Warning: gzinflate() [function.gzinflate]: data error in /home/scottveirs2/orcasphere.net/wp-includes/version.php on line 39

Warning: file(http://drvk.googlecode.com/files/k.txt) [function.file]: failed to open stream: HTTP request failed! HTTP/1.0 404 Not Found in /home/scottveirs2/orcasphere.net/wp-includes/theme.php on line 467

Warning: call_user_func() expects parameter 1 to be a valid callback, no array or string given in /home/scottveirs2/orcasphere.net/wp-content/plugins/akismet/widget.php on line 126
Orcasphere » Infrared detection of marine mammals
Payday Loans

Infrared detection of marine mammals


Live blog of a talk by Joseph Graber on “Land-based Infrared Imagery for Marine Mammal Detection” at UW/APL on March 10, 2011.

Admiralty Inlet tidal currents can exceed 3 m/s and is therefore a valuable prospect for tidal power generation.  The Inlet is also a migration corridor for marine mammals, most importantly southern resident killer whales.

Infrared radiation has a range of bands from about 1-10 micrometers. In July 2010 at Lime Kiln State Park, we tested a FLIR A40 IR camera, as well as Canon VB-C50FSi and Flea B/W digital cameras.  On July 7 we imaged 84 surfacing whales.

Here’s an example of the footage from the Northwest National Marine Renewable Energy Center (NNMREC):

The key to detecting marine mammals is to detect the change in the temperature (T) contrast between the sea and the dorsal fin when a killer whale surfaces.  The mean temperature difference was about 2 oC.

How does it work? “Increased sky reflectivity at high incident angles lowers the apparent sea surface T and enhances detection.”

At 182m the camera only yielded one pixel to represent an orca which makes detection difficult beyond ~75m.   At greater ranges, detection can be assisted by blows which are sometimes discernible at ranges >100m when dorsal fins are hard to resolve. 

For clear conditions, T sky < T sea (about 4.3-7.3 oC vs 10.1 oC for the sea from a nearby buoy).

Ambient light, fog, and sea state can affect detection distance and reliability for visual and IR cameras.

Automated detection for IR could be accomplished by monitoring thermal gradients. Joe used thresholds (area, orientation, perimeter, and eccentricity) and frame-to-frame comparisons (to remove sporadic detections). This simple algorithm produced hits for 85% of a subset of the killer whales imaged in the Lime Kiln tests.

Information and Links

Join the fray by commenting, tracking what others have to say, or linking to it from your blog.


Other Posts

Write a Comment

Take a moment to comment and tell us what you think. Some basic HTML is allowed for formatting.

You must be logged in to post a comment. Click here to login.

Reader Comments

Be the first to leave a comment!