …

A review of indoor positioning systems for UAV localization with machine learning algorithms

C Sandamini, MWP Maduranga, V Tilwari, J Yahaya… - Electronics, 2023‏ - mdpi.com
The potential of indoor unmanned aerial vehicle (UAV) localization is paramount for
diversified applications within large industrial sites, such as hangars, malls, warehouses …

Landslide identification using machine learning techniques: Review, motivation, and future prospects

VC SS, E Shaji - Earth science informatics, 2022‏ - Springer
Abstract The WHO (World Health Organization) study reports that, between 1998-2017, 4.8
million people have been affected by landslides with more than 18000 deaths. The …

Landslide susceptibility assessment of a part of the Western Ghats (India) employing the AHP and F-AHP models and comparison with existing susceptibility maps

SB Bhagya, AS Sumi, S Balaji, JH Danumah… - Land, 2023‏ - mdpi.com
Landslides are prevalent in the Western Ghats, and the incidences that happened in 2021 in
the Koottickal area of the Kottayam district (Western Ghats) resulted in the loss of 10 lives …

integrating machine learning ensembles for landslide susceptibility map** in Northern Pakistan

N Ali, J Chen, X Fu, R Ali, MA Hussain, H Daud… - Remote Sensing, 2024‏ - mdpi.com
Natural disasters, notably landslides, pose significant threats to communities and
infrastructure. Landslide susceptibility map** (LSM) has been globally deemed as an …