The Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS), which began in 2008, includes the University of Maine’s comprehensive data buoy array in the Gulf of Maine (GoM). The University of Maine buoy system started in 2001 as part
of the Gulf of Maine Ocean Observing System (GoMOOS). The buoys provide a wide variety of oceanographic and marine meteorological data in real time to scientists, environmentalists, the National Weather Service, the U.S. Coast Guard and Canadian Coast Guard, educators, regional natural resource
managers, the GoM fishing and maritime industries, and the general public. The GoM observing system is presently undergoing a redesign of the buoy control system to enhance remote access and reduce operational costs. The enhancements will allow remote trouble-shooting and reprogramming of
the buoys and subsurface sensors. The system will also accommodate sensors from other research groups and allow them post-deployment control without assistance from our buoy group.Over the near-decade of operation, the system has revealed marked seasonal and interannual variability of
the circulation and physical properties of the GoM. In the fall of 2004 to spring of 2005, Doppler currents measured an outflow of deep salty slope waters that suggest a regime shift in the inflow and outflow of transports through the Northeast Channel. During the same period, a salinity anomaly
event lowered salinity throughout the GoM by roughly 2 psu by the winter of 2005. In following years, the previously unusual slope outflow and reduced salinity have often reoccurred.
‘The Theory of a Cartographic Line’ (Peucker 1975) describes width as being the essential characteristic of a cartographic line. Digital representations have tended to ignore this basic attribute and in the context of generalization the oversight is detrimental. The theory claims that a set of enclosing bands captures the cartographic character of width and supports generalization. The Douglas algorithm, still one of the most commonly used algorithms for generalizing digital representations, uses this model. Work of a Polish mathematician Perkal, provides the basis for another model of cartographic line width and a different generalization technique. This paper examines how effectively both models capture cartographic line width and succeed in producing generalized results, particularly for larger scale reductions. The two techniques are assessed by their ability to satisfy two objectives: capturing the essential and recognizable characteristics of geographic features and creating representations which can be legibly displayed at smaller scales. The paper compares the behavior of the two methods as applied to digital coastline data.
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