International Journal of Disaster Risk Science

This study evaluated four storm surge models: the Global Tide and Surge Model (GTSMv3.0), ERA20C neural network (ERA20C_nn), ERA20C multiple linear regression (ERA20C_ml), and 20th Century Reanalysis multiple linear regression (20CR_ml).

This study proposed a new approach for rapidly estimating post-earthquake building loss with reasonable accuracy. Rapid estimation of post-earthquake building damage and loss is very important in urgent response efforts.

This study analyzed the content of Twitter data collected during Hurricane Harvey to identify the data of the highest relevance for assessing the impacts on infrastructure through automatically grouping the tweets by topics of discussion.

This paper presents a selection of 25 components used to define resilience, and an interesting linkage emerges between these components and the dimensions of risk management.

This study evaluates the build-back-better considerations in post-disaster recovery, following the devastation by Cyclone Idai-induced floods in 2019. Conducted in 2020, the study assesses the impact of Cyclone Idai-induced floods.

This study explored factors that contributed to the successful implementation of tsunami housing projects in Kerala, India.

Quick response research conducted by social scientists in the aftermath of a disaster can reveal important findings about hazards and their impacts on communities. Research to collect perishable data, or data that will change or be lost over time

Evaluated in the context of the priorities and global targets of the SFDRR, the article considers the case of the Great East Japan Earthquake and Tsunami of 2011 to illustrate advances and limitations.