estimating water optical properties.ppt
TRANSCRIPT
Estimating Water Optical Properties, Water Depth and Bottom Albedo Using High Resolution Satellite
Imagery for Coastal Habitat Mapping
Estimating Water Optical Properties, Water Depth and Bottom Albedo Using High Resolution Satellite
Imagery for Coastal Habitat Mapping
S. C. Liew#, P. Chen, B. Saengtuksin, C. W. ChangCentre for Remote Imaging, Sensing and Processing
National University of Singapore
#Corresponding Author ([email protected])
WorldView-2High resolution with 8 spectral bands
Launched: 8 October 20090.46 m panchromatic1.84 m multispectral
8 spectral bands:
Band 1: 429.3 nm (47.3) “Coastal”Band 2: 478.8 nm (54.3) BlueBand 3: 547.5 nm (63.0) GreenBand 4: 607.8 nm (37.4) YellowBand 5: 658.5 nm (57.4) RedBand 6: 723.5 nm (39.3) “Red edge”Band 7: 825.0 nm (98.9) NIR1Band 8: 919.4 nm (99.6) NIR2
Effective wavelength Bandwidth
WV2 Spectral Response
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Wavelength (nm)
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Atm
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Tropical Atmosphere, 4 cm precipitable water
Note the high water vapor absorption in band 6 (“red-edge” band), humid tropical atmosphere
WorldView-2 Image
Semakau, 2010-03-24
Seagrass
Submerged reefs
• The intertidal zone of Semakau has a rich seagrass habitat of several hundred meters in length.
• Such an extensive seagrass habitat is rare in Singapore coastal area. The seagrass habitats in other areas of Singapore mostly occur in patches.
• There are also live corals on the reefs near Semakau.
Classification Map
Semi-automatic classification Based on 8-bands WV-2 image and field survey.
seagrass
Seagrass
Coral rubble with algae/seagrass/coral
Classification of submerged features
• The previous classification map shown was obtained by automatic clustering followed by manual editing guided by extensive ground truth observations.
• Time consuming, requiring visual interpretation• Visual interpretation complicated by effects of
water column– Scattering by suspended particles– Absorption by water and colored dissolved organic
matter– Different water depth
• We attempt to retrieve the water depth, bottom albedo and intrinsic optical properties of coastal sea water over submerged areas using a spectral matching algorithm.
Pre-processing of WorldView-2 Image
• Calibrate to radiance and top-of-atmosphere reflectance• Correct for Rayleigh scattering and gaseous absorptions,
integrated over sensor response functions.• Glint subtraction using band 8 (NIR2)• Convert to subsurface reflectance
S.C. Liew, B. Saengtuksin, and L.K. Kwoh, IEEE 2009 International Geoscience and Remote Sensing Symposium (IGARSS'09), 13 - 17 July 2009, Cape Town, South Africa.
S.C. Liew and J. He, IEEE Geoscience and Remote Sensing Letters 5(4), 701-704, 2008.
Band 8 (NIR2) Image
Note the presence of various surface features
Band 7 (NIR1) Image
Similar surface features are visible
Band 7 (NIR1) after subtracting Band 8
More homogeneous surface
Automatic Isodata clustering of submerged pixels into 50 classes
Above-water land surface masked out by thresholding the NIR2 band
Mean reflectance spectrum of each class is collected and matched with model reflectance
Shallow water reflectance
wL ,L
H)(b
)( ),( bba
Deep Water
Shallow water reflectance Deep water
reflectance
sF
LR
cos
)(
s
ww F
LR
cos)( ,
F
s v
Model of Subsurface shallow water reflectance
)exp(1)( MKHrw Reflection (scattering) from water column
e)(subsurfac angleszenith solar andsensor ,
depth water
cos/1cos/1
tcoefficien extinction ,)()()(
ereflectanc water deep )(
vs
sv
b
w
H
M
baK
r
Reflection (scattering) from sea bottom )exp()(
MKHb
ereflectanc bottom )( b
)exp()(
)exp(1)()( MKHMKHrr bw
Deep water reflectance
)()(
)(
)( 210
b
b
w
ba
bu
ugugr
a() = Absorption coefficient
bb() = Backscattering coefficient
g0, g1 = parameters dependent on scattering characteristics of suspended particles
Absorption and Backscattering Models
)440( )];()ln()([)(
:lchlorophylby Absorption
)440( )];440(exp[)(
:detritus and CDOMby Absorption
)550( ;)/550()(
:matter eparticulatby ringBackscatte
)()()()( :tcoefficien Absorption
);()()( :tcoefficien ringBackscatte
10
aPaPaPa
aGSGa
bXXb
aaaa
bbb
gg
bpy
bp
gw
bpbwb
Sea bottom reflectance
)()()( ssvvb
vegetation
sand
Sea bottom reflectance is modeled as a linear combination of typical sand and vegetation reflectance spectra.
)659()659()659(
)825()825()825(
ssvvb
ssvvb
)659()825(
)659()825(
bb
bbNDVI
(Sea bottom NDVI, corrected for water column effects)
Example of spectral matching:Deep water
Class 3: Deep water
X = 0.25 m-1 , G = 0.096 m-1 P = 0 Water depth set to a large value H = 25 m during spectral fitting (actual value doesn’t matter)
Example of spectral matching:Reef edge
Class 6: Fringe of coral reef
X = 0.23 m-1 , G = 0.019 m-1 P = 0 Rb547 = 0.135, Rb659 = 0.154, Rb825 = 0.282, NDVI = 0.292H = 1.30 m
Example of spectral matching:Submerged reef
Class 41: shallow reef
X = 0.26 m-1 , G = 0.0 m-1 P = 0.25 m-1
Rb547 = 0.226, Rb659 = 0.267 , Rb825 = 0.365, NDVI = 0.154H = 0.31 m
Example of spectral matching:Submerged seagrass
Class 25: submerged seagrass
X = 3.21 m-1 , G = 0.0 m-1 P = 0 m-1
Rb547 = 0.024, Rb659 = 0.020, Rb825 = 0.155, NDVI = 0.776H = 0.12 m
Water Depth
0 m
0.5 m
1.0 m
> 1.5 m
Bottom Albedo (at 547 nm)
0
0.10
0.20
> 0.30
Vegetation Index (Water column corrected)
1.0
0.50
0.0
Detection of submerged aquatic vegetation
Concluding Remarks
• We illustrated the application of a spectral matching algorithm in deriving the water depth, bottom albedo, vegetation index (for submerged aquatic vegetation) and water quality parameters from 8-bands high resolution WorldView-2 satellite images.
• The satellite derived reflectance spectra can be fitted quite well to the shallow water reflectance model.
• The 6th band (“red-edge” band centered at 723 nm) always has a high deviation from the best fit value for all the classes. This band happens to coincide with a water vapour absorption band.
Concluding Remarks
• Eight spectral bands of WorldView-2 enable the application of a spectral matching algorithm, but implementation on the full image is not time-efficient.
• Computational time efficiency is improved by clustering pixels with similar spectral values, and spectral matching is performed on the average spectrum of each class.
• The water column corrected NDVI can serve to detect submerged aquatic vegetation, and to quantify the abundance.
• Integrating with classification methods is on-going.
Acknowledgment
• Singapore Agency for Science, Technology and Research (A*STAR) for funding to CRISP
• Singapore National Parks Board (Nparks) for a grant supporting the project.
• S. C. Liew acknowledges support of Singapore-Delft Water Alliance (SDWA)
WV2 Spectral Response
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