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.

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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.

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Previous Research using SAR

Flood Mapping, Tewkesbury, U.K

Oil spill off the Spanish coast

Flood monitoring and forecasting using SAR and meteorological data

Area of interest for monitoring and forecasting flood

Schematic diagram of the method of flood monitoring system

Results: From Meteorological Data and DEM

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

Results: From DEM

Digital elevation model (DEM) of the white rectangle area

Prediction of different flooded areas

Prediction of different flooded areas at Sylhet region

Shaded water surface areas (red) on March 14, 2017

Shaded water surface areas (red) on May 25, 2017

Shaded water surface areas (red) on August 05, 2017

Flood map on August 19, 2018. Red border indicates AOI

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.

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