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REMOTE SENSING FOR FLOOD HAZARD STUDIES.

OPTICAL SENSORS.OPTICAL SENSORS.

DRS. NANETTE C. KINGMA

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Optical Remote Sensing for flood hazard studies.

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Floods & use of remote sensing.

Floods often leaves its imprint or ‘signature” on the surface in the form of soil moisture anomalies (increase), standing water bodies, soil scours, stressed vegetation, debris, and other indicators.⇒ reduced reflectivity.

⇒Use RS imagery a few days after the flood event upto 2 weeks.

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Floods & use of remote sensing.

Major drawback optical sensors cannot penetrate cloud;Instead combine with cloud penetrating radar.

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Remote Sensing for Flood Hazard Studies.

Different applications;Different approaches;Different platforms;

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Remote Sensing for Flood Hazard Studies: applications.

Mapping spatial distribution of inundated areas;Mapping spatial distribution of flood effects;Indirect mapping to make flood susceptibility maps using flood indicators;Flood hazard zonation using sequential imagery and or integrating different types of imagery;Damage assessment post flood;Planning of emergency & relief operations;

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Remote Sensing for Flood Hazard Studies: applications.

Monitoring for early warning;sequential inundation stage mapping; Generating DEM’s for modelling etc.;Combining DEM with areal extent map to find flood depth map (if DEM detailed enough).

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Types of Sensors

1. Space-borne imaging sensors:A. Multi-spectral sensors:

– Landsat MSS, -TM, SPOT, IRS, JERS (OPS),IKONOS, ASTER. B. Radar systems (SAR):

– ERS, JERS, RadarsatC. Environmental sensors:

– NOAA (AVHRR) 2. Air-borne imaging sensors:

A. Aerial photography B. Multi-spectral airborne sensorsC. Synthetic Aperture Radar (SAR)D. Video mapping

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Spaceborne Optical Sensors

A. Panchromatic and multi-spectral sensors:– LANDSAT-MSS, Thematic Mapper, Enhanced Thematic Mapper Plus.– SPOT-XS and SPOT-Panchromatic– India Remote Sensing Satellite (IRS) – Japan Earth Resources Satellite (JERS - OPS)– ASTER

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Common Spectral Bands

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Multi-spectral scanners

Advantages of multi-spectral scanner data:high spectral resolution;moderate temporal resolution;good processing software on the market;different sensors spectrally good compatible.

Disadvantages of multi-spectral scanner data:recent data relative expensive;( * ASTER)long ordering time;cloud coverage.

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Landsat TM

Landsat Thematic Mapper (TM-4 & -5)

Large areas covered by one scene (185 * 185 km)Temporal resolution: 18 daysOrbit nearly polar and sun-synchronic (705 km high)Good spectral resolution: 7 bands (0.45 - 2.35 um)Average spatial resolution:

- Spatial resolution bands 1 - 5, 7: 30 m- Spatial resolution band 6: 120 m

No stereo capabilities

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Landsat TM

Landsat Thematic Mapper (TM 7 ETM+)

Large areas covered by one scene (185 * 185 km)Temporal resolution: 16 daysOrbit nearly polar and sun-synchronic (705 km high)Good spectral resolution: 7 bands (0.45 - 2.35 um)Average spatial resolution:

- Panchromatic band: 15 m- Spatial resolution bands 1 - 5, 7: 30 m- Spatial resolution thermal band 6: 60 m

No stereo capabilities

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Landsat TM

Landsat Thematic Mapper bands

Band 1 .45 - .52 um - maximum penetration of waterBand 2 .52 - .60 um - reflection peak of vegetationBand 3 .63 - .69 um - chlorophyll absorption bandBand 4 .76 - .90 um - mapping of waterbodiesBand 5 1.55- 1.75 um - moisture content of the soilBand 6 10.4-12.50 um - thermal IRBand 7 2.08 -2.35 um - hydrothermally altered rocks

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Landsat TM for Flood Hazard studies -1

Landsat Thematic Mapper band combinations:

Mapping upto 1 : 50.000;FCC: Bands: 4 / 3 / 2 or Bnd 4 / 3 / 1 ; RGBTM-Band 4 Separation of land and water.TM-Band 5 Moisture content of soil and vegetation.Other: Bands: 1 / 3 / 5 soil and sediment studiesTasseled cap transformation; optimize data viewing for vegetation studies: brightness image, greenness-image , and wetness-image.

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Landsat TM example

Landsat Thematic Mapper (TM -4 & -5)Example of flooding in Caprivi, Zambezi-river and Chobe-river,

Namibia.– Date: 12 March 1989; resolution: 30 m– Processing Color Composite: R/G/B: 5 ,4 ,3.

Chobe river

Zambezi river

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Comparing TM Band 4 and TM Band 5.

Example from Caprivi, Namibia.Date: 02/07/1989

band 4 (land water boundaries) band 5 (humid soils &veget.)

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Band comparison.

Mississippi flood 1993.

Band 4 TM Band 5 TM

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Landsat TM example

Landsat Thematic Mapper (TM -4 & -5)Example of flooding in Caprivi, Zambezi-river and Chobe-river,

Namibia.– Date: August 19, 1989. Resolution: 30 m.– Processing Color Composite: R/G/B: 4 / 5 / 3

High soil moisture content

Zambezi river

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Caprivi Flood Hazard Map.

VL

VH

MH

L

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Detecting land and water boundaries.

Band 4 of TM: Example of the Missouri river pre-and post flood 1993.

Original (left) and stretched (righthand side) ; band 4.

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Selecting band combinations for detecting land – water boundaries.

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Geomorphological effects of the 1993-flood

hills

floodplain

TM images: bands 7, 5, and 3 (R,G,B).

Missouri River Floodplain, Glasgow, Missouri, USA.

http://edcwww2.cr.usgs.gov/moberly/preflood.gif

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Totally inundatedfloodplain.

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Sand deposits, from levee breaches.

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Flash flood in an arid country.

⇒ only mapping of flood effect possible.

Yemen, June 1997 flood.

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SPOT

– Area covered by one scene 60 * 60 km– Temporal resolution:

- vertical look angle: 26 days- oblique look angle: 4 days

– Orbit nearly polar and sun-synchronic (823 km high)– Average spectral resolution:

- 3 bands in XS mode (0.50 - 0.89 um)- 1 band in panchromatic mode (0.50 - 0.75 um)

– Average spatial resolution:- XS mode : 20 m- Panchromatic mode: 10 m

– Stereo capabilities

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SPOT

– Spectral resolution:3 bands in XS mode (0.50 - 0.89 um):

SPOT band 1: 0.5 - 0.6 µ m ( green light);SPOT band 2: 0.6 - 0.7 µ m ( red light);SPOT band 3: 0.8 - 0.9 µ m ( near infra-red light)

SPOT band 3: separation land - water.SPOT band 1: water-sediment studies.SPOT FCC flood effects, damage assessment etc.SPOT stereo image interpretation

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Spot band versus band .

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SPOT XS example

Example of the 1988 Flood in Bangladesh:– SPOT-XS of 10 October 1988. Resolution: 20 m– Processing FCC: Red, Green, Blue: bands 3, 2, 1

Ganges

Meghna

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1

2

3

4

5

6

7

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Monitoring geomorphological change.

.Bangladesh SPOT, TM imagery

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SPOT PAN example

Example of Missouri river near St-Louis in the 1993 flood, USA.– SPOT PANCHROMATIC, 23/07/1993– Resolution: 10 m

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Mapping land and water boundaries.

Example from Bangladesh using SPOT.Processing: in SPOT band 3 density slicing.

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Cross operation of sliced images.

Jan 87(dry), Nov 87 (mfl), Oct 88.

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Flood affected frequency analysis.

No hazard zone

Low “hazard” area

Medium “hazard” area

High “hazard” area.

From: GIS Development 2000

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Multi-temporal image.

R/G/B:

Feb89 /Oct88 / Jan87

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IRS-1C

Indian Remote Sensing satellite (IRS)– Linear Imaging Self-scanning (LISS) system– Temporal resolution 22 - 24 days: – Orbit nearly polar and sun-synchronic (904 km high)

Sensor Bands Spectral Res.Spatial Res.

LISS I 4 0.45 - 0.86 um 72.5 m LISS II 4 0.45 - 0.86 um 36.3 mLISS III 2 0.52 - 0.77 um 23.3 m (visible)

2 0.77 - 1.77 um 70.5 m (RIR)PAN 1 0.50 - 0.75 um 5.8 mWiFS 2 0.62 - 0.75 um 188 m(Wide field sensor)

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JERS-1 SAR/OPS

Japanese Earth Resource Satellite (JERS-1)Launched November 1995

Optical Sensor (OPS)– Area covered by one scene 75 * 75 km– Temporal resolution: 44 days – Orbit nearly polar and sun-synchronic (568 km high)– Spectral resolution:

- 2 bands visible 0.52 - 0.60 :m (green) 0.63 - 0.69 :m (red)- 4 bands Refl. IR 0.76 - 0.86 :m (near IR) 1.60 - 1.71 :m (mid IR) 2.01- 2.12

:m , 2.13 - 2.25 :m, 2.27 - 2.40 :m (mid IR)

– Spatial resolution: 20 m – Stereo capabilities (band 4 off-nadir look angle)

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JERS-1 OPS example

Jamuna river

Ganges river

1998 /07/27

Band combination:321

Resampled: to 25 x 25 m.

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Aster characteristics.

High spatial resolution;Wide spectral range of visible, near IR , short wave IR and thermal IR;Stereo view in the same orbit.

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ASTER.

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LANDSAT versus ASTER.

Maastricht

Meuse river north of Maastricht.

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Case study Tanaro river- Italy.

Precipitation 3 days : 350 mmintensity max: 54 mm/h

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Tasseled cap transform.

Tasseled cap transform is a way to optimize data viewing for vegetation studies.

Crist et al 1986, Crist & Kauth 1986.

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Tasseled cap transform-1.

Brightness:a weighted sum of all bands, defined in the direction of the principal variation in soil reflectance;Greenness; orthogonal to brightness, a contrast between the near infra-red and visible bands; strongly related to the amount of green vegetation in the scene.Wetness: relates to canopy and soil moisture.

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Brightness = 0.3037(TM1) + 0.2793(TM2) + 0.4743(TM3) + 0.5585(TM4) + 0.5082(TM5) + 1.865(TM7).Greenness = -0.2848(TM1) - 0.2435(TM2) -0.5436(TM3) + 07243(TM4) + 0.840(TM5) -0.1800(TM7)Wetness = 0.1509 (TM1) + 0.1973 (TM2) + 0.3279 (TM3) + 0.3406 (TM4) - 0.7112 (TM5) - ).4572(TM7).

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Shadow areas

Post-flood imagery of the Tanaro river, Italy.

Brightness, greenness and wetness, in red, green and blue displayed.

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DAEDALUS /ATM SPECTRAL RESOLUTIONS.

CHANNEL WAVELENGTHFROM

TO

1 0.42 0.452 0.45 0.523 0.52 0.604 0.60 0.625 0.63 0.696 0.69 0.757 0.76 0.908 0.91 1.059 1.55 1.7510 2.08 2.3511 8.50 13.012 8.50 13.0

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DAEDALUS /ATM SPECTRAL RESOLUTIONS.

Post-flood imagery of theTanaro river, Italy.

Daedalus/ATM; FCC;

visible spectrum:

Channel 5-3-2

Medium-high altitude flight: 3000m ; mean ground resolution 7.5 m.

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DAEDALUS /ATM SPECTRAL RESOLUTIONS

Post-flood imagery of the Tanaro river, Italy.

Daedalus/ATM; FCC

Channel 8-9-10

Medium-high altitude flight: 3000m ; mean ground resolution 7.5 m.

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Some examples of Aerial photography in flood studies.

Overbankflooding of Sinu river near, Lorica;

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Flood effects-2: Meander chute cut-off.

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Flood effects-3.

Small tributary devasting agricultural lands in Central Tunesia.

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Monitoring inundation for emergency and relief.

Coltaro

Inundated areas

Po river embankement

Inundat6ions behind the levee, due to tributary flood water cannot be drained due to embankment.

Inundated area’s

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References/Further Reading

SPOT IMAGEhttp://www.spotimage.fr

RSI Internationalhttp://www.rsi.ca

ESAhttp://www.esrin.esa.it

Space Imaginghttp://www.spaceimage.com

NASAhttp://www.rspac.ivv.nasa.gov

NOAAwww.saa.noaa.gov

IRS-1www.euromap.de

NASDAwww.eoc.nasda.go.jp

Kramer, H.J., Observation of the earth and its environment: Survey of missions and sensors, Berlin etc. -Springer Verlag, 1996, 960 p. ISBN 3-540-60933-4.

http://www.itc.nl/~bakker/invdir.htmlLinks to Data Providers:

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