flood monitoring and forecasting using sar and...
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Flood Monitoring and Forecasting Using SAR and Meteorological Data: A case
StudyDr. S.N.M. Azizul Hoque, PI
Assistant Professor, Department of Physical Sciences, IUB
Mafijul Islam Bhuiyan, External Expert Session: Disaster Management (Room 3002)
10 January, 2019
11/3/2019
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Objectives of the project
To develop a Geospatial Intelligent (GEOINT)system using Synthetic Aperture Radar (SAR)imageries and machine learning methods wherebywe can protect the people of rural and coastalareas via mitigating the devastation of natural andman-made calamities.
1/3/2019
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Output of the project
• To monitor the flooded and deforested areas, predict the critical segments of riverbank/embankment
• A software package to produce all the value added geospatial products.
• A web portal to share all the information.
1/3/2019
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Previous Research using SAR
Flood Mapping, Tewkesbury, U.K
Oil spill off the Spanish coast
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Flood monitoring and forecasting using SAR and meteorological data
Area of interest for monitoring and forecasting flood
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Schematic diagram of the method of flood monitoring system
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Results: From Meteorological Data and DEM
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Results: From DEM
Flat Digital Elevation Model (DEM) of the
AOI. Black dotted line indicates Indian
mountainous area with high elevation.
Elevation of the AOI from north to south
direction
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Results: From DEM
Digital elevation model (DEM) of the white rectangle area
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Prediction of different flooded areas
Prediction of different flooded areas at Sylhet region
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Shaded water surface areas (red) on March 14, 2017
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Shaded water surface areas (red) on May 25, 2017
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Shaded water surface areas (red) on August 05, 2017
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Flood map on August 19, 2018. Red border indicates AOI
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Percentage of affected areas and area
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Date % of water
surface area
Water surface
area (km2)
March 14, 2017
(winter)
0.09 11.88
May 25, 2017 26.93 3554.76
June 06, 2017 28.7 3788.4
June 18, 2017 20.73 2736.36
June 30, 2017 26.23 3462.36
July 12, 2017 35.99 4750.68
July 24, 2017 22.82 3012.24
August 5, 2017 31.8 4197.6
September 10, 2017 35.17 4642.44
September 22, 2017 35.16 4641.12
The dimension of the total area is
13200 km2. The mean level of the
flooded area is 3865.1 km2 with the
standard deviation of 738.8 km2
during the wet season (from March
25, 2017 to September 22, 2017).
Fig.: Areas of the water surface during different
temporal baselines.
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• The forecasting of the flood was retrospective forecasting rather than realforecasting.
• In future, by obtaining images with 6-days or 4-days intervals from any commercialsatellite company will make flood the monitoring system more effective.
1/3/2019
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