Category: Maps

Chicago’s massive parking footprint – as measured on December 30, 2022

It’s been three years since I last measured how much of Chicago’s land area is occupied by parking lots and parking garages. On December 25, 2019, using data drawn into OpenStreetMap by volunteers including myself, 2.5 percent of Chicago was for car parking.

Based on additional data since then, the land area of Chicago occupied by already-mapped parking lots and garages is 176,973,866.57 square feet, or about 2.7 percent of Chicago’s area.

This means that 0.52 additional square miles have been drawn into OpenStreetMap. If it hasn’t been drawn there, we can’t measure it. This means this number is a *minimum* of the land area devoted to car parking in Chicago.

Between 2019 and 2022, 173 more of these parking lots were drawn into OpenStreetMap in Chicago. There are still so many more parking areas that are not mapped!

That converts to:

  • 4,063.32 acres
  • 7.08 mi^2 (square miles)
  • 15.93km^2 (square kilometers)
  • 2.7% area of Chicago is parking (Chicago’s land area is ~589.56 km^2 )

There are some future parking -> building conversions coming soon. The buildings will be providing parking, but it will be integrated into a mixed-use development. The parking lot in the image, for example, is slated to become an office tower.

Chicago Crash Browser updates with stats, filters, and news article links

Today I’m adding a bunch of new features to the Chicago Crash Browser, which lives on Chicago Cityscape.

But first…special access is no longer required. Anyone can create a free Cityscape account and access the map. However, only those with special access or a Cityscape Real Estate Pro account will be able to download the data.

Five new features include:

  • Statistics that update weekly to summarize what happened in the past week: the number of crashes, the number of people killed in crashes, and the number of people with the two worst tiers of injuries. The statistics are viewable to everyone, including those without access to the crash browser.
screenshot of the new weekly statistics
The statistics will update every Sunday. The numbers may change throughout the week as Chicago police officers upload crash reports.
  • For data users, the crash record ID is viewable. The crash record ID links details about the same crash across the Chicago data portal’s three tables: Crashes, Vehicles, and People. My Chicago Crash Browser is currently only using the Crashes table. Click on the “More details” arrow in the first table column.
screenshot of the data table showing the crash record ID revealed.
The crash record ID is hidden by default but can be exposed. Use this ID to locate details in the data portal’s Vehicles and People tables.
  • Filter crashes by location. There are currently two location filters: (1) on a “Pedestrian Street” (a zoning designation to, over time, reduce the prevalence of car-oriented land uses and improve building design to make them more appealing to walk next to); (2) within one block of a CTA or Metra station, important places where people commonly walk to. Select a filter’s radio button and then click “Apply filters”.
  • Filter crashes by availability of a news article or a note. I intend to attach news articles to every crash where a pedestrian or bicyclist was killed (the majority of these will be to Streetsblog Chicago articles, where I am still “editor at large”. Notes will include explanations about data changes [1] (the “map editor” mentioned in some of the notes is me) and victims’ names.
screenshot of the two types of filters

After choosing a filter’s radio button click “Apply filters” and the map and data table will update.
  • Filter by hit and run status. If the officer filling out the crash report marked it as a hit and run crash, you can filter by choosing “Yes” in the options list. “No” is another option, as is “not recorded”, which means the officer didn’t select yes or no.
  • Search by address. Use the search bar inside the map view to center the map and show crashes that occurred within one block (660 feet) of that point. The default is one block and users can increase that amount using the dropdown menu in the filter.
screenshot of the map after the search by address function has been used
Use the search bar within the map view to show crashes near a specific address in Chicago.


[1] The most common data change as of this writing is when a crash’s “most severe injury” is upgraded from non-fatal to fatal, but the crash report in the city’s data portal does not receive that update. This data pipeline/publishing issue is described in the browser’s “Crash data notes” section.

The “map editor” (me) will change a crash’s “most severe injury” to fatal to ensure it appears when someone filters for fatal crashes. This change to the data will be noted.

How to visualize the density of point data in a grid

A common way to show the distribution of places (like grocery stores) is to use a heat map. The map will appear “hotter” where there are many grocery stores and “colder” where there are few grocery stores. This kind of map can be useful to show gaps in distribution or a neighborhood that has a lot of grocery stores.

One issue with that kind of heat map is that the coverage areas change their shape and color if you zoom in, since the algorithm that clusters or determines what’s “nearby” or dense has fewer locations to analyze.

I prefer to use grids in the shape of square tiles, since Chicago is grid-oriented city and the vast majority of our streets and our routes move along east-west and north-south lines. The map above shows the location of subjects and topics of news articles in the Chicago Cityscape database.

I use PostGIS to set up most of my spatial data before visualizing it in QGIS.

This tutorial shows the two steps to using PostGIS to (1) create a grid based on an existing area (polygon), (2) assigning each point location to a tile in that grid and counting the number of locations in that tile.

If you don’t have PostGIS installed, you should install it if you work with spatial data a lot. It is much, much faster at performing most of the tasks you use QGIS or ArcGIS to perform. Both QGIS and ArcGIS can read and edit data stored in PostGIS.

Additionally, there is a function within QGIS that can create grids, and another function that can do comparisons by location and count/summarize, so all of this can be done without PostGIS.

For this tutorial, you will need a single polygon with which to create the grid. I used the boundary of the City of Chicago limits.

  1. Create a grid based on an existing area

1.a. Add a new function to PostGIS

To create a grid, you need a function that draws the tiles based on the polygon. I got this from The Spatial Database Advisor.

-- Create required type
  gcol  int4,
  grow  int4,
  geom geometry
-- Drop function is exists
-- Now create the function
CREATE OR REPLACE FUNCTION ST_RegularGrid(p_geometry   geometry,
                                          p_TileSizeX  NUMERIC,
                                          p_TileSizeY  NUMERIC,
                                          p_point      BOOLEAN DEFAULT TRUE)
   v_mbr   geometry;
   v_srid  int4;
   v_halfX NUMERIC := p_TileSizeX / 2.0;
   v_halfY NUMERIC := p_TileSizeY / 2.0;
   v_loCol int4;
   v_hiCol int4;
   v_loRow int4;
   v_hiRow int4;
   v_grid  T_Grid;
   IF ( p_geometry IS NULL ) THEN
   END IF;
   v_srid  := ST_SRID(p_geometry);
   v_mbr   := ST_Envelope(p_geometry);
   v_loCol := trunc((ST_XMIN(v_mbr) / p_TileSizeX)::NUMERIC );
   v_hiCol := CEIL( (ST_XMAX(v_mbr) / p_TileSizeX)::NUMERIC ) - 1;
   v_loRow := trunc((ST_YMIN(v_mbr) / p_TileSizeY)::NUMERIC );
   v_hiRow := CEIL( (ST_YMAX(v_mbr) / p_TileSizeY)::NUMERIC ) - 1;
   FOR v_col IN v_loCol..v_hiCol Loop
     FOR v_row IN v_loRow..v_hiRow Loop
         v_grid.gcol := v_col;
         v_grid.grow := v_row;
         IF ( p_point ) THEN
           v_grid.geom := ST_SetSRID(
                             ST_MakePoint((v_col * p_TileSizeX) + v_halfX,
                                          (v_row * p_TileSizeY) + V_HalfY),
           v_grid.geom := ST_SetSRID(
                             ST_MakeEnvelope((v_col * p_TileSizeX),
                                             (v_row * p_TileSizeY),
                                             (v_col * p_TileSizeX) + p_TileSizeX,
                                             (v_row * p_TileSizeY) + p_TileSizeY),
         END IF;
         RETURN NEXT v_grid;
     END Loop;
   END Loop;
  COST 100
  ROWS 1000;

The ST_RegularGrid function works in the same projection as your source data.

1.b. Create a layer that has all of the tiles for just the Chicago boundary

--This creates grids of 1,320 feet square (a 2x2 block size in Chicago)
SELECT gcol, grow, geom
 into b_chicagoboundary_grid_1320squared
 FROM ST_RegularGrid((select geom from chicagoboundary where gid = 1), 1320, 1320,FALSE);

In that query, “1320” is a distance in feet for both the X and Y planes, as the “chicagoboundary” geometry is projected in Illinois StatePlane FIPS East (Feet) (EPSG/SRID 3435).

2. Assign each point location to a tile in that grid and count the number of locations in each tile

Now you’ll need a table that has POINT-type geometries in it. For the map in this tutorial, I used a layer of location-based news articles that are used in Chicago Cityscape to highlight local developments.

SELECT, count(*) as count, grid.geom
INTO news_grid
FROM news_articles, b_chicagoboundary_grid_1320squared AS grid
WHERE st_intersects(news_articles.geom, grid.geom)

This query will result in a table with three columns:

  1. The ID of the tile, which is a primary key field.
  2. The number of news articles in that tile.
  3. The POLYGON geometry of that tile.
Look at these two maps (the one above, and the one below). The first map shows the whole city. The tiles are colored according to the number of news articles within the area of each tile. The darker the blue, the more news articles within that tile.
This map is zoomed in to the Woodlawn area. As you change scale (zoom in or zoom out), the size of the “heat” area (the size of each tile) doesn’t change – they are still 1,320 feet by 1,320 feet. The color doesn’t change either. The typical heat map doesn’t have these advantages.

A new map for finding COVID vaccination sites in Illinois

The State of Illinois map of COVID vaccination sites is pretty bad. 

Screenshot of the Illinois Department of Public Health map, taken February 14, 2021.

It’s slow (caused my browser tab to crash after a couple minutes), has misspelled county and city names, missing ZIP code digits, and cannot be searched by address. There are duplicate entries, too.

I made a new version of the state’s COVID vaccination sites map.

I didn’t make any COVID maps earlier because I didn’t want to spend the time to ensure that I understood the right and wrong ways to map disease, because people make decisions based on maps and I don’t want my maps to end up harming anyone. 

The new map of COVID vaccination sites on Chicago Cityscape.

Aside from the state website’s usability issues, I’m very disappointed that there is zero data about COVID in the state’s #opendata portal.

These cities and counties have the most COVID vaccination sites, according to the IDPH’s dataset. 

For the top 10 or so, it seems to correlate with population. Except Skokie has 7 sites, and Evanston has 4, despite Evanston having 10,000 more residents. Nearly 100% of Illinois is within 60 minutes driving of the current COVID vaccination sites. (More are coming, at least in Chicago.) 

Nearly 100% of Illinois is within 60 minutes driving of the current COVID vaccination sites. (More are coming, at least in Chicago.)

And a lot of Illinois is still within 45 minutes driving of the current COVID vaccination sites. Really big gaps in geography appear at the 30 minutes driving threshold.

A map of Illinois showing 30 minute driving areas around each of the 862 COVID vaccination sites.

I’m working with some people to show access via transit. This is super important. I predict that upwards of 75 percent of Chicagoans will be able to access a vaccination site or two within 45 minutes and 100 percent within 60 minutes.

Here’s another shortcoming of the state’s map: Each site’s unique ID is not persistent, making it difficult to compare one day’s list to the following day’s list. I got around that by making a “hash” of each vaccination site and comparing between two versions.

The map has been updated once since I started. The “hash” creates a unique ID based on the attributes of each vaccination site (name, address, city, county, ZIP code). Any time one of those attributes changes, the hash will also change and thus I can more easily find new or modified vaccination sites.

Why Jefferson Park residents should allow more housing

Short answer: To provide more shoppers for the local businesses. Read on for the longer answer. 

Over on Chicago Cityscape I added a new feature called “market analysis” which measures the number of people who live within specific walking areas (measured by time) and driving areas (measured by distance). 

I am in favor of removing apartment & condo bans in Chicago, especially in areas where they were previously allowed and near train stations.

Jefferson Park is centered around two co-located train stations, serviced by CTA and Metra respectively. There have been multiple proposals for multi-family housing near the stations (collectively called the Jefferson Park Transit Center) and some have been approved. 

Always, however, there are residents who resist these proposals and the number of originally proposed apartments or condos gets reduced in the final version (classic NIMBYism). 

There’re four reasons – at least – why more housing should be allowed near the Jefferson Park Transit Center:

  • Locally owned businesses require a significant amount of shoppers who live nearby and walk up traffic
  • More people should have the opportunity to live near low-cost transportation
  • It will include more affordable housing, through Chicago’s inclusionary zoning rules (the Affordable Requirements Ordinance, ARO)
  • There will be less driving, and therefore lower household transportation costs and less neighborhood pollution

To support the first reason, I used the “market analysis” tool to see just how many people live in a walkable area centered around Veterans Square, a mixed-use office and retail development adjacent to the train stations. 

Only 9,368 people live within a 10 minute walk to Veterans Square (get the Address Snapshot). 

Comparatively, 19,707 people live within a 10 minute walk to The Crotch, or the center of Wicker Park, at the intersection of Milwaukee/North/Damen (get the Address Snapshot). The Blue Line station is about 75 feet south of the center point.

I would grant the low Veterans Square number a small discount based on the proximity to the Kennedy Expressway, which severely truncates walking areas up and down the northwest side. Still, even with that discount, ending up with less than half the amount as the one in Wicker Park, is disturbing. Wicker Park is hardly characterized by high-density housing. In fact, all of the new high-rises are just outside the 10 minute walk shed!