The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Sentinel-1-based flood mapping: a fully automated processing chain
Abstract
This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-real-time (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows deriving time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0% and 96.1% and Cohen’s kappa coefficients (κ) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.
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Citations
Cites
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Self-citationTowards an automated SAR-based flood monitoring system: Lessons learned from two case studies
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Satellite Image Analysis for Disaster and Crisis-Management Support
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Envisat multi‐polarized ASAR data for flood mapping
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Automated global water mapping based on wide-swath orbital synthetic-aperture radar
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Cited by
DeVries, B., Huang, C., Armston, J., Huang, W., Jones, J. W., & Lang, M. W. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2020.111664 · Cited by 518
Multi‐temporal synthetic aperture radar flood mapping using change detection
Clement, M. A., Kilsby, C. G., & Moore, P. (2018) · Journal of Flood Risk Management · doi:10.1111/jfr3.12303 · Cited by 403
A review of remote sensing applications for water security: Quantity, quality, and extremes
Chawla, I., Karthikeyan, L., & Mishra, A. K. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.124826 · Cited by 363
A local thresholding approach to flood water delineation using Sentinel-1 SAR imagery
Liang, J., & Liu, D. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.10.017 · Cited by 328
The Pakistan Flood of August 2022: Causes and Implications
Nanditha, J. S., Kushwaha, A. P., Singh, R., Malik, I., Solanki, H., Chuphal, D. S., Dangar, S., Mahto, S. S., Vegad, U., & Mishra, V. (2023) · Earth's Future · doi:10.1029/2022ef003230 · Cited by 269
Metadata
- Authors
- Twele, A., Cao, W., Plank, S., & Martinis, S.
- Venue
- International Journal of Remote Sensing
- Publisher
- Informa UK Limited
- Published
- 2016-06-28
- Volume
- 37
- Issue
- 13
- Pages
- 2990-3004
- ISSN
- 0143-1161 (ISSN-L)
- 1366-5901
- OpenAlex
- W2462089918
- Cited by
- 629
- References
- 14
- FWCI
- 26.80
- Type
- journal article
- Language
- en
- Open access
- closed
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