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GOCI Data Processing System : Algorithm and Cal/Val  Joo-HyungRyuwith KOSC Colleaques Korea Ocean Satellite Center Korea Ocean Research & Development Institute
Maximize the GOCI application Research/Application Next GOCI  GDPS SW +Cal/Val GOCI data
GOCI coverage  ,[object Object],(Considering the geographical size, coverage area is very small) ,[object Object]
Population : large (a heavily populated district)
Economy, Commerce : big (container traffic)
Defense, Military : important
Environments : variable, changeable
Climate change : seriousRussia China (? Billion) Japan (100 million) Korea (70 million) Taiwan
Missions of GOCI GOCI Product Applications Objects Earth EnvironmentClimatic Change Ocean Environmental Monitoring Long & Short termOcean Environment Monitoring Atmosphere & Weather Land &  Disaster Prevention Disaster Monitoring Military Application Prediction & Forecast Cooperation with Others Secret Intelligence Community +
GDPS introduction GOCI DataProcessing System
Ocean Color SW  SeaDAS : SeaWiFS, MODIS  BEAM : MERIS GDPS : GOCI A standard operational system of KOSC Basic data processing system for GOCI user Well-designed data processing structure World’s first Geostationary Ocean Color Data Processing SW
A brief overview of GOCI ,[object Object]
COMS : Communication Ocean and Meteorological Satellite
It shall be operated in a staring-frame capture mode onboard its COMS.
The mission concept includes eight visible-to-near-infrared bands, 500 m spatial resolution, and a coverage region of 2,500*2,500 km centered at Korea.
The instrument is expected to provide SeaWiFS quality observations for a single study area with imager frequency of 1 hour from 9 am to 4 pm (8 times a day).
GOCI Application : LEO mission + Operational mission    harmful algae bloom (HAB), health of marine ecosystem, movement of suspended sediment and current, and to produce marine fisheries information for fishing communities+ ocean forecasting (with modeling)
GEOvs. LEO GEO is about 50 times farther from the Earth than LEO GEO spatial resolution is 4 times better than that of LEO GEO temporal resolution is 8 times better To be considered and prepared sensor type, geometry & local coverage for overcoming GEO characteristics
Korean Seas : Case-I & II water ,[object Object]
The coastal area of Korea & China and the ECS(seasonalvariation) is a typical Case-2 waters
East/Japan Sea, central YS & Pacific come under the Case-1 waterDefinition of Case-1 and 2 waters  using in situ <chl> and <SS> data of the Korean Sea
Issue 1 : Geometry variation and Local coverage ,[object Object]
IOP and AOPIn situ measurement were performed during a lot of cruises in the Korean terrestorial seas and neighboring waters through the years 1998-2010 onboard the KORDI research vessel and fisher boats.
Ferrybox Incheon ,[object Object]
Operation time: 19:00-10:00(next day)
Instruments: YSI(SS, chl, T, S, DO), ChelSea(chl), SeaPoint(chl), McVan(SS)
Water sample: about 40(every 20 min after departure) <SS>, <chl>, adomJeju For understanding the ocean environmental parameter of the YS,  we conducted the ferrybox project during 4 years.
Concentration of SS, <chl>, aDOM in the YS SS :       0-186 g/m3 <chl> :  0 – 16 mg/m3 adom :  0-0.9   m-1
GDPS algorithm
GOCI Data Processing System flow Accessory  Data file Sub-routine Low level Data file Analyzed  data file Option KOSC IMPS LEVEL-0 Sector Image Radiometric Calibration Calibration Coefficients LEVEL-1A Digital values Land  Mask Geometrical Correction & Mosaic Image Display ASCII-Data Generation Cloud Mask LEVEL-1B Total Radiance Turbid water Mask Atmospheric Correction New & old model GDPS WaterleavingRadiance Bi- Directional Correction Lookup Table ReferenceTarget SPData LwN (B1-B8) CASE-I&II   & Fluor.  Algorithm 1-Band Algorithm Absorption Coefficient Fishing Ground Index Empirical Algorithm Image pattern Comparison 3-Bands Algorithm Red-tide Index K & Inherent Optical  algorithm Red-Tide Fishing  Ground Information CDOM TSS Under water Visibility Water Current Vector Atm. & Earth Environment Chlorophyll Optical  Properties Water New model Yellow Dust Forest Fire Inland flood Vegetation Index Heavy snowfall K-coefficient Absorption coeff. Backscattering Coeff NOAA Image Water Quality Level 1-5 Primary Productivity
GOCI L2 Product
GDPS GUI Setting Process Schedule Band-math GOCI L2 Display
(operational) GDPS Requirement Algorithm Programming Developed atmosphere/bio-optical algorithms are integrated in the software and working in real time. Timeliness  less than 30 minutes from L1B to L2 generation  Automation All data processing function can work automatically Pre-configured operating support OS PC Windows Output Format HDF-EOS 5 format Development Tool Microsoft Visual C++ <GDPS System> GDPS - R1A Duplicationl GDPS - R1B GDPS – R2 GDPS - UI Processing Server SPEC:3.0GHz4core 2cpu, 4GB ram
Product (Level) Level 1B Radiometric & geometric corrected Total Radiance Level 2 Environmental properties derived from Ocean signal(Lw) For GOCI, L2 data will be generated each hour.(8 times/day)		 Level 3 Secondary derived data from L2 like Fishery Ground information, Primary Production. Cloud-free(reduced) ocean environmental data  by daily composite of L2
GDPS result  L2 reflectance RGB-642 composite image (background: L1b band6) Suspended Sediment Concentration    (background: L1b band6) Level1b
GDPS products Lw Band 2 Band 1 Band 3 Band 4 Band 5 Band 6 Band 7 Band 8
GDPS products CDOM SS CHL Kd NDVI Absorption Coeff.
GDPS Cal/Val plan  ,[object Object]
Research vessel, Ferrybox(with KORDI), Glider(with KORDI)
Buoy, Ocean research station :
To use Korea Operational Oceanography Network(with KORDI)
To cooperate neighboring countries (with Japan, China, Taiwan)
To join International Group (with IOCCG, OCR-VS, Aeronet-OC, ESA CoastColor)
Inter-satellite Cal.
Existing OC : MODIS, MERIS
HICO (with D. Curtiss)
 New system
Kite, aerostat, airborne (with KARI)
Argo-type buoy
Uniform land Cal/Val site
Desert, Ice, Playa,[object Object]
Lessons from MERIS and MODIS Cal/Val From temporal discontinuity measurement (by ship)  To continuous measurement (by buoy and tower) : Aeronet-OC Tower measurement: 200pts/6.5years Ship measurement : 10pts/2.5years
Guideline of KOSC Cal/Val To operate optic lab for radiometer(instrument) validation : under construction To establish a serise of Cal/Val system To apply previous KORDI fixed system including buoy, tower, ferry To cooperate international Cal/Val group and neighboring country
Yellow Sea Buoy (2007) Korea Operational  Oceanography Network Dokdo Buoy  (2009) Gageocho Station  (2009) East(Japan) Sea Station (2012) Ieodo Station (2003) Two buoys and two ocean stations have already been constructed by KOON project
Korea Operational Oceanography Network These systems are not for remote sensing only
Ieodo Ocean Research Station ,[object Object]
Environment Observing Systems (6)
Ocean Monitoring Systems (22)
Spectroradiometer
Wave radar
Directional Waverider
Self Contained Ultrasonic Sensors

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20110728_IGARSS_GDPS(ryu)fin1.pptx

  • 1. GOCI Data Processing System : Algorithm and Cal/Val Joo-HyungRyuwith KOSC Colleaques Korea Ocean Satellite Center Korea Ocean Research & Development Institute
  • 2. Maximize the GOCI application Research/Application Next GOCI GDPS SW +Cal/Val GOCI data
  • 3.
  • 4. Population : large (a heavily populated district)
  • 5. Economy, Commerce : big (container traffic)
  • 8. Climate change : seriousRussia China (? Billion) Japan (100 million) Korea (70 million) Taiwan
  • 9. Missions of GOCI GOCI Product Applications Objects Earth EnvironmentClimatic Change Ocean Environmental Monitoring Long & Short termOcean Environment Monitoring Atmosphere & Weather Land & Disaster Prevention Disaster Monitoring Military Application Prediction & Forecast Cooperation with Others Secret Intelligence Community +
  • 10. GDPS introduction GOCI DataProcessing System
  • 11. Ocean Color SW SeaDAS : SeaWiFS, MODIS BEAM : MERIS GDPS : GOCI A standard operational system of KOSC Basic data processing system for GOCI user Well-designed data processing structure World’s first Geostationary Ocean Color Data Processing SW
  • 12.
  • 13. COMS : Communication Ocean and Meteorological Satellite
  • 14. It shall be operated in a staring-frame capture mode onboard its COMS.
  • 15. The mission concept includes eight visible-to-near-infrared bands, 500 m spatial resolution, and a coverage region of 2,500*2,500 km centered at Korea.
  • 16. The instrument is expected to provide SeaWiFS quality observations for a single study area with imager frequency of 1 hour from 9 am to 4 pm (8 times a day).
  • 17. GOCI Application : LEO mission + Operational mission harmful algae bloom (HAB), health of marine ecosystem, movement of suspended sediment and current, and to produce marine fisheries information for fishing communities+ ocean forecasting (with modeling)
  • 18. GEOvs. LEO GEO is about 50 times farther from the Earth than LEO GEO spatial resolution is 4 times better than that of LEO GEO temporal resolution is 8 times better To be considered and prepared sensor type, geometry & local coverage for overcoming GEO characteristics
  • 19.
  • 20. The coastal area of Korea & China and the ECS(seasonalvariation) is a typical Case-2 waters
  • 21. East/Japan Sea, central YS & Pacific come under the Case-1 waterDefinition of Case-1 and 2 waters using in situ <chl> and <SS> data of the Korean Sea
  • 22.
  • 23. IOP and AOPIn situ measurement were performed during a lot of cruises in the Korean terrestorial seas and neighboring waters through the years 1998-2010 onboard the KORDI research vessel and fisher boats.
  • 24.
  • 26. Instruments: YSI(SS, chl, T, S, DO), ChelSea(chl), SeaPoint(chl), McVan(SS)
  • 27. Water sample: about 40(every 20 min after departure) <SS>, <chl>, adomJeju For understanding the ocean environmental parameter of the YS, we conducted the ferrybox project during 4 years.
  • 28. Concentration of SS, <chl>, aDOM in the YS SS : 0-186 g/m3 <chl> : 0 – 16 mg/m3 adom : 0-0.9 m-1
  • 30. GOCI Data Processing System flow Accessory Data file Sub-routine Low level Data file Analyzed data file Option KOSC IMPS LEVEL-0 Sector Image Radiometric Calibration Calibration Coefficients LEVEL-1A Digital values Land Mask Geometrical Correction & Mosaic Image Display ASCII-Data Generation Cloud Mask LEVEL-1B Total Radiance Turbid water Mask Atmospheric Correction New & old model GDPS WaterleavingRadiance Bi- Directional Correction Lookup Table ReferenceTarget SPData LwN (B1-B8) CASE-I&II & Fluor. Algorithm 1-Band Algorithm Absorption Coefficient Fishing Ground Index Empirical Algorithm Image pattern Comparison 3-Bands Algorithm Red-tide Index K & Inherent Optical algorithm Red-Tide Fishing Ground Information CDOM TSS Under water Visibility Water Current Vector Atm. & Earth Environment Chlorophyll Optical Properties Water New model Yellow Dust Forest Fire Inland flood Vegetation Index Heavy snowfall K-coefficient Absorption coeff. Backscattering Coeff NOAA Image Water Quality Level 1-5 Primary Productivity
  • 32. GDPS GUI Setting Process Schedule Band-math GOCI L2 Display
  • 33. (operational) GDPS Requirement Algorithm Programming Developed atmosphere/bio-optical algorithms are integrated in the software and working in real time. Timeliness less than 30 minutes from L1B to L2 generation Automation All data processing function can work automatically Pre-configured operating support OS PC Windows Output Format HDF-EOS 5 format Development Tool Microsoft Visual C++ <GDPS System> GDPS - R1A Duplicationl GDPS - R1B GDPS – R2 GDPS - UI Processing Server SPEC:3.0GHz4core 2cpu, 4GB ram
  • 34. Product (Level) Level 1B Radiometric & geometric corrected Total Radiance Level 2 Environmental properties derived from Ocean signal(Lw) For GOCI, L2 data will be generated each hour.(8 times/day) Level 3 Secondary derived data from L2 like Fishery Ground information, Primary Production. Cloud-free(reduced) ocean environmental data by daily composite of L2
  • 35. GDPS result L2 reflectance RGB-642 composite image (background: L1b band6) Suspended Sediment Concentration (background: L1b band6) Level1b
  • 36. GDPS products Lw Band 2 Band 1 Band 3 Band 4 Band 5 Band 6 Band 7 Band 8
  • 37. GDPS products CDOM SS CHL Kd NDVI Absorption Coeff.
  • 38.
  • 39. Research vessel, Ferrybox(with KORDI), Glider(with KORDI)
  • 40. Buoy, Ocean research station :
  • 41. To use Korea Operational Oceanography Network(with KORDI)
  • 42. To cooperate neighboring countries (with Japan, China, Taiwan)
  • 43. To join International Group (with IOCCG, OCR-VS, Aeronet-OC, ESA CoastColor)
  • 45. Existing OC : MODIS, MERIS
  • 46. HICO (with D. Curtiss)
  • 51.
  • 52. Lessons from MERIS and MODIS Cal/Val From temporal discontinuity measurement (by ship) To continuous measurement (by buoy and tower) : Aeronet-OC Tower measurement: 200pts/6.5years Ship measurement : 10pts/2.5years
  • 53. Guideline of KOSC Cal/Val To operate optic lab for radiometer(instrument) validation : under construction To establish a serise of Cal/Val system To apply previous KORDI fixed system including buoy, tower, ferry To cooperate international Cal/Val group and neighboring country
  • 54. Yellow Sea Buoy (2007) Korea Operational Oceanography Network Dokdo Buoy (2009) Gageocho Station (2009) East(Japan) Sea Station (2012) Ieodo Station (2003) Two buoys and two ocean stations have already been constructed by KOON project
  • 55. Korea Operational Oceanography Network These systems are not for remote sensing only
  • 56.
  • 65. ADCP
  • 66. CTD
  • 67. CTR7
  • 72. etc.Ieodo station is managed by NORI (Government offfice) KORDI : design, construction, installation, test NORI : operational work
  • 73. Satlantic HyperSAS OCR-3000 Comparison between HyperSAS and SeaWiFS water-leaving radiance in each band All visible bands were well correlated with SeaWiFS excepted at longer wavelengths Lsky(λ) LwT(λ) Ed(λ)
  • 74.
  • 75. EU JRChas the scientific responsibility of the processing algorithms and performs the quality assurance of data products.
  • 76. PIs are responsible for establishing and maintaining AERONET-OC sites.30
  • 77.
  • 80.
  • 81. In-Situ TriOS Rrs(λ) : Gageocho Platform 10:35 11:35, cloudy Aug. 20 2010 - TriOS Rrs(λ) - GOCI Rrs(λ) - TriOS Rrs(λ) - GOCI Rrs(λ) 12:35 13:35 14:35 - TriOS Rrs(λ) - GOCI Rrs(λ) - TriOS Rrs(λ) - GOCI Rrs(λ) - TriOS Rrs(λ) - GOCI Rrs(λ) - MODIS Rrs(λ) 1. Cross Comparisons with time-series : in-situ TriOS, GOCI, MODIS Rrs(λ) 2. Rrs of shorter wavebands is still problem in early morning and late afternoon - Optical Path is different with time - During In-Orbit Test (IOT), this problem is our homework
  • 82. Comparison between In-Situ TriOS Rrs(λ) and GOCI Rrs(λ) : Gageocho Platform Rrs(412) Rrs(443) Rrs(490) Rrs(555) Rrs(660) Rrs(680) Rrs(745) Rrs(865)
  • 83. Statistics GOCI and in-situ matching data(Gageocho station) Xi : ith satellite-derived value Yi : ith in-situ-derived value N : number of points RMSE : root mean square error AR : average ratio of satellite to in-situ data RPD : average relative percent difference (%) APD : average absolute percent difference (%)
  • 84. Statistics of GOCI and in-situ matching data(Gageocho station) Rrs(l) Rrs(l) All bandsRMSE=0.436 All bandsRMSE=0.436
  • 85. Comparison of Chl. algorithms
  • 86. <chl> comparison of each algorithm GOCI OC4v4 OC2v2 - Local algorithms are well matched with in situ measurements - <chl> of local algorithm decreases about 50 % than that of NASA standard alg.
  • 87. Inter-satellite Cal : GOCI vs. HICO (by D. Curtiss) HICO Data Google Earth HICO ImagePusan, South Korea: Nov.18, 2009 North
  • 88. Inter-satellite Cal : GOCI vs. MERIS GOCI(2010 09 24 01: 16:43) (R(680), G(555), B(412)) MERIS(2010 09 24 01: 43:51) (R(681.55), G(560), B(412.5)) *GOCI image is geo-corrected by MERIS Geometric information
  • 91.
  • 92. No international OC Cal/Val site in GOCI coverage
  • 93. Indirect method : Inter-satellite Cal using MERIS,MODIS, NPP, HICO
  • 94. Existing Ocean Research stations need to be stabilize for GOCI Cal/Val
  • 96. Supporting of International groups (instrument Cal/Val)
  • 97. AERONET-OC site selection : Gageocho Station (with TriOS)
  • 100. “Once started, termination is irreversible”
  • 101. No land Cal/Val site in GOCI coverage
  • 102. No desert, ice, playa : uniform, wide, long term-radiometric stability
  • 103.
  • 104. Green algae bloom in ECS and YS
  • 105.
  • 106. Applied algorithm BRDF correction : GOCI algorithm & relative algorithm Atmospheric correction : coastal standard correction & SSMM Empirical SS algorithm developed based upon the in-situ data sets obtained on the Yellow Sea 2005 – 2010
  • 107. Hourly SS variations 10:16 11:16 12:16 Flood tide High tide Flood tide 0 10 SS (g/m3) 13:16 14:16 Ebb tide Ebb tide There is no notable difference over the study area from 10:30 to 12:30. However, white box area is gradually decreased time after time until high tide and then suddenly decreased.
  • 108. SSC profiles N W E S SSC profile showed a lot of fluctuations in the image at 10:30 near the coastal area, which came to be stable as time passed along both the lines.
  • 109. 2008 Green algae : EnteromorphaProliphera Total removal quantity in Qingdao : about 1 million ton Sea During 2008 Beijing Olympic Game, sailing stadium of Qingdao was attacked by green algae.
  • 110. 2008 Green algae monitoring Background image : May 20, 2008 MODIS aqua band1 image
  • 111. Korea Qingdao 6월 13일 Yellow Sea 군산 흑산도 목포 China 제주도 East China Sea 양쯔강 하구 GOCI June 13, 2011(13:15)
  • 112. Korea Qingdao Yellow Sea 7월 18일 한국 남서해상 및 동중국해녹조 탐지 (천리안 해양관측위성 분석영상, 14시16분 촬영 ) 군산 흑산도 목포 China 제주도 East China Sea 양쯔강 하구 GOCI July 18, 2011(14:15)
  • 113. 한국 Korea Qingdao Yellow Sea 군산 7월 19일 한국 남서해상 및 동중국해녹조 탐지 (천리안 해양관측위성 분석영상, 16시16분 촬영 ) 흑산도 목포 China 제주도 East China Sea 양쯔강 하구 GOCI July 19, 2011(16:15)
  • 114. 2011 Green algae (July 19-20)
  • 115. A 7월 10일 흑산도 인근 해역, 한국해양연구원 온누리호 촬영 (b) 7월 16일 동중국해(31N, 125E) 한국해양연구원과 일본 나가사키 대학 합동 조사에서 촬영 A (c) 7월 21일 흑산도 인근 해역(34N°31.9, 125E°27.8) 전남대학교 김광용 교수 연구팀 서해어업관리단 무궁화 2호에서 촬영 B B
  • 116. BohaiBay Oil Spill(by Chosunilbo) The sea area polluted in an oil spill in China's Bohai Bay was five times as large as Beijing previously announced. A probe conducted by the Chinese State Oceanic Administration found that some 4,240 sq.km of water, or seven times the size of Seoul, were polluted by oil leaks from the Peng Lai 19-3 oilfield in Bohai Bay, the daily Xin Jing Bao reported Wednesday.Beijing admitted the oil spill for the first time on July 5, a month after two oil leaks occurred at China's largest marine oilfield on June 4 and 17, saying only 840 sq.km were polluted. But the water quality of a 3,400 sq.km area nearby dropped from Grade 1 to Grade 3.China National Offshore Oil Corp. and ConocoPhillips, the joint operators of the oilfield, said the oil spill was quickly contained and cleaned up, but earlier this week Beijing admitted that oil continues to leak out.The Chinese government on Wednesday ordered the operators to suspend production until there is no more danger of further spills. Concern is increasing about the safety of seafood from the West Sea. The city of Yantai in Shandong Province near the ill-fated oilfield has set up an observation post on the coast to check for pollution.
  • 117. Oil Spill (GOCI June 13, 2011) Spilled point Bohai 다롄 Spilled point 펑라이
  • 118. GOCI and Model comparison 5 days 3 days 7 days 9 days
  • 119. GOCI discussion Enhanced temporal resolution, high performance of MTF and SNR of GOCI show better effectiveness than we expected. GOCI has an excellent capability to monitor ocean environment and disaster.
  • 120.
  • 121. Comparison of GOCI-I andGOCI-II Special Resolution(m) Obser-vation Frequen-cy Channels (Bands) Bits [Local and Global Area] [Comparison of Resolution among Ocean Sensors]
  • 122. Future Prospect Global observation in a day! OCAPI/ESA GOCI-II /KORDI GEO-CAPE/NASA