Landslide susceptibility mapping and assessment using geospatial platforms and weights of evidence (WoE) method in the Indian Himalayan Region: recent …

AK Batar, T Watanabe - ISPRS International Journal of Geo-Information, 2021 - mdpi.com
The Himalayan region and hilly areas face severe challenges due to landslide occurrences
during the rainy seasons in India, and the study area, ie, the Rudraprayag district, is no …

Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution

B Ganesh, S Vincent, S Pathan, SRG Benitez - … Applications: Society and …, 2023 - Elsevier
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 …

GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and …

SA Ali, F Parvin, QB Pham, M Vojtek, J Vojteková… - Ecological …, 2020 - Elsevier
Flood is a devastating natural hazard that may cause damage to the environment
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …

[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

SA Ali, F Parvin, J Vojteková, R Costache, NTT Linh… - Geoscience …, 2021 - Elsevier
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …

A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

W Chen, X Xie, J Wang, B Pradhan, H Hong, DT Bui… - Catena, 2017 - Elsevier
The main purpose of the present study is to use three state-of-the-art data mining
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …

A novel hybrid artificial intelligence approach for flood susceptibility assessment

K Chapi, VP Singh, A Shirzadi, H Shahabi… - … modelling & software, 2017 - Elsevier
A new artificial intelligence (AI) model, called Bagging-LMT-a combination of bagging
ensemble and Logistic Model Tree (LMT)-is introduced for mapping flood susceptibility. A …

Identifying the essential conditioning factors of landslide susceptibility models under different grid resolutions using hybrid machine learning: A case of Wushan and …

M Liao, H Wen, L Yang - Catena, 2022 - Elsevier
This study attempts to identify the essential conditioning factors of landslides to increase the
predictive ability of landslide susceptibility models and explore the effects of different grid …

Prediction of the landslide susceptibility: Which algorithm, which precision?

HR Pourghasemi, O Rahmati - Catena, 2018 - Elsevier
Coupling machine learning algorithms with spatial analytical techniques for landslide
susceptibility modeling is a worth considering issue. So, the current research intend to …

Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using …

BT Pham, DT Bui, I Prakash, MB Dholakia - Catena, 2017 - Elsevier
The main objective of this study is to evaluate and compare the performance of landslide
models using machine learning ensemble technique for landslide susceptibility assessment …

[HTML][HTML] Flash flood susceptibility mapping using a novel deep learning model based on deep belief network, back propagation and genetic algorithm

H Shahabi, A Shirzadi, S Ronoud, S Asadi, BT Pham… - Geoscience …, 2021 - Elsevier
Flash floods are responsible for loss of life and considerable property damage in many
countries. Flood susceptibility maps contribute to flood risk reduction in areas that are prone …