Automatic extraction of flood inundation areas from SAR images: a case study of Jilin, China during the 2017 flood disaster-Reference-Cited by-同舟云学术

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Automatic extraction of flood inundation areas from SAR images: a case study of Jilin, China during the 2017 flood disaster

Published:2019-02-12 Issue:13 Volume:40 Page:5050-5077
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wan L.¹²³,Liu M.⁴,Wang F.¹²,Zhang T.¹²³^ORCID,You H. J.¹²³

Affiliation:

1. Institute of Electronics, Chinese Academy of Sciences, Beijing, China

2. Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Beijing, China

3. University of Chinese Academy of Sciences, Beijing, China

4. Satellite Application Center for Disaster Reduction, MCA, Beijing, China

Funder

the National Key R&D Program of China

the HREOS project

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1577999

Reference43 articles.

1. A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery

2. Geographic Object-Based Image Analysis – Towards a new paradigm

3. Progress in operational flood mapping using satellite synthetic aperture radar (SAR) and airborne light detection and ranging (LiDAR) data

4. Sentinel-1-based flood mapping: a fully automated processing chain

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1. Residual wave vision U-Net for flood mapping using dual polarization Sentinel-1 SAR imagery;International Journal of Applied Earth Observation and Geoinformation;2024-03

2. CLDRNet: A Difference Refinement Network Based on Category Context Learning for Remote Sensing Image Change Detection;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. Water Stream Extraction via Feature-Fused Encoder-Decoder Network Based on SAR Images;Remote Sensing;2023-03-13

4. Detecting Urban Floods with Small and Large Scale Analysis of ALOS-2/PALSAR-2 Data;Remote Sensing;2023-01-16

5. Flood mapping and damage assessment due to the super cyclone Yaas using Google Earth Engine in Purba Medinipur, West Bengal, India;Environmental Monitoring and Assessment;2022-10-12

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