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A Good Introduction To Geospatial Data Analysis

Jeff at Vector One asks, “Why is there so little geospatial analysis?” I can think of any number of possible reasons:

  • People aren’t aware of it, or what it can do; for some people, geographic analysis ends when you put a point on a map
  • It can involve advanced analytical and statistical techniques that are challenging to learn
  • Commercial software can be expensive, and difficult to learn; ArcGIS’s Spatial Analyst and Geostatistical Analyst extensions list at $2500 apiece.

While there are many freeware programs available for geospatial data analysis (I’ll post on some of them on the future), there’s one program I’d select as the best choice to address the above issues: GeoDA, spearheaded by Luc Anselin at Arizona State University. And that’s as much for its teaching materials and documentation as it is for its capabilities. There’s a 100+-page user’s guide, a 200+-page workbook that’s a mini-course on analyzing spatial data, multiple publications, dozens of sample datasets, even a QuickTime movie. It’s by no means complete; for example, there’s no geostatistical interpolation capabilities in this program (e.g. variograms, Kriging). But just by itself, it’s a great introduction to many techniques for analyzing spatial data correlation. It’s only for Windows now, but they’re working on a cross-platform open source port for Windows, Linux and Mac; no word on when that might become available.

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6 Responses to “A Good Introduction To Geospatial Data Analysis”

  1. 1 Peter

    Thx for your blog. I read it every day via feed. always good news.

    Greetings, Peter

  2. 2 Thomas

    Another happy reader reporting in!



  3. 3 Andrés

    Why don’t you try gvSIG. It’s a Spanish free open software developed by Jaume I University and supported by Valencia’s Government.

  4. 4 askan

    Hi Leszek

    Another gem on your blog. You are worth every donation possible. Ans I am happy that you want to attack geospatial analysis.



  5. 5 Leszek Pawlowicz

    Thanks for the comment, Andres. I’ve mentioned gvSIG briefly on this website before:

    but I’ve been meaning to look at it in more detail for quite a while. Of all the JUMP derivatives I’ve seen, it has the most promise.

  6. 6 Yiyi

    Thank you. It’s valuable resource for me and my students.

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