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Harmful algal blooms: the contrast with other algal blooms (2)

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When? This feed was archived on June 24, 2018 16:45 (6y ago). Last successful fetch was on April 13, 2018 04:19 (6+ y ago)

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Manage episode 187915453 series 1564588
Content provided by IOCCG Summer Lecture Series 2012. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by IOCCG Summer Lecture Series 2012 or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
1.What are harmful algal blooms (HABs)? Contrast of HABs to functional groups What must be known to detect HABs Environment Simple physiology and ecology Ecological conditions “Operational” vs research considerations Work exercise: A strategy to respond to reports of a HAB 2.Methods Chlorophyll Change detection Analytical algorithms Spectral shape (MCI, FLH, CI) Other algorithms (brightness, empirical, etc.) Ancillary data (SST, winds) Ensemble methods Work exercise: Case Study (to be provided) 3.Using satellite Limitations defined by objective, method, species, environment Satellite strengths and weakness Algorithm failures Atmospheric correction challenges Work exercise: identify best method for a case study (to be provided) 4.Validation Quantitative data vs qualitative data False positives and false negatives Field observations (ocean color, cells, toxins, impacts) Work exercise: sampling strategy 5.Applications Advisories Forecasts “Event response” (dead marine mammals, fish kills, bird kills, sickness) Discussion of case studies Bibliography J. GOWER, S. KING, G. BORSTAD and L. BROWN (2005). Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer International Journal of Remote Sensing 26(9): 2005–2012 Stumpf, R.P. and M.C. Tomlinson (2005) Remote sensing of harmful algal blooms. In: Miller, R.L., C.E. Del Castillo, and B.A. McKee, eds. Remote Sensing of Coastal Aquatic Environments. Springer, AH Dordrecht, The Netherlands, chapter 12, pp. 277?296. Stumpf, R.P. (2006) Forecasting Harmful Algal Blooms: The Roles of Optical Oceanography and Remote Sensing. Material presented at Ocean Optics XVIII. Wynne, T. T., Stumpf, R. P., Tomlinson, M. C., and Dyble, J. (2010). Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data. Limnol. Oceanogr., 55(5), 2025–2036
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31 episodes

Artwork
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Archived series ("Inactive feed" status)

When? This feed was archived on June 24, 2018 16:45 (6y ago). Last successful fetch was on April 13, 2018 04:19 (6+ y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 187915453 series 1564588
Content provided by IOCCG Summer Lecture Series 2012. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by IOCCG Summer Lecture Series 2012 or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
1.What are harmful algal blooms (HABs)? Contrast of HABs to functional groups What must be known to detect HABs Environment Simple physiology and ecology Ecological conditions “Operational” vs research considerations Work exercise: A strategy to respond to reports of a HAB 2.Methods Chlorophyll Change detection Analytical algorithms Spectral shape (MCI, FLH, CI) Other algorithms (brightness, empirical, etc.) Ancillary data (SST, winds) Ensemble methods Work exercise: Case Study (to be provided) 3.Using satellite Limitations defined by objective, method, species, environment Satellite strengths and weakness Algorithm failures Atmospheric correction challenges Work exercise: identify best method for a case study (to be provided) 4.Validation Quantitative data vs qualitative data False positives and false negatives Field observations (ocean color, cells, toxins, impacts) Work exercise: sampling strategy 5.Applications Advisories Forecasts “Event response” (dead marine mammals, fish kills, bird kills, sickness) Discussion of case studies Bibliography J. GOWER, S. KING, G. BORSTAD and L. BROWN (2005). Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer International Journal of Remote Sensing 26(9): 2005–2012 Stumpf, R.P. and M.C. Tomlinson (2005) Remote sensing of harmful algal blooms. In: Miller, R.L., C.E. Del Castillo, and B.A. McKee, eds. Remote Sensing of Coastal Aquatic Environments. Springer, AH Dordrecht, The Netherlands, chapter 12, pp. 277?296. Stumpf, R.P. (2006) Forecasting Harmful Algal Blooms: The Roles of Optical Oceanography and Remote Sensing. Material presented at Ocean Optics XVIII. Wynne, T. T., Stumpf, R. P., Tomlinson, M. C., and Dyble, J. (2010). Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data. Limnol. Oceanogr., 55(5), 2025–2036
  continue reading

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