This content is
presented from a geomatics engineering perspective; it is written for computer scientists
who know the fundamental concepts related to spatial datacubes and OLAP.
Background. Information
With the recent evolution of geomatics sciences (geodesy, global positioning systems
(GPS), photogrammetry, remote sensing, surveying, mapping, and GIS), we
gather today terabytes of land-related data everyday at a cost that is much lower
than a decade ago. Mainstream applications using spatial data are appearing everywhere.
The benefits of using spatial data have been discussed previously in a
general manner. In the particular case of SOLAP, the tight integration of GIS and
02 B?©dard, Rivest, & Proulx
Copyright ?© 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of
Idea Group Inc. is prohibited.
OLAP bring significant profits such as (1) offering the most intuitive user interface
insofar to access cross-referenced spatial data, (2) offering the fastest solution to
access aggregated spatial data, and (3) allowing the discovery of spatial patterns
and clusters of phenomena that cannot be detected with OLAP solely (e.g., a phenomenon
taking place in the forest stands located along a river gets unnoticed when
the next aggregated level of OLAP spatial units are administrative regions made
of thousands of stands).
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