Project: Scientific Publications Regarding LIDAR projects
PI: Contract No.: Award Amount/Year(s):  
James H. Churnside   03-10-04   FY03 ($25,000)    
Affiliation: Address: Phone: E-mail:
Environmental Technology Laboratory/NOAA   ETL/NOAA
325 Broadway
Boulder, CO 80305 
303-497-6744   James.h.churnside@noaa.gov  

Deliverables:
Two papers to be prepared for submittal to scientific journals. One paper will compare the airborne lidar results of plankton surveys with the ship surveys done by the PWSSC. The second paper’s topic will be the detection of salmon by airborne radar.

Project Summary

The proposal for completion funding for the ETL remote sensing program in Prince William Sound asks for support to publish two novel aspects of the work.

The first topic is application of airborne lidar to plankton surveys. While we clearly see plankton on all of our fish surveys, no one has done a survey with ship support to provide information on plankton species, concentration, and depth distribution. We will prepare a paper for journal publication that compares the lidar results with the ship surveys done by PWSSC. This will be the first paper on the subject, and may open an entirely new area of airborne surveys of plankton. To do this, we need to modify our data processing technique for the plankton signal. We then need to bin the lidar and acoustic data on the same special scale so that they can be compared directly. Finally, we need to interpret and write up the results.

The second area is the imaging lidar that was developed for the surveys of adult salmon in the turbid waters of the Copper River. The work is also unique; no one has yet used lidar to obtain images in turbid water. This technique has the potential to provide a tool to map the distribution of returning salmon both outside the river mouth and up the length of the river. Even in very shallow and turbid water, it should be possible to identify and count individual fish. We take lidar images of salmon and apply established techniques for increasing contrast and image quality, we also look for automatic recognition and counting of fish.