CDI-Type I: Collaborative Research: A Computational Thinking Approach to Mapping Critical Marine Mammal Habitat Through Readily-Deployable Video Systems.

[No authors listed]

UIID-NSF: 426

Abstract

Unprecedented thinning and retreat of the Arctic sea ice cover together with recent climate modeling studies that predict the Arctic could be free or nearly free of sea ice in summertime within the next few decades have raised concern for the future of Arctic ice-?associated marine mammals. All species of ice-dependent marine mammals of Beringia have been subject to petitions to designate them as threatened or endangered under the Endangered Species Act of 1973. Accordingly, in 2008, the polar bear was listed as threatened after the U.S Fish and Wildlife Service [2008] found that ?polar bear habitat - principally sea ice - is declining throughout the species? range?. The case for the Pacific walrus is under review with the U.S. Fish and Wildlife Service Endangered Species Program and two ice seal species have been proposed for protective status. A major challenge facing these national policy decisions is lack of information concerning the extent and distribution of critical habitat within the overall ice pack. Most climate models and standard sea ice data products provide ice extent and concentration information, but these quantities only partially explain the distribution of Arctic marine mammals. The size and shape of ice floes and openings has also been shown to be important, but there are currently no standardized means of monitoring these properties of the sea ice cover. The work proposed here aims to develop new, powerful video processing techniques and bring them to bear on the problem of identifying and quantifying critical habitat areas within the Arctic ice pack. The project team brings together scientists and engineers with expertise in advanced image and video analysis and modeling, computational science, sea ice geophysics and marine mammal ecology. The research plan is centered on a computational-thinking approach to transforming high-volume video data into low-volume high-relevance information that is key to decision support in a range of settings. The overall aim is to develop and implement advanced video processing algorithms based on geophysical and ecological knowledge of sea ice to routinely map marine mammal habitat in ice covered waters. Data from the system will be disseminated to a cyber-enabled forum of experts, who will aid in habitat interpretation and provide guidance for data acquisition. The project will build on existing cyber-enabled forums such as the Sea Ice for Walrus Outlook (SIWO, co-organized by Eicken) as models for implementation. The techniques that will be developed will be readily extendible to other observing tasks such as marine hazard identification. Such information will become increasingly important in the near future with growing commercial activity and limited decision-making and support infrastructure in the Arctic. A readily-deployable, networkable system will allow increased marine traffic in the Arctic to be turned to an advantage. This project is supported by the NSF Directorate for Geosciences and the Experimental Program to Stimulate Competitive Research (EPSCoR).

Other Details

• Award Instrument: Standard Grant
• Email: [email protected]
• Organization: University of Delaware
• Other Investigators: David Collard, Emelita Breyer
• Primary Investigator: Chandra Kambhamettu
• Program(s): CDI TYPE I, EXP PROG TO STIM COMP RES
• Start Date: 09/15/2011