It is shown that an SPP group where individuals assume the average velocity of their neighbours behaves as a fluid over large spatial scales. The stability of this orderly state of motion in large SPP-groups is studied by developing a fluid-dynamic theory for flocking behavior based on perturbation analysis. Several species of fish, birds, insects, mammals and other self propelled particles (SPPs) are known to group in large numbers and exhibit orderly migrations. By quantifying the formation processes of vast oceanic fish shoals during spawning, it is shown that (1) a rapid transition from disordered to highly synchronized behavior occurs as population density reaches a critical value (2) organized group migration occurs after this transition and (3) small sets of leaders significantly influence the actions of much larger groups. Observations of fish shoals made during the OAWRS 2006 experiment in the Georges Bank are used to confirm general theoretical predictions on group behavior believed to apply in nature irrespective of animal species. By applying MEF to fish population density image sequences collected during the OAWRS 2003 experiment in the New Jersey strataform, we quantify (1) inter-shoal dynamics such as coalescence of fish groups over tens of kilometers, (2) fish mass flow between different parts of a large shoal and (3) the stresses acting on large fish shoals. Using density image sequences describing cell splitting, for example, we show that cell division is driven by gradients in apparent pressure within a cell. The MEF method is applied to experimentally obtained density images, spanning spatial scales from micrometers to several kilometers. Shoal dynamics is studied by developing a novel Minimum Energy Flow (MEF) method to extract velocity and force fields driving motion from time-varying density images describing compressible or incompressible motion. In this Thesis, it is shown how the recently developed Ocean Acoustic Waveguide Remote Sensing (OAWRS) technique can be used to (1) quantify the acoustic scattering response of fish and remotely infer their physiological characteristics to enable species classification, and (2) remotely assess shoaling populations and quantify their group behavior in a variety of oceanic ecosystems. Despite their ecological importance, there is substantial evidence that fish populations are declining worldwide, motivating the need for an ecosystem approach to fisheries management through ecosystem scale sensing of fish populations and behavior. They typically play an essential role in inter-trophic energy transport, and serve as a mainstay for human consumption comprising roughly 16% of the animal protein consumed by the world's population. Second, from an applications point of view the developed algorithm can be used to augment the tools that are available for the measurement of fluid dynamics other imaged flows that observe compatible constraints might benefit in a similar fashion.ДЇish populations often comprise the largest biomass in a productive marine ecosystem. First, from a theoretical point of view it is shown how information derived from the physical behavior of fluids can be used to motivate a flow-recovery algorithm. The significance of this work is twofold. In these experiments, the algorithm recovered accurate and precise estimates of the flow. Empirical results from application of the algorithm to transmittance imagery of fluid flows, where the fluids contained a contrast medium, are presented. The approach centers around a motion-recovery algorithm that is based on principles from fluid mechanics: The algorithm is constrained so that recovered flows observe conservation of mass as well as physically motivated boundary conditions.

This paper presents an approach to measuring fluid flow from image sequences.

Playblast fluid image sequence