CategoryData

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_Subdivide function 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.

How to download data from ArcGIS MapServers using your computer’s command line

A lot of geospatial data (GIS) is stored on ArcGIS MapServers, which is part of the Esri “stack” of products that municipalities use to manage and publish GIS data. And a lot of people want that data. If you have ArcGIS software on your Windows computer, then it can be pretty easy to plug in the map server URL and manipulate and extract the data.

For the rest of us who don’t have an extremely expensive license to that software, you can use a “command line” tool (written in Python) on any computer to download any layer of GIS data hosted on the ArcGIS MapServer and automatically convert it to GeoJSON.

You’ll need to install the Python package pyesridump, from the OpenAddresses GitHub repository, created by Ian Dees and other contributors.

Installing pyesridump is easy if you have pip installed, using the command pip install esridump.

The next thing you’ll need is the URL to a layer in a MapServer, and these are not easy to find.

Finding data to download

I can guarantee the county where you live has one. Before you continue, check to see if your county (or other jurisdiction) has the “open data portal” add-on to their ArcGIS stack.

Here are links to the open data portals enabled by Esri for Lake County, Illinois, and Broomfield County, Colorado). This is much easier to browse and find data to download (in shapefile and other formats) and you can skip this tutorial.

I don’t have a good recommendation to find the MapServer URL, though. A reader suggested looking for MapServers for jurisdictions around the world by looking through Esri’s portal of open data called ArcGIS Hub. Once you locate a dataset you want, you can find the MapServer URL under About>Data Source on the right side of the page.

I normally find them by looking at the HTML source code of a MapServer I already know about.

For this example I’ll use one of the GIS layers in the Cook County, Illinois, election service MapServer – here’s the layer for the Cook County commissioners districts.

Fetch the data

Once you have the URL the command is simple:

esri2geojson http://cookviewer1.cookcountyil.gov/ArcGIS/rest/services/cookElectnSrvc/MapServer/11 cookcounty_commissioners.geojson

  • The first term, esri2geojson tells your computer which program to load.
  • The second term is the URL of the MapServer URL.
  • The third term is the filename and location where you want to store the file. I prefer running the command “inside” the folder where I want the file to be stored. You can also specify a full path of the file. On a Mac this would look like ~/Users/username/Documents/GIS/projectname/cookcounty_commissioners.geojson

After you enter the command into your computer’s terminal, press enter. esri2geojson will report back once, after it finds and understands the MapServer URL you gave it. When it’s done, the command will “close” and your computer’s terminal will wait for the next command.

Do you have questions, or need some help? Leave a comment below.

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.

Inclusionary zoning calculator will tell you how many units a developer can afford to make “affordable”

An “inclusionary zoning” calculator can help you determine how much affordable housing your town should require that developers build in their new construction residential buildings.

I learned about Grounded Solutions Network’s Inclusionary Housing Calculator at the second-ever YIMBYtown conference in Oakland, California, two weeks ago.

YIMBY (yes in my back yard) is a movement to reduce barriers to building more housing in order to be able to house everyone at a level they can afford. It’s a movement for other things, and it means a lot of different things to a lot of different people but the end result is that more housing needs to be built.

An interested person inputs a lot of values relevant to their local housing market into the IHC and it will calculate the cost of construction per unit and the rental income from those units, and then will figure the profit margin for the developer. What makes this “inclusionary” is that one also needs to enter the desired portion of units that are set aside as “affordable” (to people making a certain income) and subsidized by the developer’s rental income.

I put the IHC through a real world exercise by inputting as much data as I knew about a rejected proposal in Pilsen.

The first proposal from Property Markets Group had 500 units, and 16 percent of them were set aside (news on this and their subsequent proposals). Chicago’s Affordable Requirements Ordinance, or ARO, requires that 10 percent of the units are affordable, and that 25 percent of those 10 percent must be built on site. The other 75 percent can be built on site, or the developer can pay an in-lieu fee per unit.

Needless to say, 16 percent on-site is much, much higher than 25 percent of 10 percent. A neighborhood organization, the Pilsen Land Use Committee, however, requires 21 percent in the area, and the city council member, Danny Solis, 25th Ward, adheres to.

PMG said they couldn’t go that high, and that’s what I wanted to test.

According to this Inclusionary Housing Calculator, could the developer make enough profit (considered as 10 percent) if the building had 21 percent of units as affordable?

In this exercise, the answer was “no, PMG could not make a profit if they had to set aside 21 percent of the units as affordable.”

But the calculator showed that they could earn a 12 percent profit if 16 percent of the units were affordable. 

Some of the inputs are actual, like the sale price of the land (found in the Illinois Department of Revenue’s transactions database), but I had to make up some inputs, including the apartments’ bedroom mix, and the future rental prices of those apartments.

Further reading

  • It’s tough for people to move into one of these set-aside apartments in Chicago (DNAinfo Chicago, July 28, 2017)
  • Inclusionary zoning cannot create enough affordable units (City Observatory, February 11, 2016)
  • Other housing cost calculators like this one (City Observatory, July 26, 2016)

The U.S. DOT should collaborate with existing “National Transit Maps” makers

The U.S. DOT demonstrated one idea for how a National Transit Map might look and work at a conference in February.

The Washington Post reported this month that the United States Department of Transportation is going to develop a “National Transit Map” because, frankly, one doesn’t exist. The U.S. DOT said such a map could reveal “transit deserts” (the screen capture above shows one example from Salt Lake City, discussed below).

Secretary Anthony Foxx wrote in an open letter to say that the department and the nation’s transit agencies “have yet to recognize the full potential” of a data standard called the General Transit Feed Specification that Google promoted in order to integrate transit routing on its maps. Foxx described two problems that arose out of not using “GTFS”.

  1. Transit vehicles have significantly greater capacity than passenger cars, but are often considered just vehicles because we are unable to show where and when the transit vehicles are scheduled to operate. The realistic treatment of transit for planning, performance measures, and resiliency requires real data on transit system operations.
  2. One of the most important social values of transit is that it makes transportation available to people who do not have access to private automobiles, and provides transportation options for those who do. Yet, we cannot describe this value at a national level and in many regions because we do not have a national map of fixed transit routes.

“The solution is straightforward”, Foxx continued, “[is] a national repository of voluntarily provided, public domain GTFS feed data that is compiled into a common format with data from fixed route systems.”

The letter went on to explain exactly how the DOT would compile the GTFS files, and said the first “collection day” will be March 31, this week. As of this writing, the website to which transit agencies must submit their GTFS files is unavailable.

What Foxx is asking for has already been done to some degree. Two national transit maps and one data warehouse already exist and the DOT should engage those producers, and others who would use the map, to determine the best way to build a useful but inexpensive map and database. Each of the two existing maps and databases was created by volunteers and are already-funded projects so it would make sense to maximize the use of existing projects and data.

“Transitland” is a project to host transit maps and timetables for transit systems around the world. It was created by Mapzen, a company funded by Samsung to build open source mapping and geodata tools. Transitland is also built upon GTFS data from agencies all over the world. Its data APIs and public map can help answer the question: How many transit operators serve Bay Area residents, and what areas does each service?

For the United States, Transitland hosts and queries data from transit agencies in 31 states and the District of Columbia. In Washington, D.C., Transitland is aware of four transit agencies. It’s a great tool in that respect: Not all of the four transit agencies are headquartered in D.C. or primarily serve that city. The app is capable of understanding spatial overlaps between municipal and regional geographies and transit agencies.

Transitland has a “GUI” to show you how much transit data it has around the world.

“Transit Explorer” is an interactive map of all rail transit and bus rapid transit lines in the United States, Mexico, and Canada. Yonah Freemark, author of The Transport Politic, created the map using data culled from OpenStreetMap, the National Transit Atlas Database (administered by the DOT and which shows fixed-guideway transit), and his own research. I wrote the custom JavaScript code for the Leaflet-powered map.

No other agency or project has collected this much data about fixed-guideway transit lines in any of the three countries, since the map includes detailed information about line lengths, ridership, and other characteristics that are not included in GTFS data. Transit Explorer, though, does not include local bus service or service frequencies, which the DOT’s map may if it incorporates the full breadth of GTFS data.

Transit Explorer also goes a step further by providing data about under construction and proposed fixed-guideway transit lines, which is information that is very relevant to understanding future neighborhood accessibility to transit, but which is not available through GTFS sources.

Finally, “GTFS Data Exchange” is a website that has been storing snapshots of GTFS feeds from agencies around the world for almost a decade, or about as long as GTFS has been used in Google Maps. The snapshots allow for service comparisons of a single agency across time. For example, there are over 100 versions of the GTFS data for the Chicago Transit Authority, stretching back to November 2009; new versions are added – by “cta-archiver” – twice a month.

Josh Cohen, writing in Next City, highlighted the significance of Google’s invention of GTFS, saying, “Prior to the adoption of GTFS, creating such a map would’ve been unwieldy and likely produced an out-of-date product by the time it was completed.” The DOT’s own National Transit Atlas Database includes only fixed-guideway (a.k.a. trains) routes, and hasn’t been updated since 2004.

Not all GTFS feeds are created equal, though. Some transit agencies don’t include all of the data, some of which is optional for Google Map’s purpose, that would make the National Transit Map useful for the spatial analysis the DOT intends. Many agencies don’t include the “route shapes”, or the geographic lines between train stations and bus stops. Researchers are able to see where the vehicles stop, but not which streets or routes they take. Foxx’s letter doesn’t acknowledge this. It does, however, mention that transit agencies can use some federal funds to create the GTFS data.

David Levinson, professor at the University of Minnesota, believes the map will bias coverage (geographic reach of transit service) over frequency (how many buses are run each day that someone could ride).

The U.S. DOT’s chief data officer, Dan Morgan, whom I met at Transportation Camp 2015 in Washington, D.C., presented at the FedGIS Conference this year one idea to demonstrate coverage and frequency in Salt Lake City, using the GTFS data from the Utah Transit Authority.

Levinson also tweeted that it will be difficult for a national map to show service because of the struggles individual transit providers have symbolizing their own service patterns.

Foxx’s letter doesn’t describe how planners will be able to download the data in the collection, but whichever app they build or modify will cost money. Before going much further, and before spending any significant funds, Foxx should consult potential users and researchers to avoid duplicating existing projects that may ultimately be superior resources.

Foxx can also take advantage of “18F” a new agency within the General Services Administration to overcome government’s reputation for creating costly and difficult to use apps. The GSA procures all kinds of things the federal government needs, and 18F may be able to help the DOT create the National Transit Map (and database) in a modern, tech and user-friendly way – or write a good RFP for someone else to make it.

Look for the National Transit Map this summer.

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.

How to use Chicago Cityscape’s upgraded names search tool

Search for names of people who do business in Chicago.

I created a combined dataset of over 2 million names, including contractors, architects, business names, and business owners and their shareholders, from Chicago’s open data portal, and property owners/managers from the property tax database. It’s one of three new features published in the last couple of weeks.

Type a person or company name in the search bar and press “search”. In less than 1 second you’ll get results and a hint as to what kind of records we have.

What should you search?

Take any news article about a Chicago kinda situation, like this recent Chicago Sun-Times article about the city using $8 million in taxpayer-provided TIF district money to move the Harriet Rees house one block. The move made way for a taxpayer-funded property acquisition on which the DePaul/McCormick Place stadium will be built.

The CST is making the point that something about the house’s sale and movement is sketchy (although I don’t know if they showed that anything illegal happened).

There’re a lot of names in the article, but here are some of the ones we can find info about in Chicago Cityscape.

Salvatore Martorina – an architect & building permit expeditor, although this name is connected to a lot of other names on the business licenses section of Cityscape

Oscar Tatosian – rug company owner, who owned the vacant lot to which the Rees house was moved

Bulley & Andrews – construction company which moved the house

There were no records for the one attorney and two law firms mentioned.

How to make a map of places of worship in Cook County using OpenStreetMap data

The screenshot shows the configuration you need to find and download places of worship in Cook County, Illinois, using the Overpass Turbo website.

If you’re looking to make a map of churches, mosques, synagogues and other places of worship, you’ll need data. The Yellow Pages won’t help because you can’t download that. And Google Maps doesn’t let you have a slice of their database, either. That’s where OpenStreetMap comes in. It’s a virtual planet that anyone can edit and anyone can have for free.

First we need to figure out what tag people use to identify these places. Sometimes on OSM there are multiple tags that identify the same kind of place. You should prefer the one that’s either more accurate (and mentioned as such in the wiki) or widespread.

The OSM tag info website says that editors have added over 1.2 million places of worship to the planet using “amenity=place_of_worship”.

Now that we know which tag to look for, we need an app that will help us get those places, but only within our desired boundary. Open up Overpass Turbo, which is a website that helps construct calls to the Overpass API, which is one way to find and download data from OSM.

In the default Overpass Turbo query, there’s probably a tag in brackets that says “[amenity=drinking_fountain]”. Change that to say “[amenity=place_of_worship]” (without the quotes). Now change the viewport of the map to show only the area in which you want Overpass Turbo to look for these places of worship. In the query this argument is listed as “({{bbox}})”.

The map has a search bar to find boundaries (cities, counties, principalities, neighborhoods, etc.) so type in “Cook County” and press Enter. The Cook County in Illinois, United States of America, will probably appear first. Select that one and the map will zoom to show the whole county in the viewport.

Now that we’ve set the tag to [amenity=place_of_worship] and moved the map to show Cook County we can click “Run”. In a few seconds you’ll see a circle over each place of worship.

It’s now simple to download: Click on the “Export” button and click “KML” to be able to load the data into Google Earth, “GeoJSON” to load it into a GIS app like QGIS, or “save GeoJSON to gist” to create an instant map within GitHub.

Two things I don’t like about TIF expenditures in Chicago

Chicago Cityscape's TIF Projects map

I built a map of most Chicago TIF projects that you can filter on the fly. Type in any keyword, alderman’s name, or neighborhood and the map will re-center and zoom to the results.

1. Millions of dollars ($14.4 to be exact) has been or will be given to rich corporations, like Home Depot, to build massive stores with huge roofs and parking lots far away from where people live so everyone has to drive there. It’s highly unlikely they don’t mitigate stormwater runoff (except through temporary storage in a retention pond) or treat any of the water on site, contributing to local flooding and clogged pipes.

According to the project descriptions, property tax payers in these four TIF districts have partially subsidized the construction of over 1,903 car parking spaces and the associated ills of expansive asphalt areas and motorized traffic.

2. A massive subsidy was approved – $96 million – for McCaffery Interests’s Lakeside development on the former U.S. Steel South Works plant to build a mixed-use tower of 250 apartments in an area that has weak transit access and will take decades to fully fill out. We should instead be spending this kind of money building housing in already developed parts of the city (where there’s already amenities, or infrastructure for amenities – the Rezko land comes to mind).

What’s interesting about the Lakeside TIF project approval is that the containing TIF district, “Chicago Lakeside Development Phase 1”, has collected zero property tax revenue because there is no property in it!

Trolley on the future Lake Shore Drive

A tour bus drivers on the Lakeside development. Photo by Ann Fisher.

There are some projects I like, though. TIF has been used frequently to build affordable housing, housing for seniors, and housing for people who need assistance. 78 out of 380 projects mention the word “affordable”.

The City Hyde Park building, designed by Studio Gang Architects, will have 20% of its residential units designated as “affordable”, for families (of varying sizes) earning up to 60 percent of the area median income. The city standard is 10 percent but developers are also able to pay an “in lieu” fee so they don’t have to build the affordable units and instead can offer those units at market rates.

Other projects have a majority of affordable units.

Who are the top property owners in Cook County

235 West Van Buren Street

There are several hundred condo units in the building at 235 W Van Buren Street, and each unit is associated with multiple Property Index Numbers (PIN). Photo by Jeff Zoline.

Several people have used Chicago Cityscape to try and find who owns a property. Since I’ve got property tax data for 2,013,563 individually billed pieces of property in Cook County I can help them research that answer.

The problem, though, is that the data, from the Cook County combined property tax  website, only shows who receives the property tax bills – the recipient – who isn’t always the property’s owner.

The combined website is a great tool. Property value info comes from the Assessor’s office. Sales data comes from the Recorder of Deeds, which is another, separately elected, Cook County government agency. Finally, the Treasurer’s office, a third agency, also with a separately elected leader, sends the bills and collects the tax.

The following is a list of the top 100 (or so) “property tax bill recipients” in Cook County for the tax years 2010 to 2014, ranked by the number of associated Property Index Numbers.

Many PINs have changed recipients after being sold or divided, and the data only lists the recipient at its final tax year. A tax bill for Unit 1401 at 235 W Van Buren St was at one time sent to “235 VAN BUREN, CORP” (along with 934 other bills), but in 2011 the PIN was divided after the condo unit was sold.

Of the 100 names, DataMade’s new “probablepeople” name parsing Python script identified 13 as persons. It mistakenly identified eight names as “Person”, leaving five people in the top 100.

The actual number is closer to 90, arrived at by combining 5 names that seem to be the same (using OpenRefine’s clustering function) and removing 5 “to the current taxpayer” and empty names. You’ll notice “Altus” listed four times (they’re based in Phoenix) and Chicago Title Land Trust, which can help property owners remain private, listed twice (associated with 643 PINs).

[table id=2 /]

© 2017 Steven Can Plan

Theme by Anders NorénUp ↑