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: 3,738 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,964
682
92
3,738
99
130
HTML: 2,964
PDF: 682
XML: 92
Total: 3,738
BibTeX: 99
EndNote: 130
Views and downloads (calculated since 10 May 2023)
Cumulative views and downloads
(calculated since 10 May 2023)
Total article views: 2,844 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,094
658
92
2,844
80
111
HTML: 2,094
PDF: 658
XML: 92
Total: 2,844
BibTeX: 80
EndNote: 111
Views and downloads (calculated since 15 Nov 2023)
Cumulative views and downloads
(calculated since 15 Nov 2023)
Total article views: 894 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
870
24
0
894
19
19
HTML: 870
PDF: 24
XML: 0
Total: 894
BibTeX: 19
EndNote: 19
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: 3,738 (including HTML, PDF, and XML)
Thereof 3,706 with geography defined
and 32 with unknown origin.
Total article views: 2,844 (including HTML, PDF, and XML)
Thereof 2,812 with geography defined
and 32 with unknown origin.
Total article views: 894 (including HTML, PDF, and XML)
Thereof 894 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...