REMOTE SENSING FOR FLOOD HAZARD STUDIES.

Transcription

1 REMOTE SENSING FOR FLOOD HAZARD STUDIES. OPTICAL SENSORS. 1 DRS. NANETTE C. KINGMA 1

2 Optical Remote Sensing for flood hazard studies. 2 2

3 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. 3 3

4 Floods & use of remote sensing. Major drawback optical sensors cannot penetrate cloud; Instead combine with cloud penetrating radar. 4 4

5 Remote Sensing for Flood Hazard Studies. Different applications; Different approaches; Different platforms; 5 5

6 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; 6 6

7 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). 7 7

8 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, Radarsat C. Environmental sensors: NOAA (AVHRR) 2. Air-borne imaging sensors: A. Aerial photography B. Multi-spectral airborne sensors C. Synthetic Aperture Radar (SAR) D. Video mapping 8 8

9 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 9 9

10 Common Spectral Bands

11 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

12 Landsat TM Landsat Thematic Mapper (TM-4 & -5) Large areas covered by one scene (185 * 185 km) Temporal resolution: 18 days Orbit nearly polar and sun-synchronic (705 km high) Good spectral resolution: 7 bands ( um) Average spatial resolution: - Spatial resolution bands 1-5, 7: 30 m - Spatial resolution band 6: 120 m No stereo capabilities

13 Landsat TM Landsat Thematic Mapper (TM 7 ETM+) Large areas covered by one scene (185 * 185 km) Temporal resolution: 16 days Orbit nearly polar and sun-synchronic (705 km high) Good spectral resolution: 7 bands ( 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

14 Landsat TM Landsat Thematic Mapper bands Band um - maximum penetration of water Band um - reflection peak of vegetation Band um - chlorophyll absorption band Band um - mapping of waterbodies Band um - moisture content of the soil Band um - thermal IR Band um - hydrothermally altered rocks

15 Landsat TM for Flood Hazard studies - 1 Landsat Thematic Mapper band combinations: 1 5 Mapping upto 1 : ; FCC: Bands: 4 / 3 / 2 or Bnd 4 / 3 / 1 ; RGB TM-Band 4 Separation of land and water. TM-Band 5 Moisture content of soil and vegetation. Other: Bands: 1 / 3 / 5 soil and sediment studies Tasseled cap transformation; optimize data viewing for vegetation studies: brightness image, greenness-image, and wetness-image. 15

16 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. Zambezi river Chobe river

17 Comparing TM Band 4 and TM Band 5. Example from Caprivi, Namibia. Date: 02/07/1989 band 4 (land water boundaries) &veget.) band 5 (humid soils

18 Band comparison. Mississippi flood Band 4 TM Band 5 TM

19 Landsat TM example Landsat Thematic Mapper (TM -4 & -5) Example of flooding in Caprivi, Zambezi-river and Chobe-river, Namibia. Date: August 19, Resolution: 30 m. Processing Color Composite: R/G/B: 4 / 5 / 3 High soil moisture content Zambezi river

20 Caprivi Flood Hazard Map. VH H M VL L

21 Detecting land and water boundaries. Band 4 of TM: Example of the Missouri river preand post flood Original (left) and stretched (righthand side) ; band

22 Selecting band combinations for detecting land water boundaries

23 Geomorphological effects of the 1993-flood floodplain hills TM images: bands 7, 5, and 3 (R,G,B). Missouri River Floodplain, Glasgow, Missouri, USA

24 Totally inundated floodplain

25 Sand deposits, from levee breaches

26 Flash flood in an arid country. only mapping of flood effect possible. 2 6 Yemen, June 1997 flood. 26

27 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 ( um) - 1 band in panchromatic mode ( um) Average spatial resolution: - XS mode : 20 m - Panchromatic mode: 10 m Stereo capabilities

28 SPOT Spectral resolution: 3 bands in XS mode ( um): SPOT band 1: µ m ( green light); SPOT band 2: µ m ( red light); SPOT band 3: 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

29 Spot band versus band

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

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32 Monitoring geomorphological change.. Bangladesh SPOT, TM imagery

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

34 Mapping land and water boundaries. Example from Bangladesh using SPOT. Processing: in SPOT band 3 density slicing

35 Cross operation of sliced images. Jan 87(dry), Nov 87 (mfl), Oct

36 Flood affected frequency analysis. No hazard zone Low hazard area Medium hazard area High hazard area. From: GIS Development

37 Multi-temporal image. R/G/B: Feb89 /Oct88 / Jan

38 IRS-1C Indian Remote Sensing satellite (IRS) Linear Imaging Self-scanning (LISS) system Temporal resolution days: Orbit nearly polar and sun-synchronic (904 km high) Sensor Bands Spectral Res. Spatial Res. LISS I um 72.5 m LISS II um 36.3 m LISS III um 23.3 m (visible) um 70.5 m (RIR) PAN um 5.8 m WiFS um 188 m (Wide field sensor)

39 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 :m (green) :m (red) - 4 bands Refl. IR :m (near IR) :m (mid IR) :m, :m, :m (mid IR) Spatial resolution: 20 m Stereo capabilities (band 4 off-nadir look angle)

40 JERS-1 OPS example Jamuna river 1998 /07/27 Band combination:321 Resampled: to 25 x 25 m. Ganges river

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

42 ASTER

43 LANDSAT versus ASTER. Meuse river north of Maastricht. Maastricht

44 Case study Tanaro river- Italy. Precipitation 3 days : 350 mm intensity max: 54 mm/h

45 Tasseled cap transform. Tasseled cap transform is a way to optimize data viewing for vegetation studies. Crist et al 1986, Crist & Kauth

46 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

47 Tasseled cap transform-2. Brightness = (TM1) (TM2) (TM3) (TM4) (TM5) (TM7). Greenness = (TM1) (TM2) (TM3) (TM4) (TM5) (TM7) Wetness = (TM1) (TM2) (TM3) (TM4) (TM5) - ).4572(TM7)

48 Tasseled cap transform-3. Post-flood imagery of the Tanaro river, Italy. Shadow areas Brightness, greenness and wetness, in red, green and blue displayed

49 DAEDALUS /ATM SPECTRAL RESOLUTIONS. CHANNEL WAVELENGTH FROM TO

50 DAEDALUS /ATM SPECTRAL RESOLUTIONS. Post-flood imagery of the Tanaro river, Italy. Daedalus/ATM; FCC; visible spectrum: Channel Medium-high altitude flight: 3000m ; mean ground resolution 7.5 m

51 DAEDALUS /ATM SPECTRAL RESOLUTIONS Post-flood imagery of the Tanaro river, Italy. Daedalus/ATM; FCC Channel Medium-high altitude flight: 3000m ; mean ground resolution 7.5 m

52 Some examples of Aerial photography in flood studies. Overbank flooding of Sinu river near, Lorica;

53 Flood effects-2: Meander chute cutoff

54 Flood effects-3. Small tributary devasting agricultural lands in Central Tunesia

55 Monitoring inundation for emergency and relief. Inundated areas Inundat6ions behind the levee, due to tributary flood water cannot be drained due to embankment. Coltaro Inundated area s Po river embankement

56 References/Further Reading SPOT IMAGE RSI International ESA Space Imaging NASA NOAA IRS-1 NASDA Kramer, H.J., Observation of the earth and its environment: Survey of missions and sensors, Berlin etc. - Springer Verlag, 1996, 960 p. ISBN Links to Data Providers: