Prediction of the spatial variability of rainfall- and human-induced landslides in the Bhagirathi Valley of the Indian NW Himalayas using machine learning techniques

Landslides are recurring and catastrophic natural hazards that cause tremendous loss in mountainous regions. Landslides in the Indian Himalayas are mainly due to rainfall, earthquakes, and anthropogenic activities such as deforestation, road widening, tunneling, and urbanization. Landslide susceptib...

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Veröffentlicht in:	Environmental earth sciences Jg. 84; H. 21; S. 598
Hauptverfasser:	Gupta, Neha, Das, Josodhir, Kanungo, D. P.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2025 Springer Nature B.V
Schlagworte:	Algorithms Anthropogenic factors Artificial neural networks Back propagation Biogeosciences Decision trees Deforestation Earth and Environmental Science Earth Sciences Earthquakes Environmental Science and Engineering Geochemistry Geological hazards Geology Hazards Human influences Hydrology/Water Resources Landslides Landslides & mudslides Learning algorithms Machine learning Mountain regions Mountainous areas Neural networks Original Article Precipitation Predictions Rainfall Regression analysis Risk assessment Roads & highways Seismic activity Seismic response Spatial variability Spatial variations Support vector machines Terrestrial Pollution Urbanization Valleys Widening Brazil Ecuador Himalaya Mountains Uttarakhand India China India Ensemble models Machine learning algorithms Statistical models Landslide susceptibility zonation mapping Bhagirathi valley
ISSN:	1866-6280, 1866-6299
Online-Zugang:	Volltext
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