Date of Completion
4-18-2017
Embargo Period
4-18-2017
Keywords
complex adaptive systems; agent based models; economic displacement; wind farm; collision risk
Major Advisor
Robert Cromley
Co-Major Advisor
Thomas Meyer
Associate Advisor
Carol Atkinson-Palombo
Associate Advisor
Nathaniel Trumbull
Field of Study
Geography
Degree
Doctor of Philosophy
Open Access
Open Access
Abstract
As marine space is managed into appropriate resource use areas, it is inevitable that some is allocated towards a mutually exclusive spatial activity. This exclusion results in displacement that has real economic consequences. When a wind energy area is placed in coastal waters, navigable space is reduced and vessels are displaced from their former routes. The USCG is concerned that re-routing will result in vessels navigating within closer proximity than they would otherwise in an open ocean scenario, and fear that this will increase the risk of vessel collision (USCG 2016). They recommend research into tools that are capable of predicting changes in vessel traffic patterns (USCG 2016). Agent based models are a method capable of predicting these traffic patterns, and are composed individual, autonomous goal directed software objects that form emergent behavior of interest. Agents are controlled by a simple behavioral rule, they must arrive at their destination without colliding with an obstacle or other vessel. They enforce this rule with the gravitational potential that exists between two objects. Attractive forces pull each agent towards their destination, while repulsive forces push them away from danger. We validated simulated vessel tracks against real turning circle test data, tested for the presence of chaotic systems, developed metrics to assess transportation costs, and applied the method to assess a wind energy area located outside of the entrance to the Port of New York and New Jersey.
Recommended Citation
Nebiolo, Kevin P., "Anticipating the Effects of Economic Displacement in Marine Space with Agent Based Models" (2017). Doctoral Dissertations. 1380.
https://digitalcommons.lib.uconn.edu/dissertations/1380