Develop proxy VIIRS Ocean Color remotesensing reflectance from MODIS

Transcription

1 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS 1) Define a VIIRS Proxy Data Stream 2) Define the required in situ data stream for Cal/Val 3) Tuning of algorithms and LUTS (Vicarious calibration and SDR feedback) 4) Ocean Algorithm, stability evaluation and uncertainty 5) Product validation and product long-term stability Presenter/Affiliation: Zhongping Lee/SU Performers: ZhongPing Lee, Ronald Vaughan Thrust area: 1, 3, 4, 5, 6 Award date: ay 2009 Total an-onths Effort: FY09 FY10 FY ) Satellite intercomparisons, robustness, seasonal and product stability

2 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS Project Objectives 1) Develop and implement the generation of VIIRS proxy ocean color data stream; 2) Evaluate/refine algorithms; 3) Ensure consistency of ocean-color products; ajor FY09 Challenges/Issues 1) Algorithms for generation of hyperspectral water-leaving radiance from multi-band ODIS measurements; 2) Software for automatic generation of data stream; 3) Integrating software with GRAVITE. Supports: Ocean cal/val plan elements 1, 3, 4, 6 1. Concept/strategy for proxy VIIRS ocean color 2. erge proxy module with GRAVITE ilestones / Deliverables FY S D S FY Evaluate proxy data S D products D FY ajor Progress 1) Developed stable algorithm to generate hyperspectral water-leaving radiance; 2) Completed v1 software development for proxy VIIRS ocean-color data stream; 3) Delivered software (v1) to IPO/GRAVITE. 4 Develop/Refine algorithms S D

3 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS Collaboration and Coordination with Inside and Outside Activities Transition Partners NASA OBPG ESA CoastalColor Program NRL Oceanography, Remote Sensing ONR Code 32 (Ackleson/Cleveland) IPO GRAVITE SDR VIIRS Cal/Val team NOAA NESDIS-Coastwatch (P. DiGiacomo) NOS (R. Stumpf) NASA SeaDAS (B. Franz) NAVOCEANO NP3- SCCT - Doug ay NP3 Satellite Optics P. Lyon NGAS Cal/val (S. Jackson, P. Patt) NRL Oceanography (R. Arnone) IPO GRAVITE (Joe Zajic) Leveraged RDT&E Projects 6.1 NRL Hyperspectral Signatures of Coastal Zone 6.2 NRL Hyperspectral/LIDAR 6.1 ONR HICO 6.1 NRL 3D Remote Sensing NASA Ocean Biology and Biogeochemistry Water Cycle and Energy NOAA Northern Gulf Institute International Partnerships ESA C. Brockmann (Germany) U. Queensland S. Phinn (Australia) Joint Research Centre G. Zibordi (Italy) Korea Ocean Research and Development Institute Y.H. Ahn (S. Korea) Plymouth arine Lab S. Groom (Britain)

4 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS FY 09- ILESTONES Completed In Progress ilestone 1: Development of concept/strategy for generation of proxy VIIRS remote-sensing reflectance ilestone 2: Expand ODIS multi-band properties to hyperspectral properties Expand atmospheric contributions to hyperspectral Expand atmospheric transmittance to hyperspectral Generate multispectral IOPs Expand multispectral IOPs to hyperspectral IOPs Generate hyperspectral water reflectance ilestone 3: Develop and deliver software module (V1) for VIIRS proxy TOA radiance Software development (V1) Generate proxy VIIRS radiance ilestone 4: Lead algorithms evaluation team for NPP ilestone 5: Coordinate with NRL on integrating proxy into APS

5 Task 1: Concept/strategy for proxy ocean-color data Top-of-atmosphere radiance: L t : Lt(λ) = LR(λ) + LA(λ) + t Lw(λ) + Lg(λ) Reflectance ec ce domain: Rt(λ) = RR(λ) + RA(λ) + t sen t sol Rw(λ) + Rg(λ) R = L/F 0 L t ODIS/AQUA Photons ODIS ultispectral Hyperspectral L t (λ) * BRF VIIRS = L T (B i ) VIIRS VIIRS Proxy Stream Hyperspectral (1nm) / Reverse APS Atmospheric Correction Atmosphere APS Atmospheric Correction Aerosol Correction Rayleigh Correction Atmosphere Water ultispectral nlw, IOPs Lw(λ) Hyperspectral ( nm, 1 nm step)

6 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS FY 09- ILESTONES Completed In Progress ilestone 1: Development of concept/strategy for generation of proxy VIIRS remote-sensing reflectance ilestone 2: Expand ODIS multi-band properties to hyperspectral properties Expand atmospheric contributions to hyperspectral Expand atmospheric transmittance to hyperspectral Generate multispectral IOPs Expand multispectral IOPs to hyperspectral IOPs Generate hyperspectral water reflectance ilestone 3: Develop and deliver software module (V1) for VIIRS proxy TOA radiance Software development (V1) Generate proxy VIIRS radiance ilestone 4: Lead algorithms evaluation team for NPP ilestone 5: Coordinate with NRL on integrating proxy into APS

7 VIIRS PROXY DATA STREA ODIS TOA L t Hyperspectral TOA L t H VIIRS TOA L t V Radiance space: t sen w r a L = t L + L + L + l Reflectance space: t sol sen w r a R = t t Rrs + R + R + R g sol t = t r t a t G Every component needs to be expanded dto hyperspectral ( nm, 1 nm resolution) before band convolution.

8 t sol sen w r a R = t t Rrs + R + R + A: Atmospheric component: R g 1. Rayleigh reflectance: R r R r ( λ ) = 1.03 R r (412 ) λ 4

9 t sol sen w r a R = t t Rrs + R + R + AAt A: Atmospheric component: R g 2. Aerosol reflectance: R a linear interpolation/extrapolation.

10 t sol sen w r a R = t t Rrs + R + R + A: Atmospheric component: R g 3. transmittance: t sen linear interpolation/extrapolation, same for t sol

11 t sol sen w r a R = t t Rrs + R + R + B: Water component (Rrs): [sr -1 ] Rrs True HS R g Wavelength [nm] Blue dots: ODIS; green line: interpolation; red line: hyperspectral Bottom line: spectral interpolation could not capture the spectral variation of Rrs.

12 B: Water component: Rrs H Rrs R rs = F( a bb + b b ) Two approaches were tested: Approach 1: Focus on hyperspectral IOPs QAA Approach 2: Focus on hyperspectral Rrs (absorption)

13 Approach 1: Inverting spectral a and b b Rrs w a( λ ) = a j w ( λ ) + j QAA 5 i= 1 β ij ( a( λ ) a ( λ )) i a(λ i ), i: 1-5; b bp (λ 0 ) and Y w i b ( λ ) = b ( λ) + b ( λ); b b bw bp λ λ ( bp λ ) = b ( 0 bp λ ) 0 Y Hyperspectral β ij has been developed. Spectral transfer coefficient ulti HS Hyperspectral a(λ)andb b (λ) R rs = F Hyperspectral Rrs H w b a + b b ( b )

14 Spectral transfer Coefficient, β i,j ulti to HS LUT Sample data of β ij (developed based on IOCCG dataset) Hyperspectral p ( nm, 1 nm step) ODIS Bands a( λ ) j = a w ( λ ) + j 5 i= 1 β ij ( a( λ ) a ( λ )) i w i Software developed, tested and integrated.

15 True Color ODIS RGB B8,B5,B2 bands ODIS Proxy TOA VIIRS RGB 5,4,2 Proxy Negative nlw412 Sample result based on Approach 1 Pro oxy Lt488 Didn t use with GRAVITE! ODIS Lt488

16 Approach 2: Focus on hyperspectral Rrs (Lw) Step 1: From ODIS Rrs, calculate parameter Z: Rrs(443) x = log Rrs(551) y = x x y z = Rrs(488) ; Rrs(667) 2 ; total absorption at 443 nm equivalent chlorophyll conc. Step2: From the above z, generate absorption coefficient of each ODIS band ( nm): a(b) a ( B) = a ( B) + K( B) z w e( B) Values of K and e are based on orel et al (2001)

17 Step 3: From the above a(b) and ODIS Rrs at each band, Rrs(B), calculate l b bp (B): b bp ( B) = R ( B) a( B)/0.05 b ( B) rs bw particle backscattering Step 4: Interpolate the above b bp (B) to hyperspectral (every 1 nm) b bp (H) Step 5: From the z of Step 1, calculate hyperspectral absorption (hyperspectral K and e values were after interpolating the orel 2001 table) a ( H ) = a ( H ) + K ( H ) z ( w e( H) HS absorption of total Step 6: From the above a(h) and b bp (H), calculate hyperspectral Rrs(H): R rs b ( H) = 0.05 bw ( H) + b a( H) bp ( H) Hyperspectral Rrs!!!

18 Approach 2: Example of output hyperspectral Rrs vs input ODIS Rrs VIIRS Bands Linear Interpolation ] Rrs [sr True HS Wavelength [nm] Proxy VIIRS water-leaving radiance is generated with Approach 2. Note that the x better represents the true spectral signature.

19 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS FY 09- ILESTONES Completed In Progress ilestone 1: Development of concept/strategy for generation of proxy VIIRS remote-sensing reflectance ilestone 2: Expand ODIS multi-band properties to hyperspectral properties Expand atmospheric contributions to hyperspectral Expand atmospheric transmittance to hyperspectral Generate multispectral IOPs Expand multispectral IOPs to hyperspectral IOPs Generate hyperspectral water reflectance ilestone 3: Develop and deliver software module (V1) for VIIRS proxy TOA radiance Software development (V1) Generate proxy VIIRS radiance ilestone 4: Lead algorithms evaluation team for NPP ilestone 5: Coordinate with NRL on integrating proxy into APS

20 Incorporating VIIRS Band Response Function: L * i t (λ) BRF VIIRS (λ)dλ =L( t i ) VIIRS 412 nm Out of band response 488 nm 555 nm 865 nm

21 Example VIIRS Proxy image Approach 2 applied, only to valid water pixels (Black: land or clouds) Top of Atmosphere True Color ODIS RGB B8,B5,B2 B5 B2 bands Top of Atmosphere Proxy TOA VIIRS RGB 5,4,2 Convolved with Spectral response of VIIRS

22 Comparison between ODIS and Proxy Lt 412 nm 488 nm A Lt IRS TOA Proxy VI 555 nm 865 nm ODIS TOA Lt

23 Proxy Rrs 555 ODIS Rrs 551 At ~550 nm, Rrs from both sensors are quite consistent!

24 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS FY 10 - ILESTONES Completed In Progress ilestone 1: Update and refine S to HS for VIIRS proxy ilestone e 2: Evaluate proxy data stream with ODIS/ERIS S data Image to image comparison (Lt, Rrs, bio-optical properties) atch-up comparison (e.g. Norfolk, Chesapeake Bay) ilestone 3: Lead the algorithms evaluation team

25 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS Status and Issues: Deliverable: Concept/strategy for proxy VIIRS ocean color 1. Dates achieved: September %. Deliverable: Algorithm for proxy hyperspectral VIIRS data 1. Dates achieved: February % 2. Steps are being taken to further refine the algorithm. Deliverable: Software module to generate proxy VIIRS ocean color data within GRAVITE 1. Version 1 module is now incorporated in GRAVITE. 90% 2. Software test/evaluation

26 Comparison between ODIS and Proxy Rrs(488) Proxy Rrs(488) > ODIS Rrs(488)! Proxy? Effect of out-of-band response? Atmosphere correction? Pro oxy VIIRS Rrs(488 8 nm) 488 nm ODIS Rrs(488 nm)

27 Comparison between ODIS and Proxy Rrs(488) Higher proxy Rrs(488) happened at open ocean

28 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS Summary: Impact of Deliverables on Program Provide critical components to test and ensure the readiness of VIIRS ocean-color data processing infrastructure Provide important data stream to evaluate the likely performance of VIIRS ocean color sensor in various environments

29 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS Schedule with ajor Deliverables Title ilestones Task #1: Develop and implement VIIRS proxy OC data algorithm Task #2: Refine algorithm for VIIRS proxy OC data and evaluate VIIRS proxy OC products Task #3: Develop and g VIIRS OC products FY08 FY09 FY10 FY11 FY12 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 S D T S C R refine algorithms for S C R S Start, C Complete, D Demo, I-Issues, - anual/documentation, R Final Report, T- Transition

30 Develop proxy VIIRS Ocean Color remotesensing reflectance from ODIS 1) Define a VIIRS Proxy Data Stream 2) Define the required in situ data stream for Cal/Val Questions? 3) Tuning of algorithms and LUTS (Vicarious calibration and SDR feedback) 4) Ocean Algorithm, stability evaluation and uncertainty 5) Product validation and product long-term stability 6) Satellite intercomparisons, robustness, seasonal and product stability

31 Extra Slides

32 Comparison between ODIS and Proxy Lt Proxy VIIRS TOA Lt (412 nm) ODIS TOA Lt (412 nm) 412 nm

33 Comparison between ODIS and Proxy Lt Proxy VIIRS TOA Lt (48 88 nm) ODIS TOA Lt (488 nm) 488 nm

34 Comparison between ODIS and Proxy Lt Proxy VIIRS TOA Lt (55 55 nm) ODIS TOA Lt (551 nm) 555 nm

35 Comparison between ODIS and Proxy Lt Proxy VIIRS TOA Lt (86 65 nm) ODIS TOA Lt (869 nm) 865 nm

36 ISSUES ODIS Rrs 488 Proxy Rrs 488