Building loss assessment using deep learning algorithm from typhoon Rusa
Climate crises such as extreme weather events, natural disasters and climate change caused by climate transformations are causing much damage worldwide enough to be called a climate catastrophe. The private sector and the government across industries are making every effort to prevent and limit the...
Main Authors: | Ji-Myong Kim, Junseo Bae, Manik Das Adhikari, Sang-Guk Yum |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2024-01-01
|
Series: | Heliyon |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023105329 |
Similar Items
-
A study of deep learning algorithm usage in predicting building loss ratio due to typhoons: the case of southern part of the Korean Peninsula
by: Ji-Myong Kim, et al.
Published: (2023-08-01) -
Identification of synoptic patterns for extreme rainfall events associated with landfalling typhoons in China during 1960–2020
by: Da-Jun Zhao, et al.
Published: (2022-10-01) -
Impacts of Tides and Typhoon Fanapi (2010) on Seas Around Taiwan
by: Dong S. Ko, et al.
Published: (2016-04-01) -
Responding to Typhoon Haiyan in the Philippines
by: Michelle McPherson, et al.
Published: (2015-11-01) -
Statistical analysis of the characteristics of typhoons approaching Japan from 2006 to 2019
by: Sridhara Nayak, et al.
Published: (2023-12-01)