Satellite-based Red-Tide Detection/Monitoring

Transcription

1 Satellite-based Detection/Monitoring Contents 1. Introduction - and Its Monitoring System 2. Detection Using Ocean Color Remote Sensing 3. Satellite-Based Monitoring in the Asian Coastal Seas Hiroshi KAWAMURA Graduate School of Science Tohoku University Increasing Red Tide Phenomena in Asian Waters Chinese Water Korean Water (After J.Z. Zou) (After Suh, 2003) - Its ccurrence in the wide Asian waters Needs of broad coverage - : a short-term variations of phytoplankton Needs of high-temporal/spatial resolutions -Its influences crossing country borders Needs of international collaboration for monitoring Functions of New Asian Red-Tice Monitoring System The Monitoring of Marine Environment and HABs KORE A Oceanographic observation 300 points (since 1921) Environmental observation 400 points (since 1972) HABs observation ( ) 160 points (since 1967) Courtesy of Professor KIM HakGyoon 1

2 Eutrophic level by COD (2002) Courtesy of Professor KIM HakGyoon Summary 1. Ocean color remote sensing technique has proven to be useful tool detecting algal bloom. Summary 5. Cooperation between biologists, satellite experts, oceanographers, and meteorologists is essential. Mutual communication and understanding among the disciplines is necessary. Organizer Participants of this Workshop 2. Detection Using Ocean Color Remote Sensing Red Tide in Ariake Bay in Winter Nori (red algae) Culture 40% ($200M!) Loss Courtesy of Professor Ishizaka 2

3 Red Tide of Ariake Bay Reclamation Area Courtesy of Professor Ishizaka SeaWiFS ( ) Courtesy of Professor Ishizaka Red-tide off Vietnam Tang et. al. (2004) SeaWiFS Chl-a images 3

4 GLI 250m Observations 250mRGB Composite 250m Chl-a 1km Chl-a GLI Detection of the Phenomena SeaWiFS Detection GLI Chl-a GLI captures the phenomena!! GLI 250m RGB Red tide detection Algorithms Basic Red tide Index (RI) Equation [ Lw (510) / Lw(555) Lw(443)] RI = [ L (510) / L (555) + L (443)] w RI = 10 w Derived Red tide Index (RI) Equation < Chl > ( mgm w 3 2 ( X X X ) Red tide Chlorophyll Algorithm 3 (0.61 RI( Derived ) ) ) = 0.316e Red tide Index Reference: Ahn, Y.H., and Shanmugam, P, Detecting red tides from satellite ocean color 0.8 observations in optically complex Northeast-Asia 0.6 coastal waters. Remote 0.4 Sensing of Environment, 103, Lw (443) (Ahn and Shanmugam, 2006), Applications: Red tide detection/forecasting Discrimination of red tide from other turbid materials Coastal monitoring program Coastal management 4

5 Red tide Index (RI) in Chinese Coastal waters Traditional In Situ Obs.+ Aircraft (Case of the Seto Inland Sea) Red-tide detection Ocean Color Remote Sensing Research - Marine biology - Environmental research - Bio-Physical interaction - Bio-Geochemical interaction Operation - Continuous monitoring - Warning - Spices identification (Water sampling and lab. Process) - Mitigation Red-tide related marine environmental information Contributions from Remote Sensing High-resolution satellite images Chl-a, SS, CDOM, nlw, SST, Solar Radiation, Surface winds, Surface currents etc. Red-tide Data Seto Island Sea Study Area Osaka Bay Harima Nada In situ Red-tide data: / occurrence information ( ) (Fisheries Observatory of Osaka Prefecture) - criteria (Joe, 1971) 1) Water Color GY-Y (Munsell Color Coding) 2) Phytoplankton cell number >3-5x10 3 cells 3) Chl-a concentration > 10mg/m 3 4) Water transparency < 3.0m 5

6 Regular Airplane observation for Monitor by Japanese Fisheries Agency ( ) Example of Airplane Observation (2001/6/26) Discolored Area Airplane View of Osaka Bay, 27 July is Discoloration of surface water associated with biological phenomena - Eye detection from ship and airplane is a proven method of monitoring Rational of nlw usage for the detection Considerations(1) 1) changes water color in a short time 2) The discolored area () has color different from its surrounding areas and forms water-color front 3) Background water color (BWC) of the discolored area is color before/after the and color of its surrounding areas Background Water Color Discolored Area 6

7 Considerations(2) 4) BWC has a time scale longer than that of the phenomena and BWC is a function of time and location > BWC can be defined as a long-term mean of nlws for the location 5) The discolored area () can be detected as nlws anomalies from the mean nlws (BWC) Working hypothesis Ocean biology Water Color Change of WC WC Valiability Satellite Observation Background Water Color Discolored area Background Water Color (BWC) BWC depends on sea region and season. But, its temporal scale is longer than that of. We define BWC as monthly means of ocean color spectra for each pixel (0.01 degree grided) SeaWiFS nlw(λ)(λ= ) for were used for BWC estimation WC spectra of and non (1) Match-up data using SeaWiFS nlws and Red- Tide information in Osaka bay (Sample N. = 109 including 16 points) non RT non RT BWC BWC BWC 1. Spectral peak of is at 555nm 2. nlw of nm is lower than that of BWC 7

8 WC spectra of and non (2) non RT nm gradient non RT nm gradient 3. spectral gradient for nm is larger than that of nm Criteria of detection 1.Spectral peak of is at 555nm 2. nlw of nm is lower than that of BWC 3. spectral gradient for nm is larger than that of nm Validation in Osaka Bay Right Wrong (16) 13 (81%) 3 Non (93) 88 (95%) 5 Total(109) 101 (92%) 8 Example of detection in Harima Nada Air-plane observation (2002/7/23) and satellitebased detection Chattonella antiqua, Chattonella marina (2002/7/17-29) 8

9 3. Satellite-Based Monitoring in the Asian Coastal Seas Detection of phenomena in Asian Waters Application of the developed methodology to the Eastern Asian Waters - Using SeaWiFS Lac data received at the Hong Kong U. Science&Technology - For the period of , 0.01-degree grided images of nlw are processed - Monthly mean nlws are calculated - s are detected through the detection criteria and SS mask (>10mg/l) by Ahn(2002) Red-tides 23 July 2 August, 2001) Occurrence Frequency ( ) 9

10 Summary Case-I, A part of Case II (e.g., Osaka bay) waters: Water color changes are well detected Coastal Case II waters: Not well detected, SS makes significant noise against the present method Background Water Color (Type I) Background Water Color (Type-II) Remote sensing strategy Discolored Area - Intensive research for Background water color Type-II - Interdisciplinary and international regional collaboration Traditional In Situ Obs. - Eye Obs.(Ship, Aircraft etc.) - Buoy/ship time series Obs. - Water sampling by ship Red-tide detection Research - Marine biology - Environmental research - Bio-Physical interaction - Bio-Geochemical interaction Operation - Continuous monitoring Ocean Color Remote Sensing - Warning Benefits - Spices identification - Wide-ranging High-resolution (Water sampling and lab. Simultaneous Obs. Process) - Regular High-resolution - Mitigation Temporal Obs. Red-tide related Defects marine environmental - No Obs. Under clouds information Possible contributions from Remote Sensing High-resolution satellite images Chl-a, SS, CDOM, SST, nlw, Solar Radiation etc., Surface winds, Surface currents TSM(mg/L) Tang s SS algorithm 10

11 Summer SS distribution and tidal residual current In order to detect the redtide in the type-ii water, we need to understand the SS behavior in the regional seas New Generation SST Ver ) Geostationary Met. Satellite Hourly Infrared AVHRR VIRS Merging by objective analyses TMI SST Microwave SST Cloud free Cloud-free, High Resolution, Quality-Controlled 5 Km Spatial Resolution, Daily SST Product NGSST-C R&D Achievements New Generation SST for Coastal Sea (NGSST-C) Spatial resolution: 1-km Temporal resolution: 6-hour (Resolve Diurnal signal) Coverage: First NEAR-GOOS, extend to the Northern WESTPAC region and the Southern WESTPAC region 11

12 Geostationary Meteorological Satellite : Hourly Solar Radiation Snapshot: 15 September 2006 Mean DSSR in Nov.,