# Spatial is Not Special – Central Feature

This post is part of a series entitled Spatial is not Special, where I will illustrate how spatial constructs in SQL provide us with a rich toolset for geographers doing spatial analysis.  To illustrate these concepts, I will be showing examples from my book Statistical Problem Solving in Geography.  Even though PostGRES, SQLServer, MySQL, spatialite, and Oracle all support spatial SQL, these examples will be presented using Manifold GIS.  The example dataset is a Manifold 8.0 .map file and can be found here.

Our previous post showed how to extend the mean center of a geographic dataset to incorporate the weighted mean center using SQL.  Today’s post examines the SQL code necessary to generate the central feature for a geographic data set.  Recall from Statistical Problem Solving in Geography (third edition), the formula and computation of the Central Point. Continue reading

# Spatial is Not Special – Weighted Mean Center

This post is part of a series entitled Spatial is not Special, where I will illustrate how spatial constructs in SQL provide us with a rich toolset for geographers doing spatial analysis.  To illustrate these concepts, I will be showing examples from my bookStatistical Problem Solving in Geography.  Even though PostGRES, SQLServer, MySQL, spatialite, and Oracle all support spatial SQL, these examples will be presented using Manifold GIS.  The example dataset is a Manifold 8.0 .map file and can be found here.

In our previous post we saw how easy it was to compute the mean center of a geographic dataset with SQL.  Today’s post examines the SQL code necessary to generate the weighted mean center for a geographic data set.  Recall from Statistical Problem Solving in Geography (third edition),  the formula and computation of weighted mean center and the 7 point data set used. Continue reading

# Spatial is not Special – Mean Center

This post is part of a series entitled Spatial is not Special, where I will illustrate how spatial constructs in SQL provide us with a rich toolset for geographers doing spatial analysis.  To illustrate these concepts, I will be showing examples from my book Statistical Problem Solving in Geography.  Even though PostGRES, SQLServer, MySQL, spatialite, and Oracle all support spatial SQL, these examples will be presented using Manifold GIS.  The example dataset is a Manifold 8.0 .map file and can be found here.

Today’s post examines the SQL code necessary to generate the mean center for a geographic data set.  Recall from Statistical Problem Solving in Geography (third edition),  the formula for mean center and the 7 point data set used. Continue reading

# 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. Continue reading