[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 …

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 …