2021
DOI: 10.1111/jfr3.12692
|View full text |Cite
|
Sign up to set email alerts
|

Sentinel‐1 remote sensing data and Hydrologic Engineering Centres River Analysis System two‐dimensional integration for flash flood detection and modelling in New Cairo City, Egypt

Abstract: Digital surface models, land use and rainfall data were used to simulate water areas using Hydrologic Engineering Centres River Analysis System (HEC‐RAS) software. Multi‐temporal synthetic aperture radar (SAR) was used for the detection of flood prone area to calibrate HEC‐RAS, due to the lack of data validation in the New Cairo City, Egypt. The thresholding water detection method was applied to two Sentinel‐1 images, one pre‐ and one post‐flash flood event from April 24 to 27, 2018. The threshold method was u… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
9
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7
2
1

Relationship

0
10

Authors

Journals

citations
Cited by 28 publications
(9 citation statements)
references
References 67 publications
0
9
0
Order By: Relevance
“…Based on the backscattering intensity of the SAR image where water appears as a dark area resulting in a low backscatter recording as incident radar signals are reflected away from the radar antenna (Henderson & Lewis, 1998), one can visualize and interpret flooding based on various classification methods. This includes a simple visual interpretation approach (Matgen et al, 2007;Oberstadler et al, 1997;Sanyal & Lu, 2004), image change detection (Bazi et al, 2005;Clement et al, 2018;Nico et al, 2000), region growing algorithms (Malnes et al, 2002;Mason et al, 2012), supervised classification (Pulvirenti et al, 2013;Townsend, 2002), histogram thresholding (Chini et al, 2012;Elkhrachy et al, 2021;Pulvirenti et al, 2016), and clustering algorithm (Ruzza et al, 2019). Further, many flood detection approaches have used a combination of thresholding, region growing, and change detection utilizing a single SAR image Matgen et al, 2011).…”
Section: Introductionmentioning
confidence: 99%
“…Based on the backscattering intensity of the SAR image where water appears as a dark area resulting in a low backscatter recording as incident radar signals are reflected away from the radar antenna (Henderson & Lewis, 1998), one can visualize and interpret flooding based on various classification methods. This includes a simple visual interpretation approach (Matgen et al, 2007;Oberstadler et al, 1997;Sanyal & Lu, 2004), image change detection (Bazi et al, 2005;Clement et al, 2018;Nico et al, 2000), region growing algorithms (Malnes et al, 2002;Mason et al, 2012), supervised classification (Pulvirenti et al, 2013;Townsend, 2002), histogram thresholding (Chini et al, 2012;Elkhrachy et al, 2021;Pulvirenti et al, 2016), and clustering algorithm (Ruzza et al, 2019). Further, many flood detection approaches have used a combination of thresholding, region growing, and change detection utilizing a single SAR image Matgen et al, 2011).…”
Section: Introductionmentioning
confidence: 99%
“…Using SAR images, it can be used to distinguish water from other objects. Therefore, Sentinel-1 has often been used in the research of flash floods in recent years [65][66][67][68].…”
Section: A Time Zone Map Of Abstractmentioning
confidence: 99%
“…Apart from multiple applications of Sentinel-1, it uses a wide area coverage with near real-time data acquisition making it a more feasible tool allowing for more efficient and cost-effective use. Over the last few decades, a considerable number of studies have been through on the SAR flood mapping method in combination with other Remote Sensing (RS) imageries (Mimich et al 2021;Jokar et al 2022) whereas other researchers suggest the use of Sentinel-1 radar image to calibrate (Elkhrachy et al 2021) or validate the extent derived using other models (Ezzine et al 2020).…”
Section: Introductionmentioning
confidence: 99%