Results 91 to 100 of about 1,693,251 (168)

Assessing Deep Learning Segmentation Models for Mapping Landslides From LiDAR‐Based Elevation Data

Earth and Space Science, Volume 13, Issue 10, October 2026.
Abstract Robust landslide inventories are critical for characterizing landslide hazard and helping reduce societal vulnerability. For this study, LiDAR‐derived digital elevation models (DEMs), their derivatives, and a landslide inventory were used to train different deep learning segmentation models to assess the functionality of automatic segmentation
Hudson J. Koch, Junfeng Zhu, Shashank Bhatt, Nathan Jacobs, Jason M. Dortch   +4 more
wiley   +1 more source

Uncertainty in Precipitation Estimates Warrants Greater Consideration in Debris‐Flow Research

Journal of Geophysical Research: Earth Surface, Volume 131, Issue 10, October 2026.
Abstract Quantitative precipitation estimates (QPEs) may provide a valuable data resource for investigations of postfire debris flows. In mountainous regions where debris flows typically occur, gauge coverage can be sparse; gridded QPEs offer remotely sensed and/or physics‐based precipitation estimates where no direct measurement is available. However,
Ann E. Sinclair, Nina S. Oakley, A. Joshua West, Marin K. Clark, Daniel E. Horton   +4 more
wiley   +1 more source

Mapping earthquake-triggered landslide susceptibility by use of artificial neural network (ANN) models: an example of the 2013 Minxian (China) Mw 5.9 event

Geomatics, Natural Hazards & Risk, 2019
A landslide susceptibility map, which describes the quantitative relationship between known landslides and control factors, is essential to link the theoretical prediction with practical disaster reduction measures.
Yingying Tian, Chong Xu, Haoyuan Hong, Qing Zhou, Duo Wang   +4 more
doaj   +1 more source

Shallow Landslides Align With Atmospheric Rivers in Coastal Steeplands

Geophysical Research Letters, Volume 53, Issue 18, 28 September 2026.
Abstract Rapid, shallow landslides in coastal mountains are triggered by extreme precipitation, shaping topography and impacting human settlements. Using an inventory of >700 landslides mapped from satellite imagery (2009–2024) and an atmospheric river database (1981–2019), this study documents linkages between climatic drivers and the topographic ...
Joshua J. Roering, Eliza R. Lawrence, Ries Plescher, Maryn A. Sanders, Deanna Nash, Annette I. Patton, Adelaide Johnson, Aaron Jacobs, Nicolas W. Mathews, Lia Salomon, Stephen McKay, Wolfgang Schwanghart, William Struble, Quinn Aboudara   +13 more
wiley   +1 more source

A comparative analysis of web-based tools for landslide mapping and visualization

Smart Construction and Sustainable Cities
Effective management of landslide events requires robust mapping and visualization tools to ensure prompt responses and a thorough understanding of the situation.
Badariah Solemon, Alshami Mohammed Zaid Ahmed, Nur Aishah Zarime   +2 more
doaj   +1 more source

Harnessing InSAR and Machine Learning for Geotectonic Unit-Specific Landslide Susceptibility Mapping: The Case of Western Greece

Remote Sensing
Landslides are one of the most severe geohazards globally, causing extreme financial and social losses. While InSAR time-series analyses provide valuable insights into landslide detection, mapping, and monitoring, AI is also implemented in a variety of ...
Stavroula Alatza, Alexis Apostolakis, Constantinos Loupasakis, Charalampos Kontoes, Martha Kokkalidou, Nikolaos S. Bartsotas, Georgios Christopoulos   +6 more
doaj   +1 more source

Linking Extreme Precipitation to Pluvial Hydrometeorological Disasters in Southeast Asia Using a Long‐Term Event Database

Geophysical Research Letters, Volume 53, Issue 18, 28 September 2026.
Abstract Frequent pluvial hydrometeorological disasters in Southeast Asia (SEA) threaten lives and property, yet the region lacks a unified disaster data set for risk management and research. This study develops a provincial‐level data set integrating multi‐source hazard reports with precipitation data and identifies empirical rainfall reference values
Junjun Li, Jingyu Wang, Hui Su, Xianfeng Wang, Edward Park, Raju Pathak, Dung Duc Tran, Luojie Dong   +7 more
wiley   +1 more source

Human Impact Index in Landslide Susceptibility Mapping

, 2010
Human activities which are represented by human impact index in landslide susceptibility mapping have great impact on the landslide occurrences in urban areas, especially in those fast developing areas.
Tian, Yuan, Wu, Lun, Liu, Yu, Zhao, Wenyi, Yuan Tian, Lun Wu, Yu Liu, Wenyi Zhao   +7 more
core   +1 more source

Study on landslide susceptibility mapping with different factor screening methods and random forest models. [PDF]

PLoS One, 2023
Gu T, Li J, Wang M, Duan P, Zhang Y, Cheng L.   +5 more
europepmc   +1 more source

Application of Transformer Models to Landslide Susceptibility Mapping. [PDF]

Sensors (Basel), 2022
Bao S, Liu J, Wang L, Zhao X.
europepmc   +1 more source