Undergraduate Geospatial Python Projects

earthballThis week my GIS Programming students presented their programming projects to ESRI. First, I cannot say enough to thank ESRI for taking time out of their schedule to meet with our students – the staff was helpful, encouraging, and provided great feedback to the students – what an honor it was to get their feedback.  I am so thankful to be a part of a GIS community that is so supportive of one another.

Now, this was a really special class of undergraduates – and some of them were part of that special group of students that presented their research at an undergraduate conference.  It was small, so we could do some really cool things.  In fact, in the middle of the semester, the students wrote a paper comparing the geocoding accuracies of Google Maps and the United States Census Bureau.

Things were going so well that I decided in lieu of a final exam, we expanded their final projects a little more, and arranged for the staff at ESRI Charlotte and ESRI Redlands to join us on a WebEx that included demonstrations and a code walk-through.  Below are each students’ presentation, and some of the Q&A from ESRI:

noahNoah Krach.  Noah is an amazing undergraduate.  Recently, we lost one of our graduate research associates, and Noah stepped in to provide technical support on a National Science Foundation project in Lake Victoria.  Without missing a beat, Noah was all over the project, and he used his time in my class to create an Arcpy tool to extract, translate, and load (ETL) gigabytes of Landsat imagery.  This tool does a lot, and I can’t even begin to describe all he did, you’ll simply have to watch and learn.

Check out his video, and you’ll see why we are so excited that Noah will be around for another semester.

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Caitlin Curry.  If you follow my blog, you’ve already met Caitlin.  She finished her summer internship I told you about, and during the middle of it, her boss wrote us to say what an excellent worker she was (he prefaced his email by saying he never does that, but was so impressed with Caitlin, he had to let us know).  We are impressed with Caitlin, too.  And, as I have now grown to expect, Caitlin did an amazing job with another ETL type tool using Arcpy, where she downloaded, unzipped, and processed earthquake data and critical infrastructure.

I did a lot of emergency response work with earthquakes in a previous life, and what Caitlin did here would have been so useful.  I think you will enjoy seeing how she integrated many different Python packages with Arcpy to provide an early warning application for emergency responders.  And just as a heads-up, Caitlin uses Python to download everything while the script is running – so you just give the script to a user and it works without any operator knowledge of the underlying data = really cool, and efficient.

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Matthew Bucklew.  After my first lecture this semester, Matt told me he built his own computer this summer – just for fun.  So, I knew he wasn’t your ordinary  geographer – he likes to try new things, and if something is done in a conventional way, Matt is going to try and be more innovative.  Matt created a great Arcpy application to locate renewable engery stations needed by automobiles.  His Python scripts use ArcGIS for analysis, but at the same time, seamlessly brings in the Google APIs to provide directions to the nearest locations.  For good measure, he also brings in other packages like heapq.

At the moment, Matt’s program works on a desktop, but his hope it to turn this application into a cloud based solution for use with mobile phones.  Keep an eye out for what Matt comes up with, and if you watch this, you’ll see it is an excellent tutorial on how to mash up bunches of Python packages with Arcpy.

jmJessica Molnar.  Like Caitlin, Jessica is another student you’ve seen before.  She’s got such a big heart, and is always looking for ways to apply GIS to humanitarian and ecological solutions.  In this project, Jessica created an Arcpy application to identify locations for community gardens in Baltimore City with special consideration for locations within food deserts, near churches and schools, and on suitable soils for growing food.  Jessica’s program also found those locations that were already owned by the City, but were vacant.  Let’s hope the City makes use of this to build a more beautiful Baltimore (BTW, Jessica wrote her program to work in any location in the State of Maryland, so any community can use this tool!).  I think Jessica may eventually roll this into a cloud based solution – hey Jessica, I think we found a project for graduate school!

 

jtJohn Tilghman.  John’s family owns an orthodontist practice, and John decided to use PostGRES/PostGIS along with a number of other different Python packages to perform market area analysis.  John integrated PostGRES, Google, and the Pygal libraries to create the first stages of a geodashboard to assess the effectiveness of marketing strategies, and other metrics.  In the video, you’ll also see how he created a distance decay algorithm in SQL to determine at what point customers drop off from visiting the practice.  With just a little bit of information (addresses and marketing strategies), John was able to extract a ton of business information – in fact, our guests from ESRI were surprised the John wasn’t already a business major!

This is an excellent presentation to watch for those of you who are interested in using Python with Open Source GIS – you’ll learn how to integrate FOSS4g and Python for a business analytics tool.

 

jyJosh Young.  Josh created an Arcpy script to assemble tons of location based data that might be useful for someone thinking about moving to a particular location.  Now, in Josh’s case, he chose location based data he deemed important for the neighborhood (download speeds, elementary school, crime statistics, distance to the downtown, etc.).  But ultimately, what Josh has shown us is how to create a template that integrates multiple Python packages and online data to provide very useful information.

It would be so easy to take Josh’s work and roll it into a site specific location-based analysis engine.  In fact, one of the people watching Josh’s presentation mentioned that he was moving, and saw how useful this could be for a community.  The best part of it is that Josh did it with all freely available online data for the State of Maryland, so any community can spin this up into a cloud-based solution.

 

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Robbie Stancil.  Robbie is our only non-geography major.  You’ve met him before when he worked with me on a National Science Foundation project to use Spatial Hadoop.  Like John, Robbie’s project used Postgres/PostGIS and the Google API to do something quite interesting: he created a mesh of points over community to determine how far the Google API will search in order to find a property address, and compared the concave hull of each series of points for an address to the actual property parcel.  This project got us thinking about some very creative uses – you’ll have to watch it until the end to see the interesting things we came up with.

 

Again, I have to give a huge shout out to the ESRI staff – they were wonderful guests, and really excellent mentors during the Q&A. As these students get ready to graduate in May, I know they will make excellent employees or graduate students – the future is really bright for them. If you are in academia, I hope that you are inspired to expect the very best of your students as I do, and you’ll be so pleased to see what they are capable of doing.

want to learn how to program geospatial solutions like these students? Check out the geospatial courses at gisadvisor.com.   

2 thoughts on “Undergraduate Geospatial Python Projects

  1. Pingback: Workshops at the Maryland Geospatial Conference | gisadvising

  2. Pingback: Great work by my undergraduates, Again! | gisadvising

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