Tag: GIS

How I created a map of Illinois Amtrak routes in TileMill in less than 30 minutes

October 22, 2012 / / 2 Comments

This interactive map was created for a Grid Chicago article to show the cities and Amtrak routes mentioned. Click and drag it around or hover your mouse on the red train station markers. 

Want to create a map like that and publish it on your own website? It’s easy. I’ll show you how to do it in less than 30 minutes. First, download the following files:

All shapefiles are from the United States Department of Transportation, Bureau of Transportation Statistics’s National Transportation Atlas 2012 edition except for Illinois places, which comes from the Census Bureau’s TIGER project.

At the end of this tutorial, you’ll have a good introduction on how to find geographic data, build a map with TileMill, style the map, and publish it for the public. Your map will not look like mine as this tutorial doesn’t describe how to add labels or use the hover/info feature.

Tutorial to make Amtrak Illinois map

  1. Unzip the four ZIP files you downloaded and move their contents into a folder, like /Documents/GIS/Amtrak Illinois/shapefiles. This is your project folder.
  2. Install TileMill and open it.
  3. Set up a project. In the Projects pane, click “New Project”. In the filename field, title it “amtrak_illinois”. Ensure that the checkbox next to “Default data” is checked – this shows a world map and helps you get your bearings (but it’s not absolutely necessary).
  4. Get familiar with TileMill’s layout. Your new project will open with the map on the left side and your Carto style code on the right side. There are four buttons aligning the left edge of your map. From top to bottom they are: Templates, Font list, Carto guide, and Layers.
  5. Add a layer. We’re going to add the four shapefile layers you downloaded. Click the “Layers” button and then click “Add layer”. In the ID field, type in “amtrak_routes”. For Datasource, browse to your project folder and find “amtrak.shp” – this file has the Amtrak route lines. Then click “Done”. Click “Save & Style”.
  6. Style that layer. When you click “Save & Style” after adding a layer, your attention will be called to the Carto style code on the right side of TileMill. A section of code with the “amtrak_routes” #selector will have been inserted with some default colors and styles. If you know CSS, you will be familiar with how to change the Amtrak routes line styles. Change the “line-color” to “#000”. After “line-color”, add a new line and insert “line-opacity: 0.5;”. This will add some transparency to the line. Press the “Save” button above the code.
  7. Add remaining layers. Repeat Step 5 and add 3 more layers: “amtrk_sta.shp” (ID field: “amtrak_stations”), “state.shp” (ID field: “states”), and “tl_2012_17_place.shp” (ID field: “illinois_cities”).
  8. Hide bus stations. The Amtrak stations layer shows bus and ferry stations as part of Amtrak’s Thruway connections. You probably don’t want to show these. In your Carto style code, rename the #selector from “#amtrak_stations” to “#amtrak_stations[STNTYPE=’RAIL’]”. That makes the following style code only apply to stations with the “rail” type. Since there’s no style definition for things that aren’t of that type, they won’t appear.

Screenshot of my map.

Prepare your map for uploading

TileMill has many exporting options. You can save it as MBTiles and publish the map for free using MapBox (TileMill’s parent), or you can export it as image files (but it won’t be interactive), or you can display the map using the Leaflet JavaScript map library (which I use for the Chicago Bike Map app). This tutorial will explain how to export MBTiles and upload to MapBox, the server I’m using to display the map at the top of this page.

  1. Change project settings. To upload to MapBox, you’ll have to export your project as MBTiles, a proprietary format. Click the “Export” button above your Carto style code and click “MBTiles”. You’ll be asked to provide a name, description, attribution, and version. Input appropriate text for all but version.
  2. Adjust the zoom levels. Adjust the number of zoom levels you want (the more you have the longer it takes to export and upload your project, and you might exceed MapBox’s free 50 MB account limit). My map has zoom levels 8-11.
  3. Adjust the bounds. You’ll then want to draw your bounds: how much of the map’s geographic extents you want to export. Zoom to a level where you can see the entire state of Illinois in your map. Hold down the Shift key and drag a box around the state, plus a buffer (so viewers don’t fall of your map when they pan to the edges).
  4. Export your map. Click Export and watch the progress! On a four-year-old MacBook it took less than one minute to export the project.
  5. Bring the export to your project folder. When export finishes, click the “Save” button and browse to your project folder. Click the file browser’s save button.
  6. Upload to MapBox. Login to MapBox’s website and click “Upload Layer”. Browse to your project folder, select the .mbtiles folder, and click “Upload file”. Upon a successful upload, your map will display.
  7. Embed it in your website. Click the “Share” button in the upper left corner of your map and copy the embed code. Paste this into the HTML source code of a webpage (or in a WordPress post) and save that (I’m not going to provide instructions on how to do that).

Now you know how to find geographic data, build a custom map using the TileMill application, begin to understand how to style it, and embed your map for the public on a website or blog.

N.B. I was originally going to use QGIS to build a map and then publish a static image before I realized that TileMill + MapBox (the website) can build a map but publish an interactive feature instead of a static image. I’m happy I went that route. However, I did use QGIS to verify the data and even create a new shapefile of just a few of the key train stations on the Lincoln Service (the centerpiece of my Grid Chicago article).

Crashes by bike or by foot at different intersections

January 16, 2012 / / 0 Comments

While working on a private web application that I call Chicago Crash Browser, I added some code to show the share of pedestrian and pedalcyclist crashes. The site offers users (sorry I don’t have a web server that can make it public) a list of the “Top 10” intersections in terms of bike crash frequency (that’s bike+auto crash). You can click on the intersection and a list will populate showing all the pedestrian and pedalcyclist crashes there, sorted by date. At the bottom of the list is a simple sentence that tells what percentage pedestrian and pedalcyclists made up at that intersection.

I’m still developing ideas on how this information may be useful, and what it’s saying about the intersection or the people using it.

Let me tell you about a few:

Milwaukee Avenue and Ogden Avenue

I mentioned in my article Initial intersection crash analysis for Milwaukee Avenue that this intersection is the most bike crash-frequent.

23 crashes within 150 feet of the center, 2005-2010

82.61% bike crashes **

17.39% ped crashes.

Ashland Avenue and Division Street

28 crashes within 150 feet of the center, 2005-2010

46.43% bike crashes

53.57% ped crashes **

Milwaukee, North and Damen Avenues

46 crashes within 150 feet of the center, 2005-2010

39.13% bike crashes

60.87% ped crashes **

Halsted Street, Lincoln and Fullerton Avenues

38 crashes within 150 feet of the center, 2005-2010

42.11% bike crashes

57.89% ped crashes **

Montrose Avenue and Marine Drive (Lake Shore Drive ramps)

11 crashes within 150 feet of the center, 2005-2010

90.91% bike crashes **

9.09% ped crashes

Why do you think some intersections have more of one kind of crash than the other?

People walking at Milwaukee-North-Damen.

The Chicago Crash Browser can be made public if I have a host that offers the PostgreSQL database. Do you have one to offer?

Are protected bike lanes going in the right places?

September 29, 2011 / / 0 Comments
Bike crash map of Ogden, Milwaukee, Chicago

Common bike-car crash locations in West Town. The bottom blue circle identifies Ogden/Milwaukee, where there is a yellow trap for northbound, left-turning motorists (from Milwaukee to Ogden) that makes them run into southbound bicyclists who have a green light.

My contribution to a discussion on The Chainlink, Are protected bike lanes going in the right places?

Kelvin, Milwaukee/Ogden/Chicago is the intersection along Milwaukee Avenue with the highest number of bicycle crashes. I created this table and map to show them, using data from 2007-2009.

The blue rings on the map are called, in GIS parlance, “buffers” and are circles used to select things (in this case, bike crashes) within a certain distance of the circle center. In this map I used 50 feet radius buffers (100 feet diameter). While this distance encompasses the intersection from center to all four curbs, it doesn’t encompass the crashes that happened just outside the buffer that were still most likely influenced by the intersection (like drivers’ turning movements).

I am working on a project with three friends to create a better map and “crash browser”. I mentioned it in the last story on Grid Chicago in this post. For this project, we are using 200 feet radius (400 feet diameter) buffers to ensure we encompass the entire intersection and the area in which it still has an effect. This also grabs the bike lane “pinch points”, places where a bike lane doesn’t start until 100-200 feet beyond the intersection.

I am also concerned with the strategy and approach CDOT is using to choose locations. It’s not transparent; at MBAC, CDOT said they were choosing locations “without controversy and that could be implemented quickly”.

Read more about Kinzie Street, Chicago’s first protected bike lane, and my other thoughts on protected bike lanes. 

How to upload shapefiles to Google Fusion Tables

September 25, 2011 / / 0 Comments

It is now possible to upload a shapefile (and its companion files SHX, PRJ, and DBF) to Google Fusion Tables (GFT).

Before we go any further, keep in mind that the application that does this will only process 100,000 rows. Additionally, GFT only gives each user 200 MB of storage (and they don’t tell you your current status, that I can see).

  1. Login to your Google account (at Gmail, or at GFT).
  2. Prepare your data. Ensure it has fewer than 100,000 rows.
  3. ZIP up your dataX.shp, dataX.shx, dataX.prj, and dataX.dbf. Use WinZip for Windows, or for Mac, right-click the selection of files and select “Compress 4 items”.
  4. Visit the Shape to Fusion website. You will have to authorize the web application to “grant access” to your GFT tables. It needs this access so that after the web application processes your data, it can insert it into GFT.
  5. If you want a Centroid Geometry column or a Simplified Geometry column added, click “Advanced Options” and check their checkboxes – see notes below for an explanation.
  6. Choose the file to upload and click Upload.
  7. Leave the window open until it says it has processed all of the rows. It will report “Processed Y rows and inserted Y rows”. You will be given a link to the GFT the web application created.

Sample Data

If you’re looking to give this a try and see results quickly, try some sample data from the City of Chicago data portal:

Notes

I had trouble many times while using Shape to Fusion in that after I chose the file to upload and clicked Upload, I had to grant access to the web application again and start over (choose the file and click Upload a second time).

Centroid Geometry – This creates a column with the geographic coordinates of the centroid in a polygon. It lists it in the original projection system. So if your projection is in feet, the value will be in feet. This is a function that can easily be performed in free and open source QGIS, where you can also reproject files to get latitude and longitude values (in WGS84 project, EPSG 4326). The centroid value is surrounded in the field by KML syntax “<Point><coordinates>X,Y</coordinates></Point>”.

Simplified Geometry – A geometry column is automatically created by the web application (or GFT, I’m not sure). This function will create a simpler version of that geometry, with fewer lines and vertices. It also creates columns to list the vertices count for the simple and regular geometry columns.

My essential QGIS plugins

April 18, 2011 / / 0 Comments

Plugins for QGIS I use most often.

All of these can be installed automatically by QGIS. Click on Plugins>Fetch Python Plugins. Then search for the plugin, click on its name, and click Install Plugin. Few plugins require a restart.

  • MMQGIS – Great for working with CSV files; also merges layers (even if they have differing attributes); has various other useful functions, including converting string data to float data. Has Voronoi diagram function (takes a long time to process).
  • fTools – Replicates some of the most basic geographic tools in ArcGIS, like Clip, Dissolve, and Reproject. Can also add X/Y values to point attribute tables that are missing them (if you want latitude/longitude, you must reproject into a coordinate reference system first, like WGS84 [EPSG: 4326]). Unfortunately, there’s little information on what each fTools function does. Below are descriptions:
    • Extract Nodes – Create a point at each intersection of vertices.
    • Basic Statistics – Generate arithmetic statistics for fields, same as statistics function in ArcGIS. Great for quickly understanding the extent of values in a field (especially numeric values), like mean, max, min, standard deviation, and number of unique values.
    • Nearest Neighbour Analysis – More details here.
    • Geoprocessing Tools>Dissolve – Combine features based on a shared attribute. For example, all features with an identical STREET_TYPE be combined into a single feature. For example, all “Avenues” will become one feature and all “Boulevards” will become a second feature. Only works on polygon layers.
    • Descrição em português
  • Table Manager
  • Open Layers – Embed Google, Yahoo, Bing, and OpenStreetMap layers in your map. See my example.