A methodology for assessing multiple hazards applied to Sweden DOI Creative Commons
Johan Björck, Margaret McNamee, Jonathan Wahlqvist

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: unknown, P. 104934 - 104934

Published: Oct. 1, 2024

Language: Английский

Machine learning methods for landslide mapping studies: A comparative study of SVM and RF algorithms in the Oued Aoulai watershed (Morocco) DOI Creative Commons
Latifa Ladel, Mohamed Mastere, Shuraik Kader

et al.

Open Geosciences, Journal Year: 2025, Volume and Issue: 17(1)

Published: Jan. 1, 2025

Abstract Effective management of watershed risks and landslides necessitates comprehensive landslide susceptibility mapping. Support vector machine (SVM) random forest (RF) learning models were used to map the in Morocco’s Taounate Province. Detailed inventory maps generated based on aerial pictures, field research, geotechnical survey reports. Factor correlation analysis carefully eliminated redundant factors from original 14 triggering factors. As a result, 30% sites randomly chosen for testing, whereas 70% locations picked model training. The RF achieved an area under curve (AUC) 94.7%, categorizing 30.07% region as low susceptibility, while SVM reached AUC 80.65%, indicating high sensitivity 53.5% locations. These results provide crucial information local authorities, supporting sound catchment planning development strategies.

Language: Английский

Citations

0
Flood susceptibility mapping in Indian Sundarban delta using multivariate statistics and machine learning algorithms in GIS DOI
Souvik Kundu, Tarun Kumar Mondal

Stochastic Environmental Research and Risk Assessment, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

Language: Английский

Citations

0
A heterogeneous ensemble landslide susceptibility assessment method based on InSAR and geographic similarity extended landslide inventory DOI
Youchen Zhu, Huan Chen, Deliang Sun

et al.

Gondwana Research, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

Language: Английский

Citations

0
Multi-hazard susceptibility mapping in the Salt Lake watershed DOI Creative Commons

Sima Pourhashemi,

Mohammad Ali Zangane Asadi,

Mahdi Boroughani

et al.

Environmental Challenges, Journal Year: 2024, Volume and Issue: unknown, P. 101079 - 101079

Published: Dec. 1, 2024

Language: Английский

Citations

2
Spatiotemporal monitoring of post-fire soil erosion rates using earth observation (EO) data and cloud computing DOI
Stefanos Stefanidis, Nikolaos Proutsos, Alexandra D. Solomou

et al.

Natural Hazards, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 16, 2024

Language: Английский

Citations

0
A methodology for assessing multiple hazards applied to Sweden DOI Creative Commons
Johan Björck, Margaret McNamee, Jonathan Wahlqvist

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: unknown, P. 104934 - 104934

Published: Oct. 1, 2024

Language: Английский

Citations

0