Evaluation of typhoon-induced inundation losses associated with LULC using multi-temporal SAR and optical images

Evaluation of typhoon-induced inundation losses associated with LULC using multi-temporal SAR and optical images

We utilized a two-branch end-to-end network (MultiSenCNN) for land use and land cover (LULC) classification and flood event mapping using multispectral (MS), panchromatic (Pan) and synthetic aperture radar (SAR) images, where flooding was induced by typhoon Lekima in August 2019. Flood damages were...

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Bibliographic Details
Main Authors: Jiafeng Wang, Yongjiu Feng, Rong Wang, Xiaohua Tong, Shurui Chen, Zhenkun Lei, Pengshuo Li, Mengrong Xi
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
LULC classification
flood mapping
synthetic aperture radar
deep learning
inundation assessment
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2022.2112624

Internet

https://www.tandfonline.com/doi/10.1080/19475705.2022.2112624

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