SQL Examples for Statistical Problem Solving in Geography

I have spent the last few years advocating the benefits of SQL, and in particular spatial constructs in SQL for solving geographic problems.  Why all the fuss?  Quite simply, I think the use of spatial constructs in SQL is one of the most powerful tools available to geographers.  Last year, I taught a couple of workshops entitled Spatial SQL: A Language for Geographers.  These workshops were well received, and most of those in attendance were unaware of the power that spatial SQL has to offer – and why would they know, the GIS industry does not really talk about this.

Yes, we like to say that spatial  is special, but what if for once we saw spatial as just another data type.  DBMS guys don’t go around saying floating point is special, or date fields are special.  Once we start treating spatial data as another data type, we can open up all kinds of potential.  The number of DBMS vendors offering spatial constructs within their software is growing, and the need for spatial solutions continue to increase outside of the traditional GIS market.  Quite frankly, I think our use of GIS Wizards and templates have limited our ability to play a significant role in GIS applications for large database implementations.

Over the next few months, I will be providing worked examples of spatial SQL for solving geographic problems.  I am going to work through statistical examples from my book Statistical Problem Solving in Geography.

In the meantime, to learn a little bit about what spatial SQL is capable of, you can view a webcast I made nearly 10 years ago when I was at Cornell University.

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