This presentation on analytics, mapping, and targeted economic development was given by Dr. Peter Haas of the Center for Neighborhood Technology at the August 2017 meeting of the Chicago City Data Users Group (CCDUG).

1. Using Analytics to Find Opportunities for
Development in Manufacturing
Prepared by Peter Haas: Chief Research Scientist
Urban Analytics | Center for Neighborhood Technology
Central Manufacturing District. Primarily located along Ashland
Avenue and Pershing Road, Chicago. (Lisa DiChiera, Landmarks Illinois)

2. ABOUT CNT
 CNT is a national hub for research, strategies and
solutions to help cities use resources more efficiently
and equitably.
 We believe addressing problems like poverty, climate
change and urban sprawl starts with making
neighborhoods, cities and regions work better.

3. ABOUT CNT
 Our main areas of impact are:
 Inclusive Economic Development and Poverty
Reduction
 Place-Based Climate Resilience
 Outcome-Driven Urban Analytics

4. Photo Credit: Jeff McC, Flickr, Creative Commons
URBAN ANALYTICS
DEVELOP RESEARCH TOOLS TO HELP
PLANNERS, DEVELOPERS, AND COMMUNITY LEADERS
MAKE SMART, DATA-DRIVEN DECISIONS.

5. CNT WEB TOOL DEVELOPMENT
ENVIRONMENT
 Linux – running on a Amazon EC2 Cloud Server

7. CNT WEB TOOL DEVELOPMENT
ENVIRONMENT
 Linux – running on a Amazon EC2 Cloud Server
 PostgreSQL – on Amazon RDS

9. CNT WEB TOOL DEVELOPMENT
ENVIRONMENT
 Linux – running on a Amazon EC2 Cloud Server
 PostgreSQL – on Amazon RDS
 Using PostGIS for geospatial engine
 Mapserver with Tiling and caching
 Often over a Google map

11. CNT WEB TOOL DEVELOPMENT
ENVIRONMENT
 Linux – running on a Amazon EC2 Cloud Server
 PostgreSQL – on Amazon RDS
 Using PostGIS for geospatial engine
 Mapserver with Tiling and caching
 Often over a Google map
 QGIS, MapInfo, and ArcGIS as desktop GIS

13. CNT WEB TOOL DEVELOPMENT
ENVIRONMENT
 Linux – running on a Amazon EC2 Cloud Server
 PostgreSQL – on Amazon RDS
 Using PostGIS for geospatial engine
 Mapserver with Tiling and caching
 Often over a Google map
 QGIS, MapInfo, and ArcGIS as desktop GIS
 PHP, Javascript, JQuery

14. EXAMPLES
 htaindex.cnt.org – finding the value of reduce auto
dependence on housing affordability
 Uses many geographical levels, block group,
municipality, county, etc…
 eTOD.cnt.org – helps promote building affordable
housing near transit
 Dive into parcel data and link to many different
datasets
 parkrightdc.org – helps planners find the right
amount of parking to build on a given site
 Build a site from parcels to develop a building

15. LOOKING AT/FOR INDUSTRIAL
PROPERTY IN COOK COUNTY
 Use Parcels from the Cook County GIS Portal
 Use Cook County Assessor data to identify tax
class – kind of like land use
 Use CMAP land use data to help classify land use
on vacant land

20. FINDING UNDERVALUED
PARCELS
 Use Cook County Assessor data to identify tax
class – kind of like land use
 This gives the assessed value of the land and the
building (improvements) for every non-exempt
parcel in the county

22. Critera
(land val/ bldg val) acres
0 39,434.81
1 15,273.21
2 10,193.13
3 8,349.51
4 7,195.45
5 6,539.14
6 5,914.84
7 5,511.06
8 5,171.62
9 4,919.29
0.00
5,000.00
10,000.00
15,000.00
20,000.00
25,000.00
30,000.00
35,000.00
40,000.00
45,000.00
0 2 4 6 8 10
Acres
Criteria
Acres vs Criteria
acres

26. -- first append the two types of parcels
select * into cc_both_parcels
from (select 'vacant' as type, gid, geom from (select gid,geom from vacant_parcels where frac >0.1) v
union
select 'under' as type, gid, geom
from (select gid,geom FROM industrial_parcels where landval::integer >= 5*bldgval::integer) i) a;
-- this is the guts of the matter- union the intersecting parcels into aggregated areas
select distinct * into cc_both_temp from (WITH geoms (geom) as
(SELECT (ST_Dump(ST_Union(geom))).geom from cc_both_parcels )
SELECT max(gid) as gid, min(gid) as other_gid, ST_Multi(g.geom) as geom
FROM cc_both_parcels p, geoms g WHERE St_Intersects(p.geom, g.geom) GROUP BY g.geom
order by gid) q;
-- now make the aggregate table
select gid,st_union(geom) as geom
into cc_aggregated_both_parcels from cc_both_temp group by gid;
-- make primary key
ALTER TABLE cc_aggregated_both_parcels ADD PRIMARY KEY (gid);

29. COOK COUNTY SUMMARY
Size Range Cook Co.
Underutilized
Industrial
Parcels
Cook Co.
Underutilized
Industrial
Area
(Acres)
Cook Co.
Vacant
>10% Ind.
LU
Parcels
Cook Co.
Vacant
>10% Ind. LU
Area
(Acres)
0-3 Acres 9633 4565 4529 1614
3-5 Acres 512 1987 148 584
5-20 Acres 531 4657 185 1639
20-25 Acres 512 1987 148 584
>25 Acres 28 629 14 312
>5 Acres 632 8615 228 3205
Total 10777 15167 4905 5403
CMAP
Industrial
Cook Co.
Industrial
Cook Co.
Vacant
>10% Ind. LU
Cook Co.
Total
39738 Acres 36355 Acres 5403 Acres 41758 Acres

30. COOK COUNTY SUMMARY SUPER AREAS
Size Range Combined
Super
Areas
Count
Cook Co.
Underutilized
Industrial
Area
(Acres)
Cook Co.
Vacant
>10% Ind.
LU
Area
(Acres)
Total Area
(acres)
0-3 Acres 4685 2163 784 2966
3-5 Acres 365 1153 268 1426
5-20 Acres 585 4267 1340 5659
20-25 Acres 47 752 305 1061
>25 Acres 153 6520 2692 9458
>5 Acres 785 11538 4336 16178
Total 5835 14854 5388 20570

31. Industrial Facility Units
A Freight Access
A.1 Within 1 mile buffer of an expressway Yes, Absolute Y/N
A.2 Adjacent to an active freight rail line High Y/N
A.3 Roadway Capacity (current traffic volume) Low Annual Weekday Daily Traffic
A.4 Miles to an expressway exit & entrance Low Miles
A.5 Miles through non-industrial land (to expressway) Low Miles
A.6 Miles to an airport Low Miles
A.7 Miles to intermodal terminal Low Miles
A.8 Miles to transload facility Low Miles
B Property Development Potential
B.1 1. Adequate vacant industrial land for facility (*1)
Yes, absolute > 10
acres Acres
C Existing Industrial Market to Be Served
C.1 1. # Industrial businesses within 5-mile radius (*2) High Number of businesses
C.2 2. # Industrial jobs within 5-mile radius High Number of workers
C.3 3. All miles to the center of regional industrial jobs (*3) Low Miles
D Access to Ready Workforce
D.1 CNT AllTransit ™ Performance Score(*4) High Score out of 10
D.2 Industrial workers within 30-minute transit shed High Number of workers
D.3 Worker education fit (*5), 30-minute transit shed High Number of workers
* 1. Contiguous land zoned for industrial use that is vacant or on which the value of built improvements is less than the value of
the land
* 2. All North American Industrial Classification (NAIC) categories in manufacturing, wholesale trade or transportation and
warehousing
*3. CNT has developed an algorithm for determining the point at the geographic center of employment for workers in any
given NAIC, i.e., the point from which the total of distances to all jobs in a given district or region is the shortest.
*4. The All-Transit™ analytical tool developed by CNT provides the frequency of transit of all modes available at a given
location (census block group).
*5. "Worker Education Fit" for industrial jobs represents the percentage of all workers in a given location (census block group)
whose highest level of educational attainment is a high school or associate degree.
*6. Some sewer capacity may be provided by "green infrastructure", vegetation planted to absorb storm water where it falls.
Factors for a Tailored COD Site Ranking Analysis

32. Summary
• CNT works in an open environment to
develop tools;
• We keep adding more interactivity for the
users;
• Use these tools to identify opportunities for
developing industrial/manufacturing – COD;
• We are helping decision makers, planners,
and citizens be more aware of sustainable
urban opportunities.

33. THANK YOU
Peter Haas
pmh@cnt.org
www.cnt.org
@CNT_tweets
COD Development Contact David Chandler
david@cnt.org
www.cnt.org
@CNT_tweets