Hurricane damage assessment using coupled convolutional neural networks: a case study of hurricane Michael-Reference-Cited by-同舟云学术

Hurricane damage assessment using coupled convolutional neural networks: a case study of hurricane Michael

Published:2022-01-27 Issue:1 Volume:13 Page:414-431
ISSN:1947-5705
Container-title:Geomatics, Natural Hazards and Risk
language:en
Short-container-title:Geomatics, Natural Hazards and Risk

Author:

Berezina Polina¹,Liu Desheng¹^ORCID

Affiliation:

1. Department of Geography, Ohio State University, Columbus, OH, USA

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19475705.2022.2030414

Reference53 articles.

1. Post-Tsunami Urban Damage Assessment in Thailand, Using Optical Satellite Imagery and the VIEWSTM Field Reconnaissance System

2. Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification

3. Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

4. Beven II, JL, Berg R, Hagen A. 2019. National Hurricane Center’s Tropical Cyclone Report: Hurricane Michael (AL142018). Retrieved from https://www.nhc.noaa.gov/data/tcr/AL142018_Michael.pdf.

5. Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks

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