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The application of satellite imagery to a predictive model of cetacean density

The application of satellite imagery to a predictive model of cetacean density. Tom Norris 1 Christine Loftus 1 Jay Barlow 2 Ed Armstrong 3. 1 Science Applications International Corporation 2 NOAA-Southwest Fisheries Science Center 3 Jet propulsion Laboratory, Caltech. Objectives.

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The application of satellite imagery to a predictive model of cetacean density

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  1. The application of satellite imagery to a predictive model of cetacean density Tom Norris1 Christine Loftus1 Jay Barlow2 Ed Armstrong3 1 Science Applications International Corporation 2 NOAA-Southwest Fisheries Science Center 3 Jet propulsion Laboratory, Caltech

  2. Objectives • To compare the results of a predictive model of marine mammal distribution and abundance that uses in-situ (i.e. ship aquired) oceanographic data versus satellite aquired oceanographic data. • To examine the effects of temporal averaging • of satellite data on model results.

  3. ORCAWALE 2001 Methods: data collection • Marine mammal surveys were conducted by NOAA-SWFSC in the temperate eastern North Pacific in ’91, ’93, ’96 & 2001. Cetacean survey data: line-transect methods used. Chl-a and SST data: standard techniques used.

  4. Methods: model development • A generalized additive model will be developed by SWFSC (after Forney, 2000) based on archival (e.g. bathymetry) and ship-acquired (in-situ) environmental data for years: 1991, 1993, and 1996. • Model will be evaluated for inter-annual predictive power using data from the 2001 fall marine mammal survey (ORCAWALE cruise).

  5. Methods: satellite data • Model applied and tested using satellite derived environmental data - specifically SST and chl-a. AVHRR - SST SeaWIFS - chl-a

  6. Methods: satellite data sets 8-day monthly SeaWiFS AVHRR seasonal annual Matchup processing (SAIC) Matchup processing (SAIC) best pixel

  7. 8-day monthly seasonal annual Daily Methods: best pixel matchup database no daily match? no 8-day match? yes no monthly match? yes seasonal match? no yes annual match yes Best pixel

  8. Methods: comparison of model results • Compare model results from satellite vs. ship acquired data inputs. • Examine effects of temporal averaging of satellite data on model results. • Quantify differences with statistical tests. • Qualitatively assess differences with maps.

  9. In-situ vs. satellite data • Satellite data are synoptic and therefore may be a better indicator of overal environmental conditions related to habitat of marine mammals. • pixel dimension = 9 km2. • covearage is widespread (with some exceptions). • archival satellite data is readily available (for running models). • in-situ data are collected continuously but are avaeraged and characterized as point measurements.

  10. Timeline • August 2003 - Begin effort. • January 2003 - Complete match-up database. • March 2003 - Complete model execution for all data. • May 2003 - Complete model validation and testing. • July 2003 - Analysis, summary, and final report.

  11. Future efforts • Model development: • Develop a model using satellite data for 2001survey (NOTE: chl-a / SeaWiFS data do not exist for ‘91- ‘96). • Validate satellite data model for other years • (once additional marine mammal survey data are available). • Include SST and chl-a and bathymetry gradients as and hydrographic modeled data (e.g. vertical temp. structure) in model development • Other: • Test for auto-correlations between SST gradients, chl- • a gradients, and bathymetry gradients.

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