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Combination of Radar and Optical Images for Rapid Flood Detection and Monitoring in Google Earth Engine Environment, (Case Study: Sheerestan Dashtiari Flood March 2024)

Document Type : Original Article

Authors
Rashed Dehani 1
Ahmad Mazidi 2
1 Doctoral student of Climatology in Environmental Planning, Yazd University, Yazd, Iran.
2 Associate Professor of Climatology in Environmental Planning, Department of Geography, Yazd University, Yazd, Iran.
10.30467/nivar.2024.474067.1305
Abstract
Flash floods are one of the common natural hazards in the Sistan and Baluchistan region, which causes extensive damage to local communities. In this study, Sentinel 1 and Landsat 8 satellite images were used in the rapid identification and monitoring of flooded areas. The availability of these images with the use of cloud computing systems such as Google Earth Engine (GEE) provides a valuable opportunity for crisis management, as it enables easy access to ready data, which is essential for effective management programs deal with floods. Sentinel 1 radar images and Landsat 8 optical images were extracted the day before and after the recent floods March 2024 in the studied area. Image processing and extraction of features related to floods including water cover, water level changes and land cover changes were done. The results showed that the images of Sentinel 1 can effectively identify the flooded areas in Dashtiari region due to the power of cloud penetration and independence from light conditions. Also, Landsat 8 images were useful for more accurate assessment of water level and land cover. The combination of these two data sources increased the ability to quickly detect and monitor flood-affected areas. The integration of satellite remote sensing data can be an effective tool for flood crisis management in the region. This approach will help local authorities in planning emergency responses and mitigating the consequences of flooding.
Keywords
Flood Monitoring
Dashtiari
Landsat 8
Sentinel 1
Google Earth Engine
Subjects
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Nivar
Volume 48, 126-127 - Serial Number 126
October 2024
Pages 138-150

  • Receive Date 18 August 2024
  • Revise Date 24 October 2024
  • Accept Date 03 November 2024
  • Publish Date 22 September 2024