GeoWorld October 2012

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Get Relational Figure 2 identifies another, more-practical mecha- nism for storage using a relational database. In essence, each of the conceptual grid-map spread- sheets can be converted to an interlaced format, with a long string of numbers forming the columns (data fields); the rows (records) identify the informa- tion available in each of the individual grid cells that form the reference grid. For fairly small areas (up to a million or so cells), this is an excellent way to store grid maps, as their spatial coincidence is inherent in the organization, and the robust standard set of database queries and processing operations is available. Larger grids use more-advanced, specialized storage mechanisms to facilitate data compression and virtual paging of fully configured grid layers. But the move to a relational database structure is far more important than simply corralling mega-gulps of map values. It provides a "universal database management system (DBMS) key" that can link seemingly disparate database tables. The process is similar to a date/time stamp, except the "where information" provides a spatial context for joining datasets. Demographic records can be linked to resource records that, in turn, can be linked to business records, health records, etc.; all sharing a common lat/lon address. All that's necessary is to tag the data with lat/lon coordinates ("where" collected) just as done with date/time ("when" collected)—not a problem with the ubiquitous availability and increasing precision of GPS that puts a real-time tool for handling detailed spatial data right in your pocket. In today's technology, most GPS-enabled smartphones are accurate to a few meters, and specialized data-collection devices are precise to a few centimeters. Spatially Implicit After the data are stamped with their "spatial key," they can be linked to any other database table with spatially tagged records, without the explicit storage of a fully expanded grid layer. All the spatial relation- ships are implicit in the relative positioning of the lat/lon coordinates. For example, a selection operation might identify all health records jointly occurring within 0.5 kilome- ters of locations that have high lead concentrations in the topsoil. Or it can find all customer records within five miles of a store; better yet, within a 10- minute drive from a store. Geotechnology truly is a mega-technology that will forever change how we perceive and process spatial information. Gone are the days of manual Figure 2. Within a relational database, lat/lon forms a universal DBMS key for joining tables. measurements and specialized data formats that have driven our mapping legacy. Lat/lon coordinates move from crosshairs for precise navigation (intersecting lines) to a continuous matrix of spaces covering the globe for consistent data storage (grid cells). The recognition of a universal spatial key coupled with spatial analysis/statistics procedures and GPS/remote-sensing technologies provides a firm foothold "to boldly go where no map has gone before." Author's Notes: "Beyond Mapping" columns for December 2004-March 2005, April-May 2012 and September 2012 are compiled into Topic 24, "Overview of Spatial Analysis and Statistics," in the online book, Beyond Mapping III, at www. Also see Topic 28, "Spatial Data Mining in Geo-Business," for more information on "The Universal Key for Unlocking GIS' Full Potential" (GeoWorld, October 2011, page 10). OCTOBER 2O12 / WWW . GEOPLA CE . CO M 11

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