# 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

# 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

# Statistical Problem Solving in Geography is now in print.

I am happy to announce that my book Statistical Problem Solving in Geography is now in print, and available from Waveland Press.  The book was unveiled at this year’s Association of American Geographers meeting in Tampa, Florida on April 9, 2014 and was sold out on the first day.  The picture shown here is the last copy that was purchased by one of my former students.

This book was three years in the making.  When Chapman McGrew and Chuck Monroe, the authors of the first and second editions, approached me to help them write a third edition, we  envisioned a fresh coat of paint on an already well written book.  The plan was to update the out-dated examples from the 1980s and 1990s, and wrap the whole thing up in about 5 months.  Along the way, we had so much fun introducing new ideas that we decided to burn the entire thing to the ground and rewrite the book from scratch.   That was the best decision we ever made, as the book turned out better than we ever imagined.

In writing the book we made certain specific choices:

1.  Make it about geography:  Most statistics in geography books have very little geography in them.  And, some of the leading books have less than 5 maps in the book!!  This book is actually a geography book, and contains almost 50 map examples.  We knew that geography students are often intimidated by mathematical concepts, so we wanted to make sure that all our examples were geographically based.

2.  Make it understandable:  I never liked books that drove home the point that the author was way smarter than I was.  I like books written for my level – a novice in most things.  The real key in writing an undergraduate text book is not to impress everyone with how smart you are, but to make your goal to help students actually understand the material. Keeping the examples geography-based certainly helped in making the material understandable.  But we also modified our writing style to make it more conversational in tone.  Also, the best way to understand how the statistical examples work is to provide fully worked examples.

3.  Make it affordable:  We were always bothered by the high cost of textbooks.  In reviewing the royalty guidelines for textbook writing I sort of see why books are so expensive – the authors make virtually no money on the book!!  Yes, it is a labor of love.  But, one way to get a little more money out of the publisher is to charge more for the book.  We decided not to do that.  We also decided to produce a black and white, soft bound book so that the price can be kept under \$50.  My hope is that this is not only the best undergraduate text in statistics and geography, but is also the lowest priced.

4.  Make it modern: We wanted this book to include modern techniques, and modern examples.  In presenting the material, we included recent data from topics like precipitation, flooding, wildfires, immigration, business, piracy, epidemiology, agriculture, and community planning.  We also presented the data within the framework of GIS, since most geographers are making greater use of GIS technology.

I hope you get an opportunity to check out the book – I am hoping that it leads to undergraduate geographers being less intimidated by quantitative analysis in geography, and that they see the benefit of using statistics within a geographic paradigm.