Department of Civil & Environmental Engineering, University of South Carolina, Columbia, SC 29208, USA
Viewed
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 2,086 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,669
349
68
2,086
61
89
HTML: 1,669
PDF: 349
XML: 68
Total: 2,086
BibTeX: 61
EndNote: 89
Views and downloads (calculated since 10 May 2023)
Cumulative views and downloads
(calculated since 10 May 2023)
Total article views: 1,866 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,449
349
68
1,866
58
83
HTML: 1,449
PDF: 349
XML: 68
Total: 1,866
BibTeX: 58
EndNote: 83
Views and downloads (calculated since 15 Nov 2023)
Cumulative views and downloads
(calculated since 15 Nov 2023)
Total article views: 220 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
220
0
0
220
3
6
HTML: 220
PDF: 0
XML: 0
Total: 220
BibTeX: 3
EndNote: 6
Views and downloads (calculated since 10 May 2023)
Cumulative views and downloads
(calculated since 10 May 2023)
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 2,086 (including HTML, PDF, and XML)
Thereof 2,078 with geography defined
and 8 with unknown origin.
Total article views: 1,866 (including HTML, PDF, and XML)
Thereof 1,858 with geography defined
and 8 with unknown origin.
Total article views: 220 (including HTML, PDF, and XML)
Thereof 220 with geography defined
and 0 with unknown origin.
Predicting flood magnitude and location helps decision-makers to better prepare for flood events. To increase the speed and availability of data during flooding, this study presents a vision-based framework for measuring water levels and detecting floods. The deep learning models use time-lapse images captured by surveillance cameras to detect water extent using semantic segmentation and to transform them into water level values with the help of lidar data.
Predicting flood magnitude and location helps decision-makers to better prepare for flood...
