1 / 33

Optical Sensors Mary Jane Perry University of Maine ALPS Workshop 31 March 2003 La Jolla, California

Optical Sensors Mary Jane Perry University of Maine ALPS Workshop 31 March 2003 La Jolla, California. What variables are amenable to detection and measurement by optical sensors ?.

salena
Télécharger la présentation

Optical Sensors Mary Jane Perry University of Maine ALPS Workshop 31 March 2003 La Jolla, California

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Optical SensorsMary Jane PerryUniversity of MaineALPS Workshop31 March 2003La Jolla, California

  2. What variables are amenable to detection and measurement by optical sensors ? * Particles -> scatter light - biologics (viruses, bacteria, phytoplankton, zooplankton, small fish) - inorganics (non-biogenic & biogenic, CaCO3)* Particles and dissolved materials -> selective absorption in UV and visible - phytoplankton - iron-rich minerals - C-DOM - nitrate

  3. 1. Individual particles * imaging (video plankton recorder) * analysis (flow cytometer) 2. Radiometric analysis of “bulk” optics * passive * active Two approaches to optical measurement:

  4. Today:Scientific questionsExamples of measurement from individual particle analysis radometeric sensorsChallenges for ALPS optical sensors

  5. Scientific questions What species are in the plankton and how does species composition change in response to environmental variability? * events - storms, aeolian Fe-rich dust * inter-annual and climatic change * HABs, species invasion, top predator loss (we don’t know due to lack of sustained observations)

  6. Scientific questions What are the patterns of distribution and abundance of: * individual species - bioluminescent organisms, salps, etc. * “bulk” variables - particulate & dissolved organic carbon - suspended minerals - total phytoplankton (satellite limitations-->)

  7. North Atlantic spring bloom, April pigment concentration

  8. North Atlantic spring bloom, April pigment concentration pixels / month

  9. Scientific questions How do processes vary in space/time and in response to environmental variability? * carbon cycle net carbon fixation carbon flux coccolithophorid production * sediment resuspension and riverine mineral delivery

  10. Imaging of individual particles Goal to identify taxa Target particles: phytoplankton, zooplankton & small fish Challenges Image quality Pattern recognition algorithms (Presentation of organism to camera) Large size and high power consumption Some systems have been deployed on AUVs

  11. Copepods - video plankton recorder (Gallager and Davis, WHOI)

  12. Flow Cytometery of individual particles *individual particle scattering and fluorescence*could be coupled w/ molecular probes* large size & high power consumption (data from Cytobuoy)

  13. Radiometry - second approach to optical measurement * “Bulk” properties (vs. individual particles) * Active and passive sensors * Smaller and lower power (vs. individual particles) *** Concept of proxies e.g., phytoplankton can be measured as absorption coefficient beam c or scattering coefficient (if no inorganics) fluorescence intensity diffuse attenuation coefficient (Kd) remote sensing reflectance

  14. Radiometry * Inherent Optical Properties absorption, scattering, attenuation * Apparent Optical Properties irradiance, radiance, reflectance, diffuse attenuation coefficient * energy conversions fluorescence bioluminescence

  15. Radiometry * Inherent Optical Properties - active absorption, scattering, attenuation * Apparent Optical Properties - passive irradiance, radiance, reflectance, diffuse attenuation coefficient * energy conversions fluorescence - active bioluminescence - passive

  16. Active sensors - higher energy - internal light source + nighttime and at depth Passive sensors + lower energy - solar light source - daytime only and in photic zone + diffuse attenuation coefficient fouling independent

  17. Active radiometers * Inherent Optical Properties absorption scattering (total, forward, backscattering)attenuation (beam c)* Energy conversionfluorescence

  18. Eriksen Seaglider WET Lab bb2f, measure chl fluorescence as proxy for phytoplankton and particle backscattering at 2 ls

  19. gli Glider track off Washington Next 3 figures, please note axis is time

  20. Backscattering - sediment and phytoplankton

  21. Chlorophyll fluorescence - daytime quenching

  22. O2 pattern similar to fluorescence (multiple sensors)

  23. Bishop et al. Iron stimulation (by dust storm) of phytoplankton production at Station PAPA, 2001 Two drifters with beam transmissometer (a proxy for POC)

  24. several days after dust event increase in beam c (carbon proxy)

  25. Passive radiometers * Apparent Optical Properties irradiance and radiance diffuse attenuation coefficient * Energy conversion bioluminescence

  26. Ed (l) Underwater light field (data from Carder, on an AUV) Lu(l)

  27. Mitchell et al. Evolution of phytoplankton bloom in the Sea of Japan. Ed, Lu was measured at 3 l ,with on-board calculation of Kd. SOLO drifter track in Sea of Japan, spring 2000

  28. Temperature K490 phytoplankton proxy

  29. AUV measured backscattering, chlorophyll fluorescence, and bioluminescence in Monterey BayHaddock et. al. (complements of J. Case) bb BL F

  30. Sensor sizePower requirementsSensor calibration, QA, QCStability in long-term deployments (long-term)Biofouling solutions Interpretation of proxies; need for multiple proxiesVolume sampled in patchy environmentsOptimization of sampling rate; conditional samplingData storage, on-board processingGeospatial/temporal data analysis

More Related