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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.

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Presentation on theme: "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."— Presentation transcript:

1 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

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

4 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 Model will be evaluated for inter-annual predictive power using data from the 2001 fall marine mammal survey (ORCAWALE cruise). Methods: model development

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

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

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

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 Satellite data are synoptic and therefore may be a better indicator of overal environmental conditions related to habitat of marine mammals. pixel dimension = 9 km 2. 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. In-situ vs. satellite data

10 Timeline August Begin effort. January Complete match-up database. March Complete model execution for all data. May Complete model validation and testing. July 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 ). 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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