Tag: Software

Trying out uDig, a free, multi-platform GIS application

ArcGIS is the standard in geographic information system applications. I don’t like that it’s expensive, unwieldy to install and update, and its user interface is stymying and slow*. I also use Mac OS X most of the time and ArcGIS is not available for Mac. It doesn’t have to be the standard.

I’ve tried my hand at Cartographica and QGIS. I really like QGIS because there’re many plugins, it’s open source, there’s a diverse community supporting it, and best of all, it’s free. I’ve written about Cartographica once – I’m not a fan right now.

My project

  • The data: Bicycle crashes in the City of Chicago as reported to IDOT for 2007-2009
  • Goal: Publish an interactive map of this data using Google Fusion Tables and its instant mapping feature.
  • Visualizing it: Added streets (prepared beforehand to exclude highways), water features, and city boundary (get that here)
  • Process: Combine bike crash data; reproject to WGS84 for Google; remove extraneous information; add latitude/longitude coordinates; export as CSV; upload to Google Fusion Tables; map it!
  • View the final product

Trying out uDig

In reaching my goal I had a task that I couldn’t figure out how to complete with QGIS: I needed to combine three shapefiles with identical table schemes into one shapefile – this one shapefile would eventually be published as one map. The join feature in fTools wasn’t working so I looked for a new solution, uDig, or “User-friendly Desktop Internet GIS.”

The solution was very easy. Highlight all the records in the attribute table of one shapefile, click Edit>Copy, then select the destination table and click Edit>Paste. The new records were added within a couple seconds. I could then bring this data back into QGIS to finish the process (outlined above under Project). I did use fTools later in the process to add lat/long coordinates to my single shapefile.

After adding more data to better visualize the crashes in Chicago, I noticed that uDig renders maps to look smoother and slightly prettier than QGIS or ArcGIS. See the screenshot below.

A screenshot of the three bicycle crash datasets (2007, 2008, 2009) with the visualization data added.

The end product: three years of police reported bicycle crashes in the City of Chicago on an interactive map powered by Google Fusion Tables, another product in Google’s arsenal of GIS for the poor man. View the final product.

*I haven’t used ArcGIS version 10 yet, which I see and read has an improved user interface; it’s unclear to me and other users if the program’s been updated to take advantage of multi-core processors. ESRI has a roundabout way of describing their support.

How to convert GTFS to GIS shapefiles and KML

This tutorial will teach how you to convert any transit agency’s General Transit Feed Specification (GTFS) data into ESRI ArcGIS-compatible shapefiles (.shp), KML, or XML. This is simple to do because GTFS data is essentially a collection of CSV (comma separated values) text files (really, really large text files).

Note: I don’t know how to do the reverse, converting shapefiles or other geodata into GTFS data. I’m not sure if this is possible and I’m still investigating it. If you have tips, let me know.

Converting GTFS to GIS shapefiles

Instructions require the use of ArcGIS (Windows only) and a free plugin called ET GeoWizards GIS for any version of ArcGIS. I do not have instructions for Mac users at this time.

I wrote these instructions while converting the Chicago Transit Authority’s GTFS files into shapefiles based on a reader’s request. “Field names” are quoted and layer names are italicized.

  1. Download the GTFS data you want. Find data from agencies around the world (although not many from Europe) on GTFS Data Exchange.
  2. Import into ArcGIS the shapes.txt file using Tools>Add XY Data. Specify Y=lat and X=lon
  3. Using ET GeoWizards GIS tools, in the Convert tab, convert the points shapefile to polyline.
  4. Select the shapes layer in the wizard, then create a destination file. Click Next.
  5. Select the “shape_id” field
  6. Click the checkbox next to Order and select the field “shape_pt_sequence” and click Finish.
  7. Depending on the number of records (the CTA has 466,000 shapes), it may take a while.
  8. The new shapefile will be added to your Table of Contents and appear in your map.
  9. Import the trips.txt and routes.txt files. Inspect them for any NULL values in the “route_id” field. You will be using this field to join the routes and trips table. It may be a case that ArcGIS imported them incorrectly; the text files will show the correct data. If NULL values appear, follow steps 10 and 11 and continue. If not, follow steps 10 and 12 and continue. This happens because ArcGIS inspected some of the data and determined they were integers and ignored text. However, this is not the case.
  10. Export the text files as DBF files so that ArcGIS operates on them better. Then remove the text files from the Table of Contents.
  11. (Only if NULL values appear) Go into editing mode and fix the NULL values you noticed in step 9. You may have to make a new column with a more forgiving data type (string) and then copy the “route_id” column into the new column. Then continue to step 12.
  12. Join routes and trips based on the field “route_id” – export as trips_routes.dbf
  13. Add a new column to shapes.shp called “shape_id2”, with data type double 18, 11. This is so we can perform step 14. Use the field calculator to copy the values from “shape_id” (also known as ET_ID) to “shape_id2”
  14. Join routes_trips with shapes into routes_poly based on the field “shape_id” (and “shape_id2”)
  15. Dissolve routes_poly on “route_id.” Make sure all selections are cleared. Use statistics/summary fields: “route_long,” “route_url.” Save as routes_diss.shp
  16. Inspect the new shapefile to ensure it was created correctly. You may notice that some bus routes don’t have names. Since these routes are well documented on the CTA website, I’m not going to fill in their names.

Click on the screenshot to see various steps in the tutorials.

Converting GTFS to KML

After you have it in shapefile form, converting to KML is easy – follow these instructions for using QGIS. Or if you want to skip the shapefile-creation process (quite involved!), you can use KMLWriter, a Python script. Also, I think the latest version of ArcGIS has built-in KML exporting.

Converting GTFS to XML

If you want to convert the GTFS data (which are essentially comma-separated value – CSV – files) to XML, that’s easier and you can avoid using GIS programs.

  • First try Mr. Data Converter (very user friendly).
  • If that doesn’t work, try this website form on Creativyst. I tested it by converting the CTA’s smallest GTFS table, frequencies.txt, and it worked properly. However, it has a data size limit. (User friendly.)
  • Next try csv2xml, a command line tool. (Not user friendly.)
  • You can also use Microsoft Excel, but read these tips and caveats first. (I haven’t found a Microsoft application I like or think is user friendly.)

How to geocode a single address in QGIS

Since the last time I wrote about how to use BatchGeocode.com to perform pseudo-geocoding tasks in QGIS, there have been considerable improvements in the multi-platform, free, and open source GIS software. Now, geocoding (turning addresses into coordinates) is more automatic, albeit difficult to setup. (Okay, this has been around June 2009 and I just found out about it in October 2010.)

Once you install all the components, you’ll never have to do this again.

This method can only geocode one address at a time, but it will geocode all of the addresses into a single shapefile.

  1. Download QGIS.
  2. Download and install Python SetupTools. This includes the easy_install function that will download a necessary Python script, simplejson. On Mac you will have to use the Terminal (Applications>Utilities). Email me if you run into problems.
  3. Install simplejson. In the command line (Terminal for Mac; in Windows press Start>Run>”cmd”>Enter), type “easy_install simplejson”.
  4. Download the GeoCode plugin by Alessandro Pasotti via QGIS>Plugins>Fetch Python Plugins. You may have to load additional repositories to see it.
  5. Install geopy. In the command line (like step 3), type “easy_install geopy”.
  6. Specify your project’s projection in File>Project Properties.
  7. Get a Google Maps API key and tell the GeoCode plugin about it (QGIS>Plugins>GeoCode>Settings). You will need a Google account. If you don’t have your own domain name, you can just enter “google.com” when it asks for your domain.
  8. Geocode your first address by clicking on Plugins>GeoCode>Geocode. Type the full address (e.g. 121 N LaSalle Street, Chicago, IL for City Hall).
  9. The geocoded address will then appear in your Layers list as its own shapefile. All addresses geocoded (or reverse geocoded) in this project will appear in the same layer (therefore same attribute table).

Once you install all the components, you’ll never have to do this again. Geocoding will be available each and every time you use QGIS in the future on that workstation.


  • When you’re done geocoding,  save your results as a shapefile (right click the layer and click “Save as shapefile”). Twice I’ve lost my results after saving the project and quitting QGIS. When I reopened the project, the results layer was still listed, but contained no data.
  • Add a “name” column to the GeoCoding Plugin Results layer’s attribute table (toggle editing first). You can then type in the name of the building or destination at the address you geocoded. Edit the layer’s properties to have that name appear as a label for the point.

A map I made with QGIS showing three geocoded points of interest in Chicago. Data from City of Chicago’s GIS team.


Trying out new GIS software

I want to draw 50 and 120 feet buffers around the points of store entrances to show where bike parking should and shouldn’t be installed. I want to follow this example:

walgreens with bike parking buffers

Aerial photo of a Tucson, Arizona, Walgreens showing the location of existing bike parking and two buffers (50 and 120 feet) where proposed city rules would allow bike parking. I advocate for ratifying the 50 feet rule, which I’ve discussed on this blog and elsewhere many times.

I want to do this easily and accurately, so I will use GIS software to create a “buffer.” I use QGIS occasionally, but I want to try out other Mac-friendly applications. I’m getting my orthoimagery (geometrically corrected aerial photography) from the United States Geological Survey (USGS) using a web protocol called Web Map Server. I’m trying:

  • Cartographica, $495, with free trial license.
  • uDig, completely free software. UPDATE: I have had NO success getting any data to load from a WMS connection into uDig. I would like to understand why. Cartographica can obtain some of the WMS-stored data I want, although it messes up often.

I’m having success with neither – both are having issues downloading or maintaining a connection to the USGS orthoimagery. In one case, Cartographica trims the Bing Maps imagery to match the extent of my other objects (the buffer). In another case, it won’t even download the USGS imagery (and gives no indication that anything is happening). uDig hasn’t been able to download anything so far – I hope it’s asking for the current extent, instead of all data because it’s taking a looong time to do anything (so long that I just quit in the  middle of it).

This screenshot shows how to add new WMS connections to Cartographica.

UPDATE: I did it! I successfully used Cartographica (and the integrated Bing Maps) to create this drawing that shows the current (abysmal) bike parking at a Chicago Home Depot outside the 50 feet line.

Google Maps and Earth is the poor man’s GIS

For over four years, Google’s geography products have become the most popular geographic information systems on the Earth (no, the earth). Google is now as much a platform of GIS for computers and users as ESRI, the number one GIS software maker.

To continue its corporate goal of organizing the world’s information, Google has made sure to also organize the world’s (and other realms) geographic information.

Google’s free tools and products manipulate, map, reproduce and analyze geographic information:

  • Maps – the simplest source of satellite imagery for the public, although Microsoft’s TerraServer was probably first
  • Street View
  • Transit – including travel directions for trips on Transit
  • Ocean
  • Earth desktop software – includes Moon, Mars, Sky
  • My Maps
  • Yellow pages-style business listings
  • Driving and Walking Directions – including automobile traffic overlay
  • Keyhole Markup Language (KML) – a file format based on XML that allows for the easy sharing and portability of data about locations. I wrote about it here.
  • Maps API – this allows developers to include maps in their own applications and websites as well as build features on top of maps

These applications now allow anyone in the world with an internet connection* and a computer to start thinking about the world and neighborhood in which they live in terms of space, distance, the environment, land use, and most important of all the relationships between real life places and these greater themes. But not only will these instruments influence the thinking of individuals and the groups to which they belong, but they will give people tools to create.

What have people created with Google’s GIS tools?

I created a map that shows the locations of open grated metal bridges on bikeways (featured in the bike map) in Chicago. This is important to bicyclists because open grated metal bridges can be hazardous to them, especially those with high centers of gravity or narrow tires on their bikes. Bicyclists will most often encounter these bridges on trips into and out of the Central Business District. This map will help bicyclists find routes that avoid these bridges. Precipitation exacerbates the danger, especially if it’s actively raining, or snow isn’t melting.

UPDATE 12-03-10: I was looking for information on an upcoming Chicago Cyclocross meet and I found a great example of using the tools Google has created for everyone. See a screenshot of the map below:

I’m posting this image to show how easy it is to create a map that tells a story. The story here is a guide on how to be a participant or spectator at the meet. It points out places where people can park, cannot park, and where the restrooms are in relation to parking or the race course. See the full map.

What have you created? Leave a comment below.

Evolution of Google’s GIS toolbox

I believe that Google will continue to expand its array of GIS-related applications, and also expand their existing ones. I would like to see them create new connections between the applications they’ve already created. For example:

  • Google can mimic the attribute table essential in desktop GIS software (like ESRI’s ArcGIS, qGIS, or GRASS) by integrating their Docs web application with My Maps. I want to save my information in a Google Docs spreadsheet (either inputted directly online or uploaded from my computer), then create a custom map and assign a location to each of the records in my spreadsheet. Then, using tools shared between Docs and My Maps, I can automate the creation of colored points and lines for the records based on categories or numbers in my spreadsheet, much like the classification and symbology tools of desktop GIS software. For example, on my “open grated metal bridges” custom map discussed above, I want to create a spreadsheet with a column that has a yes or no value to the question, “Is the bridge treated?” All records with “yes” will have green dots, and all “no” values will have blue dots.
  • The reverse situation could also be made possible by an integration between My Maps and Google Docs. Let’s say I’m a clerk at my church and I need to group the congregants into geographically close clusters for purposes of assigning community service work. I’ve inputted all of their addresses into My Maps and added a point for every house. There’re only 40 houses on the map and I can see see about 5 clusters (to keep it simple I won’t introduce arithmetic means of finding clusters). I use a selection lasso in My Maps and select the points in my first cluster. Using a new Classify function I label these points part of Cluster 1 and color them purple – I also assign Cluster 1 to work at the nearest park. I continue for the remaining four clusters, assigning each cluster to help clean a different park. Once I’ve completed grouping the houses, I tell My Maps to generate for me a spreadsheet that lists the names and phone numbers and clean up time for all the congregants. Now I can quickly call everyone in Cluster 1 and give them their community service assignment which is convenient to where they live.
  • Google should open up its many data layers. Google has many data layers in its table of contents: They recently added real estate data, but they also have the locations of transit stations and bus stops (including timetables and route information), the addresses and phone numbers of businesses (like the Yellow Pages), as well as terrain in some cases and bike trails in others. If the data in these layers were open, map users could perform some basic analysis like counting the number of check cashing businesses within 1 mile for a study of banking behavior in low-income neighborhoods. Or a map users could find the gain in elevation on a bike trail over 4 miles to determine their ride’s difficulty. Another map user could use the transit information to calculate the level of bus service in a neighborhood by counting the number of stops available and the number of buses scheduled.

I’ll have to figure out a way Google can extract revenue from these features if I want to convince Google to produce them, but sometimes the company builds products and features before it figures out how to make money.