Artificial intelligence, machine learning and big data in natural resources management: a comprehensive bibliometric review of literature spanning 1975–2022
Applying artificial intelligence (AI), machine learning (ML), and big data to natural resource
management (NRM) is revolutionizing how natural resources are managed. To gain more …
management (NRM) is revolutionizing how natural resources are managed. To gain more …
[HTML][HTML] Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization
X Zhou, H Wen, Y Zhang, J Xu, W Zhang - Geoscience Frontiers, 2021 - Elsevier
The present study aims to develop two hybrid models to optimize the factors and enhance
the predictive ability of the landslide susceptibility models. For this, a landslide inventory …
the predictive ability of the landslide susceptibility models. For this, a landslide inventory …
Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution
Ongoing landslides have wreaked havoc in various regions across the globe. This article
presents a study of two forms of landslide monitoring viz; creation of Landslide Susceptibility …
presents a study of two forms of landslide monitoring viz; creation of Landslide Susceptibility …
[HTML][HTML] Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …
landslide susceptibility research, but most studies have no unified ensemble framework …
A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility mapping
Landslides are dangerous events which threaten both human life and property. The study
aims to analyze the landslide susceptibility (LS) in the Kysuca river basin, Slovakia. For this …
aims to analyze the landslide susceptibility (LS) in the Kysuca river basin, Slovakia. For this …
An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong
HM Lyu, ZY Yin - Sustainable Cities and Society, 2023 - Elsevier
Hong Kong frequently suffers from multi-hazards such as floods, muddy-water flows and
landslides induced by rainstorms. This study presents an improved multi criteria decision …
landslides induced by rainstorms. This study presents an improved multi criteria decision …
Assessing the imperative of conditioning factor grading in machine learning-based landslide susceptibility modeling: a critical inquiry
Current machine learning approaches to landslide susceptibility modeling often involve
grading conditioning factors, a method characterized by substantial subjectivity and …
grading conditioning factors, a method characterized by substantial subjectivity and …
Spatial modeling and susceptibility zonation of landslides using random forest, naïve bayes and K-nearest neighbor in a complicated terrain
SA Abu El-Magd, SA Ali, QB Pham - Earth Science Informatics, 2021 - Springer
Recently, one of the most frequent natural hazards around several regions in the world is the
landslide events. The area of Jabal Farasan in the northwest Jeddah of Saudi Arabia suffers …
landslide events. The area of Jabal Farasan in the northwest Jeddah of Saudi Arabia suffers …
A GIS-based landslide susceptibility mapping and variable importance analysis using artificial intelligent training-based methods
Landslides often cause significant casualties and economic losses, and therefore landslide
susceptibility mapping (LSM) has become increasingly urgent and important. The potential …
susceptibility mapping (LSM) has become increasingly urgent and important. The potential …
An ensemble approach of feature selection and machine learning models for regional landslide susceptibility mapping in the arid mountainous terrain of Southern …
This study evaluates the utility of the ensemble framework of feature selection and machine
learning (ML) models for regional landslide susceptibility mapping (LSM) in the arid climatic …
learning (ML) models for regional landslide susceptibility mapping (LSM) in the arid climatic …