Detecting urban changes using phase correlation and ℓ1-based sparse model for early disaster response: A case study of the 2018 Sulawesi Indonesia earthquake-tsunami

Author:

Moya LuisORCID,Muhari Abdul,Adriano Bruno,Koshimura ShunichiORCID,Mas Erick,Marval-Perez Luis R.,Yokoya Naoto

Funder

Japan Society for the Promotion of Science

Japan Science and Technology Agency

Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference49 articles.

1. Buildings damage due to the 2013 haiyan typhoon inferred from Sar intensity images;Adriano,2015

2. Coastal subsidence induced several tsunamis during the 2018 Sulawesi earthquake;Arikawa;Journal of Disaster Research,2018

3. A framework of rapid regional tsunami damage recognition from post-event terrasar-x imagery using deep neural networks;Bai;IEEE Geosci. Remote Sens. Lett.,2018

4. Early and persistent supershear rupture of the 2018 magnitude 7.5 Palu earthquake;Bao;Nat. Geosci.,2019

5. Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python;Canty,2014

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