Designing and Building a Vector Feature Database
NAVAL RESEARCH LAB STENNIS SPACE CENTER MS MARINE GEOSCIENCES DIV
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High-resolution imagery can be stored on the computer in digital form as a picture, for example, a digital raster map image file. These images then can be geo-registered by computing coefficients from points with known latitude and longitude locations. Features such as roads and airports can be extracted by applying image-processing techniques to the geo-registered raster image. Attributes describing these features and their geographical locations are stored in a vector feature database. The vector feature database contains many feature types and is considered accurate to a given map scale. In a realtime processing system there is a need to input attributes and their locations and subsequently retrieve such feature attributes from the database with minimum processing time. The overall size of the database is also a consideration. This paper explores the design and construction of a vector feature database to 1 optimize the size of the database by reducing the number of attributes while still maintaining an adequate and unique description of the feature, and 2 enable high-speed input and retrieval of features. Several data structures that might be used to construct the database are discussed, including hash tables, binary-trees, quad-trees, and R-trees. Ultimately a quadtree structure modified to use geographic bitmaps is implemented and evaluated.
- Computer Systems
- Cartography and Aerial Photography