Detecting Marine Life from the Air
James Churnside
NOAA Environmental Technology Laboratory
There are a couple of airborne technologies that should be considered in a discussion of emerging technologies. The primary advantage of airborne measurements is the speed of the sensor - 120 to 150 kts instead of 10 kts for a surface vessel. The speed of the aircraft allows measurements of processes with large spatial scales and short temporal scales. It allows large areas to be covered at lower cost that a surface vessel. The primary disadvantage of airborne measurements is that blue-green light is the only viable basis for candidate technologies, and it is limited in its depth penetration to the top few tens of meters of the ocean. Fortunately, this is a region of considerable interest.
The first emerging technology is airborne lidar. In its simplest form, airborne lidar acts like an echosounder, except that it uses a short light pulse instead of a short acoustic pulse. Under favorable conditions, we expect this type of lidar to penetrate down to about 50 m. The challenges of this type of lidar are similar to those of the echosounder - species identification and robust relationships between target strength and biomass. More sophisticated lidars provide either volume images or horizontal images at fixed depths. These may help to provide species identification information, but are more expensive. It is not clear at the present time whether or not the additional information is worth the extra cost.
Multi- or hyper-spectral imaging from an aircraft is another emerging technology. Since it uses ambient light, the depth penetration is not as great, and there is little depth information contained in the images. However, the addition of spectral information that these technologies provide may be very useful in species identification. Expert fish spotters are very good at species identification, and it seems plausible that that skill could be transferred to an appropriate passive sensor.
The primary benefits of airborne technologies will probably not be realized through lidar or imager measurements alone; the information is not complete. Instead, airborne measurements can most effectively be used in conjunction with ship-based measurements using acoustics, in-water optics, and direct sampling. They may be used to resolve questions of aliasing space and time scales measured by the ship. They may be used to extrapolate ship measurements over larger areas. They may be used to direct the ship so that limited days at sea are used most productively. The most effective combination of platforms is an area that needs much more investigation.
A brief description of the lidar is presented below. More details (and pictures) can be found on the web at http://www.etl.noaa.gov/lidar
Block diagram of airborne lidar Light from laser is expanded by a lens and directed to the surface by a pair of steering mirrors. The return light is passed through a polarizer into a telescope onto a detector. The detected signal is digitized and recorded in a personal computer.
Photograph of lidar installed in aircraft The large white round object is the telescope. The black object to the right of the telescope is the laser. The computer and laser power supply are in the rack to the left.
Lidar image of fish school This is an image of the return from 30 s of flight. The red to green object is a school of anchovies. The blue to violet regions are plankton.
Lidar image of a school of sardines This image is of a school of sardines. It has been thresholded to remove the plankton signal.
Map of relative distribution of fish The size of the symbol is related to the target strength, which can be related to the amount of fish present. It is averaged over about 1 nautical mile along the flight track, and represents one flight.
Depth distribution of biomass These are histograms of one-nautical-mile averages of depth distribution of fish for one flight. For this flight, there were significant fish near the surface, and another band with a peak at 15 - 20 m in depth.
This page is maintained and was last updated 14-Nov-00 by Pip Sumsion (sumsionp@dfo-mpo.gc.ca).