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A Remote Sensing Study of Coral Reefs; Kailua Bay, Oahu. Ebitari Isoun, Charles Fletcher, Neil Frazer, Jonathan Gradie, Scott Rowland
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Acknowledgements For shared data and field work: John Rooney, Jodi Harney, Eric Grossman, Melanie Coyne and Zoe Norcross Members of the Coastal Geology Team for moral support: Tara Miller, Dolan Eversole, Clark Sherman, Scott Calhoun, Matt Barbee, Mary Engels, Rob Mullane, Rikki Grober- Dunsmore, Chris Conger, Ole Kaven For spectral band selection and use of field targets: Eric Hochberg and Marlin Atkinson
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Acknowledgements (continued) The people at TerraSystems Inc. for friendly assistance: Pamela Elwin, Kevin Jim, and Elbert Hwang For funding and workspace: NASA, USGS- Coastal Geology Program, Sea Grant, Department of Geology and Geophysics, and SOEST For unconditional love: My Family For mystery and blessings: God
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Topical Overview n High-resolution multi-spectral imagery n Map bathymetry and percent living coral N Kailua Bay, Oahu
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Topical Overview (continued) n Passive remote sensing n Radiative transfer model Atmosphere, ocean surface, water, and ocean substrate n “Differencing” of two spectral bands
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Topical Overview (continued) n Error Assessment Depth: hydrographic survey Percent living coral: diver-obtained ground truth
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Topical Overview (continued) n Correlation of predictions to environmental and human factors n Geographic Information System (GIS) space Better reef management e.g. Maragos and Grober-Dunsmore, 1998 Basemaps for scientific studies e.g. Harney et al., 1999
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n Introduction Study Site Data Collection n Methods Data Processing Radiative Transfer Theory Depth and Bottom-type by Band Difference Applying the Model n Results Depth Predictions Percent Living Coral Predictions n ConclusionOutline
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Study Site Oahu Kailua Bay 0 10 km 21.5˚ 158˚ 21˚ 158˚ Hawaiian Islands Oahu N 0 100 km
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63 05 00 m E. 1015202530 63 35 00 m E. 236 95 00 m N. 90 85 80 75 236 95 00 m N. 90 85 80 75 236 70 00 m N. 63 05 00 m E. 1015202530 63 35 00 m E. 236 70 00 m N. sand channel spur and groove Sand fields karst caves and caverns Submerged beach rock plains Reef front Kailua Reef N
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Data collection n January 10, 1998 –Light winds –No rain –Minimal ocean swell –9:30 to 10:30 a.m. –20 to 30 m horizontal visibility in water –Ocean floor visible to 30 m
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Data collection (continued) n Low flying (1400 m) airplane –ThunderChicken
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Data collection (continued) n Application Specific Multi-Spectral Camera System (TerraSystems, Inc.) 8-bit precision
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Data collection (continued) n Multi-spectral images collected along a north-west to south-east transect n 60% overlap along flight path n 20% overlap across flight path N Oahu Kailua 335˚ 1 m 2 m
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Data collection (continued) An image from the 6th flight path1 pixel = 1 m 578 m 740 m 488 nm 551 nm 557 nm 10 nm full width half maximun Hochberg and Atkinson, 2000
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Outline n Introduction Study Site Data Collection n Methods Data Processing Radiative Transfer Theory Depth and Bottom-type by Band Difference Applying the Model n Results Depth Predictions Percent Living Coral Predictions n Conclusion
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Data processing n PCI Geomatics TM 1 1 2 3 2 3 1:5000 aerial photographs Coyne et al., 1998 RMS = 0.5 m N Oahu Kailua
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Radiative Transfer Theory n Irradiance: time rate of change of sunlight energy with area (W m -2 nm -1 ) n Radiance: flux per projected area per unit solid angle (W m -2 nm -1 sr -1 )
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irradiance reflectance upwelling irradiance downwelling irradiance Remote Sensing Reflectance, Mobley, 1994
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reflectance beneath the water surface wavelength reflectance of infinitely deep ocean bottom albedo (R just above the ocean bottom) water attenuation distribution function for the underwater light field depth Philpot, 1989
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Two-Flow Model Gordon, 1989 Gregg and Carder, 1991 Elterman, 1968 Burt, 1954 Mobley, 1994
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can be written in a simple equation in terms of Radiance : If where L b is the radiance of the ocean substrate L w is the radiance of the ocean is the water attenuation coefficient D is the water distribution function z is depth L d = L b exp - Dz + L w
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From the simplified equation: A derivative band, X i, can be defined: (1) solve for the water attenuation coefficient, (2) solve for depth and bottom-type L d = L b exp - Dz + L w X i ln((L d -L w ) = lnL b - Dz
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Solve for water attenuation coefficient, -10 m -20 m-30 m X 488 X 551 X 557 -10 m -20 m-30 m -10 m -20 m-30 m Depth*D 600 200 y = 0.05 x + 8.00 y = 0.07 x + 8.84 y = 0.07 x + 8.78 X i ln((L d -L w ) = lnL b - Dz Y-axisX-axis slope intercept Sand Maritorena, 1996 In agreement with Maritorena, 1996
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Solve for depth (z) and bottom-type (Y) from the “difference” in two bands (i,j) Assumptions: (1) Homogeneous water quality (2) Bottom reflectance is the same in two bands (Frazer) where g = D X = derivative band
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How do we apply the model to multi-spectral data? 1 2 3 4 5 6 7 8 9 10 8-bit 32-bit 488 nm 551 nm 557 nm ca cw t( cw ca ) sa sw T sun D eb06aj.pix
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Mosaic_model.pix 1, 2, 3 4 5 6 7 8 9 10 8-bit 32-bit 488 nm, 551 nm, 557 nm D ca cw t( cw ca ) sa sw T sun
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A eb06aj.pix B eb07aj.pix Relative Difference in Overlap Before After 488 nm 7% 0.9% 551 nm 4% 0.7%
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n Introduction Study Site Data Collection n Methods Data Processing Radiative Transfer Theory Depth and Bottom-type by Band Difference Applying the Model n Results Depth Predictions Percent Living Coral Predictions n ConclusionOutline
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157˚44’00”W157˚42’50”W 157˚43’30”W 157˚44’00”W157˚42’50”W 157˚43’30”W 157˚44’00”W157˚42’50”W157˚43’30”W 21˚25’20”N 21˚24’55”N 21˚25’20”N 21˚24’55”N 21˚25’20”N 21˚24’55”N 21˚25’20”N 21˚24’55”N -3 m-6 m-9 m-12 m-15 m-18 m-21 m-24 m Predicted Depth (z 488/551 ) Hydrographic Survey Depth (USGS data, E. Grossman)
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Percent Error 157˚44’00”W157˚42’50”W 157˚43’30”W 157˚44’00”W157˚42’50”W 157˚43’30”W 21˚25’20”N 21˚24’55”N 21˚25’20”N 21˚24’55”N 0-5% 6-10% 11-15% 16-20% 21-25% 26-30% 31-35% >35% Median = 11%Mean = 14%Std. Dev. = 11 Percent error to depth R = 0.21 Boundaries sand channel Difference in water quality Bottom-type assumption
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Percent Living Coral Zones (Harney, 2000) hardgrounds sand Living Coral <15% 15-25% 25-40% 40-75% >75% 0.73 0.85 1.0 0.76 0.58 0.62 0.74 0.44 0.54 0 0 0 0 0 0 0 0.67 0.74 0.42 0.16 0.3 0.16 0.53 0.73 0.42 0.2 0.65 0.38 0.12 0.47 0.07 0.030.57 0.12 0.49 0.71 0.82 0.4 157˚44’00”W157˚42’45”W30”15” 157˚44’00”W157˚42’45”W30”15” 21˚25’30” 21˚25’00” 21˚25’30” 21˚25’00” line-intercept transect percent living coral value
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hardgrounds sand Living Coral <15% 15-25% 25-40% 40-75% >75% 0.73 0.85 1.0 0.76 0.58 0.62 0.74 0.44 0.54 0 0 0 0 0 0 0 0.67 0.74 0.42 0.16 0.3 0.16 0.53 0.73 0.42 0.2 0.65 0.38 0.12 0.47 0.07 0.030.57 0.12 0.49 0.71 0.82 0.4 157˚44’00”W157˚42’45”W30”15” 157˚44’00”W157˚42’45”W30”15” 21˚25’30” 21˚25’00” 21˚25’30” 21˚25’00” Multi-Spectral Percent Living Coral (Y 488/551 ) Map 0.10
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Accuracy Assessment of Multi-Spectral Percent Living Coral Map R = 0.73, producers accuracy to # reference points Re-sampling loss of detail in 40-75%
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38% 2% 12% 3% 15% 7% 25% sand 1,500,000 m 2 hardgrounds 70,000 m 2 <15% living coral 500,000 m 2 15-25% living coral 70,000 m 2 25-40% living coral 600,000 m 2 40-75% living coral 300,000 m 2 >75% living coral 1000,000 m 2 Substrate Diversity
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Outline n Introduction Study Site Data Collection n Methods Data Processing Radiative Transfer Theory Depth and Bottom-type by Band Difference Applying the Model n Results Depth Predictions Percent Living Coral Predictions n Conclusion
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Conclusion n Radiative transfer model can be used to normalize several multi-spectral images n Bathymetry and percent living coral is predicted with 488 nm and 551 nm n It may be possible to map change through time
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Tuesday,June 12, 2001
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