Extending General Compact Querieable Representations to GIS Applications
Nieves Brisaboa, Ana Cerdeira, Guillermo de Bernardo, Gonzalo Navarro,
and Oscar Pedreira.
The raster model is commonly used for the representation of images
in many domains, and is especially useful in Geographic Information
Systems (GIS) to store information about continuous variables of the space
(elevation, temperature, etc.). Current representations of raster
data are usually designed for external memory or, when stored in
main memory, lack efficient query capabilities. In this paper we
propose compact representations to efficiently store and query
raster datasets in main memory.
We present different representations for binary raster data, general
raster data and time-evolving raster data. We experimentally compare
our proposals with traditional storage mechanisms such as linear quadtrees or
compressed GeoTIFF files. Results show that our structures are up to 10 times
smaller than classical linear quadtrees, and even comparable in space to
non-querieable representations of raster data, while efficiently answering a
number of typical queries.