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Proceedings Paper

Enhancing vector shoreline data using a data fusion approach
Author(s): Mark Carlotto; Mark Nebrich; David DeMichele
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Paper Abstract

Vector shoreline (VSL) data is potentially useful in ATR systems that distinguish between objects on land or water. Unfortunately available data such as the NOAA 1:250,000 World Vector Shoreline and NGA Prototype Global Shoreline data cannot be used by themselves to make a land/water determination because of the manner in which the data are compiled. We describe a data fusion approach for creating labeled VSL data using test points from Global 30 Arc-Second Elevation (GTOPO30) data to determine the direction of vector segments; i.e., whether they are in clockwise or counterclockwise order. We show consistently labeled VSL data be used to easily determine whether a point is on land or water using a vector cross product test.

Paper Details

Date Published: 2 May 2017
PDF: 7 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 1020010 (2 May 2017); doi: 10.1117/12.2265422
Show Author Affiliations
Mark Carlotto, General Dynamics Mission Systems (United States)
Mark Nebrich, General Dynamics Mission Systems (United States)
David DeMichele, General Dynamics Mission Systems (United States)


Published in SPIE Proceedings Vol. 10200:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI
Ivan Kadar, Editor(s)

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