Presentation is loading. Please wait.

Presentation is loading. Please wait.

Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Sensitivity Analysis of Model-Predicted Suspended Sediment Inherent.

Similar presentations


Presentation on theme: "Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Sensitivity Analysis of Model-Predicted Suspended Sediment Inherent."— Presentation transcript:

1 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Sensitivity Analysis of Model-Predicted Suspended Sediment Inherent Optical Properties and Their Effect on Remote Sensing Water Leaving Radiance Jason Hamel Dr. Rolando Raqueño Dr. John Schott Dr. Minsu Kim March 19, 2005

2 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Outline ObjectiveObjective Water ModelingWater Modeling Suspended SolidsSuspended Solids Hydrolight Analysis Test CasesHydrolight Analysis Test Cases Some Initial resultsSome Initial results ConclusionConclusion

3 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Objective Examine the effect of suspended solids on water leaving radianceExamine the effect of suspended solids on water leaving radiance –Perform a sensitivity study using a model to determine effect of: »Composition »Particle size »Concentration –Examine errors associated with assigning inappropriate inherent optical properties (IOP’s) to an unmeasured water body Tools:Tools: –Oops –Hydrolight

4 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Signal Sources Air/Water Transition Water/Air Transition In Water Atmosphere to Sensor 10% 80% 10%

5 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Characteristics of Spectral data Irondequoit Bay Lake Ontario Genesee River

6 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Outline ObjectiveObjective Water ModelingWater Modeling Suspended SolidsSuspended Solids Hydrolight Analysis Test CasesHydrolight Analysis Test Cases Some Initial resultsSome Initial results ConclusionConclusion

7 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Water Modeling Hydrolight is our current water modeling toolHydrolight is our current water modeling tool To model the radiance leaving the water surface Hydrolight needs defined:To model the radiance leaving the water surface Hydrolight needs defined: –Illumination –Surface wind speed –Water quality parameters –Bottom conditions

8 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Water Modeling Water quality parametersWater quality parameters –Material components in the water column (typically included is pure water, chlorophyll, suspended solids, and color dissolved organic matter) »Concentration »Absorption coefficient »Scattering coefficient »Scattering phase function –All variables can be defined for wavelength and depth

9 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T New Modeling Opportunity Ocean Optical Plankton Simulator (OOPS) developed at CornellOcean Optical Plankton Simulator (OOPS) developed at Cornell Models absorption and scattering coefficients and the scattering phase functionModels absorption and scattering coefficients and the scattering phase function Generate these IOP’s of in-water constituents if basic properties of the materials are knownGenerate these IOP’s of in-water constituents if basic properties of the materials are known Can generate test data sets with Hydrolight to analyze how specific constituents effect the water leaving radianceCan generate test data sets with Hydrolight to analyze how specific constituents effect the water leaving radiance

10 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Outline ObjectiveObjective Water ModelingWater Modeling Suspended SolidsSuspended Solids Hydrolight Analysis Test CasesHydrolight Analysis Test Cases Some Initial resultsSome Initial results ConclusionConclusion

11 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Suspended Solids in Oops Basic physical and optical properties needed by Oops to model IOP’s:Basic physical and optical properties needed by Oops to model IOP’s: –Suspended solids composition –Refractive index –Density –Particle size distribution

12 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Suspended Solids Composition QuartzSiO 2QuartzSiO 2 FeldsparsFeldspars –OrthoclaseKAlSi 3 O 8 –AlbiteNaAlSi 3 O 8 –AnorthiteCaAl 2 Si 2 O 8 Clay mineralsClay minerals –KaoliniteAl 4 (OH) 8 [Si 4 O 10 ] –Chlorite(Al, Mg, Fe) 3 (OH) 2 [(Al,Si} 4 O 10 ] Mg 3 (OH) –Illite(K, H 2 O) Al 2 (H 2 O, OH) 2 [AlSi 3 O 10 ] –Montmorillonite{(AL 2-x Mg x ) (OH) 2 [Si 4 O 10 ]} -x Na x. n H 1 O Calcite/aragoniteCaCO 3Calcite/aragoniteCaCO 3 OpalSiO 2 (amorphous)OpalSiO 2 (amorphous)

13 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Refractive Indices Ordinary RayExtraordinary RayTertiary Ray Quartz1.5441.553Quartz1.5441.553 FeldsparsFeldspars –Orthoclase1.5231.5271.531 –Albite1.5271.5311.538 –Anorthite1.5771.5851.590 ClaysClays –Kaolinite1.5491.5641.565 –Chlorite1.611.621.62 –Illite1.561.591.59 –Montmorillonite1.551.571.57 Calcium CarbonateCalcium Carbonate –Calcite1.4861.658 –Aragonite1.5311.6801.686 Opal1.44Opal1.44 From Lide, D. R. (2003). CRC Handbook of Chemistry and Physics 2003-2004. CRC Press, 84th edition.

14 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Refractive Indices From Gifford, J. W. (1902). The refractive indices of fluorite, quartz, and calcite. Proceedings of the Royal Society of London, 70:329-340.

15 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Particle Size Distributions Will test 3 particle size distributions (PSD):Will test 3 particle size distributions (PSD): –Junge –Gaussian –Log-Normal

16 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Typical Ocean PSD’s From Simpson, W. R. (1982). Particulate matter in the oceans-sampling methods, concentration, size distribution, and particle dynamics. Oceanography and Marine Biology, 20:119-172.

17 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Junge PSD’s

18 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T In Situ PSD’s Measurements made using a Benthos plankton cameraMeasurements made using a Benthos plankton camera Found 80% of particulate matter in suspension as flocs larger than 100  m in sizeFound 80% of particulate matter in suspension as flocs larger than 100  m in size From Eisma, D., et al. (1991). Suspended-matter particle size in some West-European estuaries; Part I: Particle-size distribution. Netherlands Journal of Sea Research, 28(3):193-214.

19 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Gaussian PSD’s

20 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Log-Normal PSD’s

21 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Outline ObjectiveObjective Water ModelingWater Modeling Suspended SolidsSuspended Solids Hydrolight Analysis Test CasesHydrolight Analysis Test Cases Some Initial resultsSome Initial results ConclusionConclusion

22 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Hydrolight Analysis Now that some variations of suspended solids are known, Oops can generate various suspend solid IOP’sNow that some variations of suspended solids are known, Oops can generate various suspend solid IOP’s These IOP’s can operate as variables in Hydrolight to test the effect different suspended solids have on the water leaving radianceThese IOP’s can operate as variables in Hydrolight to test the effect different suspended solids have on the water leaving radiance Since the different IOP’s are of main interest, most Hydrolight inputs will be held constant between runsSince the different IOP’s are of main interest, most Hydrolight inputs will be held constant between runs

23 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Hydrolight Analysis Illumination conditionsIllumination conditions –Constant, based on illumination in the Rochester area during the summer near noon Surface conditionsSurface conditions –Constant, 5 m/s to simulate calm but not completely smooth wave conditions Bottom conditionsBottom conditions –Constant, measured reflectance of Ontario Lake sand

24 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Hydrolight Analysis Water Quality conditionsWater Quality conditions –Oops variables: »Particle types Quartz, albite, kaolinite, calcite, and opalQuartz, albite, kaolinite, calcite, and opal »Refractive index Basic ordinary ray RI for each particle typeBasic ordinary ray RI for each particle type Extraordinary ray RI for calciteExtraordinary ray RI for calcite Calcite RI measured spectrally from 350-950nmCalcite RI measured spectrally from 350-950nm

25 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Hydrolight Analysis Water Quality ConditionsWater Quality Conditions –OOPS Variables: JungeJunge –Coefficient of 2, 3, 4 and 5 –Size ranges of 0.2-125  m, 0.2-60  m, 0.2-90  m and 10-60  m GaussianGaussian –30  m mean and 1 or 8 standard deviation Log-NormalLog-Normal –Mean size of 1, 2, 3, 4, and 5  m –1 or 2 standard deviation

26 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Hydrolight Analysis Water quality conditionsWater quality conditions –Hydrolight variables »Concentrations 2.7510.004.28 Genesee River Plume 2.1410.376.51 Conesus Lake 6.1222.4462.96 Long Pond 0.570.570.76 Lake Ontario 0.010.00.0 TSS only CDOMTSSCHL Water Body

27 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Outline ObjectiveObjective Water ModelingWater Modeling Suspended SolidsSuspended Solids Hydrolight Analysis Test CasesHydrolight Analysis Test Cases Some Initial resultsSome Initial results ConclusionConclusion

28 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Different Constituents

29 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Small Particles Removed

30 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Different Concentrations

31 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Atmospheric Correction Difficulties

32 Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Conclusions OOPS and Hydrolight model the water-leaving radiance from water bodies given physical and optical properties of constituentsOOPS and Hydrolight model the water-leaving radiance from water bodies given physical and optical properties of constituents Initial results are following expectationsInitial results are following expectations –Composition has little effect in many situations –PSD’s have an effect –Concentration of CHL, TSS, and CDOM has large effect –Situations exist between 800-900nm where significant light is reflected from the water interfering with normal atmospheric correction attempts


Download ppt "Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Sensitivity Analysis of Model-Predicted Suspended Sediment Inherent."

Similar presentations


Ads by Google