Random forest-based multi-hazard loss estimation using hypothetical data at seismic and tsunami monitoring networks

Measure and spatial identification of social vulnerability, exposure and risk to natural hazards in Japan using open data

(2023) Theo Raduszynski et al.   Scientific Reports

Seismic vulnerability and risk assessment at the urban scale using support vector machine and GIScience technology: a case study of the Lixia District in Jinan City, China

(2023) Yaohui Liu et al.   Geomatics Natural Hazards & Risk

Flood susceptibility modeling of the Karnali river basin of Nepal using different machine learning approaches

(2023) Sunil Duwal et al.   Geomatics Natural Hazards & Risk

A Hybrid Multi-Hazard Susceptibility Assessment Model for a Basin in Elazig Province, Türkiye

(2023) Gizem Karakas et al.   International Journal of Disaster Risk Science

Risk-based tsunami early warning using random forest

(2023) Yao Li et al.   COMPUTERS & GEOSCIENCES

Comparison of national and local building inventories for damage and loss modeling of seismic and tsunami hazards: From parcel-to city-scale

(2023) Dylan Sanderson et al.   International Journal of Disaster Risk Reduction

Testing machine learning models for seismic damage prediction at a regional scale using building-damage dataset compiled after the 2015 Gorkha Nepal earthquake

(2022) Subash Ghimire et al.   EARTHQUAKE SPECTRA

Multi-hazard mapping of droughts and forest fires using a multi-layer hazards approach with machine learning algorithms

(2022) Yong Piao et al.   Geomatics Natural Hazards & Risk

Machine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami

(2022) Riantini Virtriana et al.   Geomatics Natural Hazards & Risk

Multi-hazard parametric catastrophe bond trigger design for subduction earthquakes and tsunamis

(2021) Katsuichiro Goda   EARTHQUAKE SPECTRA

Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area

(2021) Meriame Mohajane et al.   ECOLOGICAL INDICATORS

A CitSci Approach for Rapid Earthquake Intensity Mapping: A Case Study from Istanbul (Turkey)

(2020) Ilyas Yalcin et al.   ISPRS International Journal of Geo-Information

Prediction of coastal flooding risk under climate change impacts in South Korea using machine learning algorithms

(2020) Sang-Jin Park et al.   Environmental Research Letters

Adjustability of exposed elements by updating their capacity for resistance after a damaging event: application to an earthquake–tsunami cascade scenario

(2020) Caterina Negulescu et al.   NATURAL HAZARDS

Probabilistic seismic and tsunami damage analysis (PSTDA) of the Cascadia Subduction Zone applied to Seaside, Oregon

(2019) Hyoungsu Park et al.   International Journal of Disaster Risk Reduction

Rapid tsunami loss estimation using regional inundation hazard metrics derived from stochastic tsunami simulation

(2019) Katsuichiro Goda et al.   International Journal of Disaster Risk Reduction

Proposed methodology for building‐specific earthquake loss assessment including column residual axial shortening

(2019) Ahmed Elkady et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

Hypothetical Real‐Time GNSS Modeling of the 2016 Mw 7.8 Kaikōura Earthquake: Perspectives from Ground Motion and Tsunami Inundation Prediction

(2018) Brendan W. Crowell et al.   BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA

Multi-hazard loss estimation for shaking and tsunami using stochastic rupture sources

(2018) Katsuichiro Goda et al.   International Journal of Disaster Risk Reduction

A GIS-based approach for earthquake loss estimation based on the immediate extraction of damaged buildings

(2016) Hamid Reza Ranjbar et al.   Geomatics Natural Hazards & Risk

Tsunami impact and vulnerability in the harbour area of Tangier, Morocco

(2013) Sabah Benchekroun et al.   Geomatics Natural Hazards & Risk

Rapid earthquake loss assessment after damaging earthquakes

(2010) M. Erdik et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman

(2009) Klaus Nordhausen   INTERNATIONAL STATISTICAL REVIEW