Abstract
Many spatial data analyses demand processing geographic phenomena varying continuously over space, e.g., air pollution. In the paper such phenomena are called geofields and queries concerning them - geofield queries.When geofields are represented in a database as point measurements, than answering geofield queries requires computationally intensive interpolation. Writing a spatial analysis as one declarative geofield query makes it possible to optimize its execution. Such an optimization was the goal of the presented computational model consisting of: (a) discrete computational space, (b) relational representation of geofields based on Peano N space-filling curve and RVA, and (c) a set of operations extending relational algebra. The presented computational model made it possible to evaluate geofield queries by two orders of magnitude faster than in classical raster representation.
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Bajerski, P., Kozielski, S. (2009). Computational Model for Efficient Processing of Geofield Queries. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_60
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DOI: https://doi.org/10.1007/978-3-642-00563-3_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00562-6
Online ISBN: 978-3-642-00563-3
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