Tag: Chicago Cityscape

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
DROP   TYPE IF EXISTS T_Grid CASCADE;
CREATE TYPE T_Grid AS (
  gcol  int4,
  grow  int4,
  geom geometry
);
-- Drop function is exists
DROP FUNCTION IF EXISTS ST_RegularGrid(geometry, NUMERIC, NUMERIC, BOOLEAN);
-- Now create the function
CREATE OR REPLACE FUNCTION ST_RegularGrid(p_geometry   geometry,
                                          p_TileSizeX  NUMERIC,
                                          p_TileSizeY  NUMERIC,
                                          p_point      BOOLEAN DEFAULT TRUE)
  RETURNS SETOF T_Grid AS
$BODY$
DECLARE
   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;
BEGIN
   IF ( p_geometry IS NULL ) THEN
      RETURN;
   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_srid);
         ELSE
           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),
                             v_srid);
         END IF;
         RETURN NEXT v_grid;
     END Loop;
   END Loop;
END;
$BODY$
  LANGUAGE plpgsql IMMUTABLE
  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 grid.id, 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)
GROUP by grid.id;

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.

Is it possible for us to “greenline” neighborhoods?

(I don’t mean extending the Green Line to its original terminal, to provide more transportation options in Woodlawn.)

Maps have been used to devalue neighborhoods and to excuse disinvestment. There should be maps, and narratives, to “greenline” – raise up – Chicago neighborhoods.

The Home Owners’ Loan Corporation “residential lending security” maps marked areas based on prejudicial characteristics and some objective traits of neighborhoods to assess the home mortgage lending risk. (View the Cook County maps.) The red and yellow areas have suffered almost continuously since the 1930s, and it could be based on the marking of these neighborhoods as red or yellow (there is some debate about the maps’ real effects).

The Home Owners’ Loan Corporation and its local consultants (brokers and appraisers, mostly) outlined areas and labeled them according to objective and subjective & prejudicial criteria in the 1930s. Each area is accompanied by a data sheet and narrative description. The image is a screenshot of the maps as hosted and presented on Chicago Cityscape.

The idea of “greenlining”

I might be thinking myopically, but what would happen if we marked *every* neighborhood in green, and talked about their strengths, and any historical and current disinvestment – actions that contribute to people’s distressed conditions today?

One aspect of this is a form of affirmative marketing – advertising yourself, telling your own story, in a more positive way than others have heard about you in the past.

In 1940, one area on the Far West Side of Chicago, in the Austin community area, was described as “Definitely Declining”, a “C” grade, like this:

This area is bounded on the north by Lake St., on the south by Columbus Park, and on the west by the neighboring village of Oak Park. The terrain is flat and the area is about 100% built up. There is heavy traffic along Lake St., Washington Blvd. Madison St., Austin Ave. (the western boundary) and Central Ave. (the eastern boundary).

High schools, grammar schools, and churches are convenient. Residents shop at fine shopping center in Oak Park. There are also numerouss small stores along Lake St., and along Madison St. There are many large apartment buildings along the boulevards above mentioned, and these are largely occupied by Hebrew tenants. As a whole the area would probably be 20-25% Jewish.

Some of this migration is coming from Lawndale and from the southwest side of Chicago. Land values are quite high due to the fact that the area is zoned for apartment buildings. This penalizes single family occupancy because of high taxes based on exclusive land values, which are from $60-80 a front foot, altho one authority estimates them at $100 a front foot. An example of this is shown where HOLC had a house on Mason St. exposed for sale over a (over) period of two years at prices beginning at $6,000 and going down to $4,500. it was finally sold for $3,800. The land alone is taxed based on a valuation exceeding that amount. This area is favored by good transportation and by proximity to a good Catholic Church and parochial school.

There are a few scattered two flats in which units rent for about $55. Columbus Park on the south affords exceptional recreational advantages. The Hawthorne Building & Loan, Bell Savings Building & Loan, and Prairie State Bank have loaned in this area, without the FHA insurance provision. The amounts are stated to be up to 50% and in some cases 60%, of current appraisals.

Age, slow infiltration, and rather indifferent maintenance have been considered in grading this area “C”.

Infiltration is a coded reference to people of color, and Jews.

My questions about how to “greenline” a neighborhood

  1. How would you describe this part of Austin today to stand up for the neighborhood and its residents, the actions taken against them over decades, and work to repair these?
  2. How do you change the mindset of investors (both small and large, local and far) to see the advantages in every neighborhood rather than rely on money metrics?
  3. What other kinds of data can investors use in their pro formas to find the positive outlook?
  4. What would these areas look like today if they received the same level of investment (per square mile, per student, per resident, per road mile) as green and blue areas? How great was the level of disinvestment from 1940-2018?

In the midst of writing this, Paola Aguirre pointed me to another kind of greenlining that’s been proposed in St. Louis. A new anti-segregation report from For the Sake of All recommended a “Greenlining Fund” that would pay to cover the gap between what the bank is appraising a house for and what the sales price is for a house, so that more renters and Black families can buy a house in their neighborhoods.

That “greenlining” is a more direct response to the outcome of redlining: It was harder to get a mortgage in a red area. My idea of greenlining is to come up with ways to say to convince people who have a hard time believing there are qualities worth investing in that there they are people and places worth investing in.


The Digital Scholarship Lab at the University of Richmond digitized the HOLC maps and published them on their Mapping Inequality website as well as provided the GIS data under a Creative Commons license.

The genius of using ST_Subdivide to speed up PostGIS intersection comparisons

You should use ST_Subdivide to break up large shapes into smaller ones

This infographic visually compares the difference between running a PostGIS comparison query like ST_Intersects on a large shape versus a subdivided version of that large shape. Click to embiggen.

Hundreds of GIS intersection comparisons are completed every hour on Chicago Cityscape.*

People are looking at, say, a map of the South Shore community area. That “Place” page then grabs all of the building permits, building violations, business licenses, and other “feature layers” that are stored as points.

A classic “point in polygon” comparison is made using the ST_Intersects(place_geometry, permits_geometry) function.

This has worked very well for several years.

The problem

But as Chicago Cityscape handles larger shapes – they come from users drawing their own, large shapes, and from large shapes like the downtown Chicago area – this query doesn’t cut it.

Setting indexes on the geometry is imperative, but it’s not the end of the to optimize performance. That’s because the index of the geometry is a rectangular bounding box (which is also called an “envelope” in GIS) that contains the entire shape of the South Shore community area.

The downtown Chicago area, however, is not even the largest shape I have. That belongs to the new Place, “Neighborhood Opportunity Fund investment zones” (NOF). Combined, they cover 75 square miles of Chicago. Downtown is only 7.7 square miles.

After I added the NOF map and tested its Place page, it “crashed” my server, metaphorically speaking. The query to just count the number of building permits in the area would take about five minutes.

There had to be a better way; in the meantime, however, I divided the NOF map into the West and South sections. This hardly improved the counting time.

The solution

Thankfully, today, I saw a tweet from Paul Ramsey linking to his blog that linked to his slides from a recent presentation about the use of PostgreSQL to store and manipulate GIS data.

In it he explained how the ST_Subdividefunction worked. I’m going to demonstrate it using graphics from my own maps.

A normal intersection comparison, using ST_Intersects(place_geometry, permits_geometry) in a query creates a bounding box (envelope) around each geometry and quickly determines whether the two envelopes overlap. If they do, then it checks again to see if the actual geometries overlap. If they do, that data is returned as a response to your query.

When your two datasets are massive, like the NOF zones, which collectively cover 1/3rd of Chicago, and the building permits, which are found across the entire city…well, that led to the five minutes counting time.

Enter ST_Subdivide. To use it properly you would run it against your existing geometry and store the much smaller shapes, derived from the big shape, in a new table. I applied the function to all the 22,203 maps that Chicago Cityscape has and stored their unique IDs and subdivided geometries in a new “lookup” table.

Now, any time I want to compare the building permits against the NOF, the building permits are instead compared to the small shapes that were subdivided.

The query

Chicago Cityscape uses a single table (created as a materialized view) to combine all 22,203 maps. Each map is stored in a source table (for example, there’s a table to hold the 77 community areas) and the materialized view runs once a day to combine all of the maps in the source tables. This ensures our data is managed well: different source tables can hold different information, and the single table holds only the name, type, and geometry of the source tables, for faster comparison. Each entry in the single table also has a “slug”, its unique identifier.

Thus, the materialized view of the subdivided maps is created from the aforementioned single table, using this query:

create materialized view view_places_subdivided as
select gid || '_' || random() as gid, slug, st_subdivide(geom) as geom
from view_places;

The “gid” is designed to create a new unique ID field, as the slug field will be repeated for every subdivided of each map. A unique ID field is necessary if you want to refresh the materialized view concurrently (to allow for other queries to access the materialized view while it’s being refreshed).

* The results are cached for a few hours, because the feature layers change 1-2 times per day and at different times each day, so the limited duration cache accommodates that. Ideally I would code a way to invalidate the cache when the feature layer data is updated.

Update 12/31/19: ST_Subdivide will fail if your geometries have any or certain geometry errors (I don’t know if it’s any kind of error, or certain kinds of errors that make the function fail). Chicago Cityscape has over 37,000 features that ST_Subdivide is attempting to process, and there is a lot of room for error in managing that many features from dozens of sources.

Upzone the 606

Map of the single family-only zoning around the Bloomingdale Trail

The area in green only allows single-family houses to be built.

Something’s gotta give.

This is all of the land area within two blocks of the Bloomingdale Trail that allows only single-family housing to be built (view full map). This isn’t to say that multi-family housing doesn’t exist here; it definitely does, and there’s probably a handful of two-flats on a majority of the blogs.

All of the five parks of the 606 are within this two block radius, and 49.6 percent of the land allows only single-family housing to be built.

But why build a transportation corridor, a park, a new, expensive, public amenity, and not change the kind of housing – which often determines the kind of family and makeup of a household – that can afford to buy a home near here.

It’s already been shown that detached single-family housing prices have grown intensely the closer you get to the trail. That price growth has meant displacement for some, and “no chance to buy or build a house here” for many others.

There are still plenty of vacant lots within the mapped area; lots that should have a 2-4 unit building built on them, but where only a 1-unit building is allowed.

This map was made possible by the new Zoning Assessment tool on Chicago Cityscape. Read about it or use it now.

Fun with stats: Building permits by street name and number edition

John Hancock Center

The John Hancock Center. Photo by Kevin Dickert.

 

On which street are the most building permits issued?

Michigan Avenue!

But where on Michigan Avenue are the most building permits issued?

Take a guess!

First, can you answer: Are most building permits issued to North Michigan Avenue (between Madison Street, 0 north/south, and Oak Street, 1000 north), or South Michigan Avenue (between Madison Street, 0 north/south, and um, somewhere south of 130th Street, 13000 south)?

Here’s the answer…

Even though South Michigan Avenue is at least 13x longer than North Michigan Avenue, South Michigan Avenue has 39 percent fewer building permits!

From 2006 to yesterday (Saturday), there were 7,828 building permits issued to projects on North Michigan Avenue and 4,714 building permits issued on South Michigan Avenue.

The most common address on North Michigan Avenue to receive building permits was 875 N Michigan Avenue. It’s also the most common address to receive building permits on all Chicago streets.

What’s there? The John Hancock Center (tower)!

The average building address number on North Michigan Avenue is 540.6. That means that building permits on North Michigan Avenue concentrate around Grand Avenue, which is near the city’s biggest Marriott hotel, and is where the Under Armor flagship store is.

The next most common street – after South Michigan Avenue – is North Clark Street, which extends from Madison Street (0 north/south) to the northern edge of the city at Howard Street, which is 7600 north, about 7.6 times longer than North Michigan Avenue.

S. Clark Street Signs

Businesses in the 400 block of South Clark Street, as of when the photo was taken in November 2008. I believe the hotel is still there. This is the busiest block of South Clark Street, for building permits. Photo by Bruce Laker.

South Clark Street doesn’t register in the top 10 or even the top 100. It comes it at number 162, with 772 building permits. This is surprising to me because South Clark Street runs from Madison Street (0 north/south) in downtown and goes to 2200 south, and has a lot of downtown office buildings.

South LaSalle Street (3,613 building permits), South Wabash Avenue (2,916), and South Dearborn (1,611) are all in the top 50. The data could be wrong somehow.

A map of maps

The map of maps.

Over on my website Chicago Cityscape I’ve assembled a map of maps: There are 20,432 maps in 36 layers. You might say there are 36 maps, and each of those maps has an arbitrary number of boundaries within. I say there are 20,000+ maps because there’s a unique webpage for each of them that can tell you even more information about that map.

This post is to throw out some analysis of these maps, in addition to the simple counts above.

The data comes from the City of Chicago, Cook County, and the U.S. Census Bureau. Some layers have come from bespoke sources, including the entrances of CTA and Metra stations drawn by Yonah Freemark and me for Transit Explorer. The sections of the Chicago River were divided and sliced by the Metropolitan Planning Council. The neighborhood and business organizations layers were drawn by me, by interpreting textual descriptions of the organizations’ boundaries, or by visually copying an organization’s own map.

There are 6,879 unique words longer than 2 characters, in the metadata of this map of maps. The most common word is “annexation”, which makes sense, given that the layer with the most maps shows the 10,668 Cook County annexation actions since 1830 – the first known plat was incorporated in the City of Chicago.

The GeoJSON file, an open source, human readable GIS format, comes out to 30 MB, and it make break your browser when you try to display this layer.

The next group of words are also generic, like “planned” and “development”, related to the Planned Development kind of zoning process in Chicago – called Planned Unit Development in other jurisdictions.

After that, some names of municipalities that traded back and forth between unincorporated Cook County and incorporated municipalities are on the list.

Working down the list, however, it gets really boring and I’m going to stop. I bet if you’re a smarter data science person you can find more interesting patterns in the words, but I’ve also increased the number of generic words (like planned development) by adding these as keywords to each map’s “full text search” index, to ensure that they would respond to a variety of search phrases from users.

Designing a new static map style for Chicago Cityscape

I redesigned the static maps that are shown on Chicago Cityscape’s Place pages to tone down their harsh hues, and change what data (which comes from OpenStreetMap) is shown.

All 2,800 maps are automatically generated using a program called MOATP (“Map of all the places”) which is based on Neil Freeman’s svgis program. Both programs are open source.

The map now shows all roads; it was awkward to see so many empty spaces between buildings. Secondary* and residential roads are shown with slightly less thickness than primary and motorway roads. Also included are multi-use trails in parks.

Parks and grass are shown in different hues of green, although I don’t think it’s distinctive enough to know there’s a difference. Cemeteries remain a darker green.

I’ve changed the building color to soften the harsh brown. Only named buildings and schools appear, which is why you see a lot of gaps. Most buildings outside downtown aren’t named.

Retail areas have been added in a soft, salmon and tan-like color to show where “activity” areas in each Place.

I’ll be uploading the new maps soon.

* These road categories come from the OpenStreetMap “highway” tag.

What should this area in Chicago be called?

The area is generally bounded by Harrison Street or Congress Parkway, Dan Ryan Expressway or Desplaines Street, Roosevelt Road, and the Chicago River.

The area is generally bounded by Harrison Street or Congress Parkway, Dan Ryan Expressway or Desplaines Street, Roosevelt Road, and the Chicago River.

Currently it’s called the South Loop, which is a neighborhood name. It’s in the “Near West Side” community area. See how the City of Chicago mapped the “South Loop” in the past when it used to keep track of neighborhood boundaries.

I think it should have a new name. It should not be called the South Loop because the commonly identified center of the South Loop is probably somewhere between Roosevelt and Harrison, and Michigan Avenue and State Street, very far from this area. It just might be the Roosevelt CTA station, which has over 12,000 boardings a day.

Saying that you’re going to some business that’s west of the river and saying that the business is in the South Loop would confuse a lot of people as to what its nearby.

It’s more of an industrial and commercial area that gained a lot of new big box (faceless) retail in the 2000s, so very few people live there. There are several stores that exist that came decades before the big box outlets; for fabric, clothing, shoes, and suits. It’s probably these independent store owners that can point to an older neighborhood name as they were the center of consumer commerce in this area.

It’s easy to give it a new name. Most of the housing is north of Harrison Street. It’s difficult to figure out how many people live here because the block groups for this area include more than the area in question.

It’s easy to argue that because of the land uses, it really has no current identifiable “place” or pattern that attracts people. I’d like to know more about its history and, South Loop being a modern name, its previous names.

Which places in Chicago get the most building permits?

View from the CTA green roof

The Merchandise Mart in the Near North Side community area ranks second place in locations receiving the most building permits.

Ed. note: I changed the title of this blog post because one interpretation of the original, “Where are the most building permits issued in Chicago?”, has the answer “City Hall”, the location of the issuer. My bad. 

Without regard to type or construction cost, the most building permits in the City of Chicago are issued at 11601 W Touhy Ave.

Where is that? It depends on which geocoder you use.

Two buildings at 11601 W Touhy Ave from Google Street View. The City of Chicago has issued thousands of building permits to this address, but the work is actually distributed across the O'Hare airport grounds. Google Maps and the Cook County parcel map places these buildings in Des Plaines.

Two buildings at 11601 W Touhy Ave from Google Street View. The City of Chicago has issued thousands of building permits to this address, but the work is actually distributed across the O’Hare airport grounds. Google Maps and the Cook County parcel map places these buildings in Des Plaines.

Google Maps puts it on this building that’s on a street called “Upper Express Drive” and in the city of Des Plaines, Illinois. But the City of Chicago wouldn’t issue building permits in another city.

Our own geocoder converts the geographic coordinates given in the city’s building permits database for these permits to the address “399 E Touhy Ave, Des Plaines, IL”. The Cook County parcel for the same location has the address “385 E Touhy Ave, Des Plaines, IL”.

Now where is this building?

It’s at O’Hare airport, and it’s one of a handful of addresses* the city’s buildings departments uses to denote permits issued to work at O’Hare. Since 2006 to Saturday, December 12, 2015, there’ve been 2,403 building permits issued here. The permits’ work descriptions indicate that a lot of the work occurs elsewhere on the airport grounds.

13 buildings have had more than 400 permits issued since 2006 to yesterday.

address community area count
11601 W Touhy Ave O’Hare

2403

222 W Merchandise Mart Plz Near North Side

802

141 W Jackson Blvd Loop

538

233 S Wacker Dr Loop

518

2301 S Lake Shore Dr Near South Side

516

30 S Wacker Dr Loop

510

5700 S Cicero Ave Garfield Ridge

495

500 W Madison St Near West Side

482

227 W Monroe St Loop

422

55 E Monroe St Loop

421

875 N Michigan Ave Near North Side

408

151 E Wacker Dr Loop

407

350 N Orleans St Near North Side

401

A pattern emerges: 10 of these 13 buildings are in the Central Business District and the other three are O’Hare airport, McCormick Place (2301 S Lake Shore Drive), and Midway airport (5700 S Cicero Ave).

The first location that’s outside the Central Business District and not one of the city’s airport or its convention center is at 1060 W Addison St – better known as Wrigley Field – in the Lake View community area with 321 building permits issued. It ranks #30. If you keep running down the list, the next most frequently issued location is 7601 S Cicero Ave – that’s the Ford City Mall and I think the city’s only sprawl-style indoor mall. It ranks #39 because it pulls monthly electric maintenance permits.

The Merchandise Mart’s position at #2 is notable because the majority of its permits are for small amounts of work: there is a lot of electrical rewiring done because of the frequent shows and exhibitions in the interior design materials “mall”.

The Mart sees other activity, though, including multi-million renovations for technology companies like Motorola Mobility and Braintree. The Mart also received a permit this year for a new $3 million staircase construction, part of its building-wide renovation project.

Rendering of new main (south) lobby staircase at the Merchandise Mart

This rendering shows a new grand staircase that will be built in the Merchandise Mart’s south lobby jutting from the side of the lobby that’s between the doors on the Chicago River side, and the reception desk and central elevator bank. A building permit issued this fall puts the construction cost at $3 million.

If you want to know more about building trends in Chicago, send me a message through the Chicago Cityscape website and I can put together a custom report for you.

* Other addresses I’ve noticed are:

  • 10000 N Bessie Coleman Dr
  • 10000 W Ohare St
  • 11600 W Touhy Ave
  • 11555 W Touhy Ave

Of these only the two Touhy Ave addresses are logical: O’Hare Street isn’t a real road, and 10000 N Bessie Coleman Dr is much further north than the northernmost point in Chicago.