Unsupported Browser Detected

Internet Explorer lacks support for the features of this website. For the best experience, please use a modern browser such as Chrome, Firefox, or Edge.

Citizen Scientists Help Count Deep-7 Bottomfish in Hawaiʻi

September 15, 2020

NOAA scientists are partnering with citizen scientists to count seven important bottomfish species.

750x500-Sette-PIFSC.jpg

The Pacific Islands Fisheries Science Center is launching a new citizen science project called OceanEYEs. We are seeking volunteers to help find Deep 7 bottomfish in underwater videos.

A student in the Young Scientist Opportunity program and our scientists have partnered with Zooniverse.org to develop a user-friendly web page called OceanEYEs. There, citizen scientists can help review images from our annual bottomfish survey, tagging and identifying all the fish that they see. Scientists can then use those data to train advanced artificial intelligence (AI) tools, to look at different ways of counting fish in video. The data can also be used as information for stock assessments.

Image
A Modular Optical Underwater Survey System lowered via crane from the side of a boat into the water.
The Modular Optical Underwater Survey System MOUSS deploying off a NOAA 19' SafeBoat.

The images are collected every year during the Bottomfish Fishery-Independent Survey in Hawaii (#BFISH) using state of the art stereo-camera systems. The survey provides an estimate of the number of “Deep 7” bottomfish. That’s a group of seven species of fish that have both economic and cultural value to the islands. The data from this survey are used in the Deep 7 stock assessment to provide managers with the best information to make management decisions. That includes annual commercial fishery catch limits.

The camera systems, which rest on the seafloor for 15 minutes at a time, record hundreds of thousands of images over the course of the survey. NOAA scientists currently analyze these images but, as you can imagine, the number of images collected during survey operations can quickly overwhelm them.

NOAA has been investing heavily in the development of AI solutions, allowing scientists to use machine learning and computer vision to analyze images. However, for the machine to learn, it requires large numbers of training images. Those are images of fish that a human has already tagged and identified.

Image
Black and white image of a school of fish as they swim by a square metal rod with survey equipment attached to it.
A school of opakapaka, as seen by the Modular Optical Underwater Survey System.

The OceanEYEs web page gives users a tutorial on how to recognize each fish species and how to properly mark them in the image. It also has a field guide and text to help users identify and annotate fish. Users can also learn about the science behind OceanEYEs.

Video tutorial on how to annotate fish in the Zooniverse-hosted OceanEYEs.

Fifteen different people view and annotate each image, and the results are compiled to give a “consensus” annotation. Initial results suggest that consensus annotations can match the accuracy of professional analysts, greatly enhancing NOAA’s capabilities to process image data from the Pacific Islands region. So log on, dive in, and start exploring the underwater world while helping assess Hawaii’s bottomfish populations!

The information collected via the OceanEYEs project is authorized under the OMB Control Number included in the Citizen Science & Crowdsourcing Information Collection page. This information helps inform management decisions for bottomfish in the Pacific Islands.

Last updated by Pacific Islands Fisheries Science Center on October 22, 2024

Citizen Science