Report - East St. Louis Action Research Project

ESLARP GIS: A REPORT ON THE CURRENT STATUS AND OPPORTUNITIES
OF GIS WITHIN THE EAST ST. LOUIS ACTION RESEARCH PROGRAM
PREPARED BY:
KRISTOFER JOHNSON
AS PARTIAL FULFILLMENT OF UP 497 – INDEPENDENT STUDY
AUGUST 2, 2002
DEPARTMENT OF LANDSCAPE ARCHITECTURE
UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN

INTRODUCTION
The work of a landscape architect is rooted in the characteristics of the site. This
site can be a wide variety of things: an urban plaza, a residential backyard, or a regional
open space network. Yet, in all cases, many of the design constraints and opportunities
are derived from the ecology and spatial attributes of the area. During the site analysis
stage or to explore the benefits of different design proposals, many landscape architects
will employ the use of Geographic Information Systems or GIS. GIS are able to organize
and display the geographic components of a site extremely quickly and easily.
Embedded within each point, line, or polygon layer is an attribute table that contains all
of the information associated with the individual elements of the layer. In addition to
having very basic data, such as an element’s location, length, and size, the attribute table
can be customized by the user to include any type of information desired.
GIS has proven to be a valuable tool for landscape architects and urban planners.
Comprehensive planning has typically run on a twenty-year time schedule. However,
due to the rapid demographic, economic, and political changes that occur in the modern
world, there is now a need to update these plans every five years. With GIS, more
frequent updates are possible and plans have a greater ability to change with new
development. GIS can also be used on many different types of projects. It has been used
successfully on projects ranging from economic and streetscape renewal in Albuquerque,
NM, viewshed preservation in the Hudson River Valley, and recreational master planning
in Chattanooga, TN (Hanna, 1999).
The focus of this report will be on how GIS can be used with grassroots,
neighborhood development organizations. Specifically, it will describe the East St. Louis
Action Research Project (ESLARP) and its use of GIS. There will also be a discussion of

the information that can be derived from existing ESLARP GIS data. Following this
section, the opportunities that ESLARP has to generate new types of data will be
examined. Finally, there will be a short discussion on how creating new data can be
incorporated into the ESLARP studio (ARCH 372, LA 236/338, UP 378) that occurs
during the spring semester. Within each subject, this report will attempt to provide both
the benefits of GIS and any possible concerns or limitations that may exist.
ESLARP AND GIS
The East St. Louis Action Research Project began it history with GIS in 1994
under the guidance of then University of Illinois Landscape Architecture Professor Brian
Orland. It was Professor Orland and his Fall 1994 LA 437 studio that first used GIS as a
tool to analyze the site conditions that exist in East St. Louis
(www.eslarp.uiuc.edu/la/LA437-F94/main.html). GIS was again used the following year
in many of the 1995 LA 437 projects (www.eslarp.uiuc.edu/la/LA437-F95/main.html).
However, here it can be seen that GIS was not only being used for site analysis, but also
to display different design proposals (Figure 1). Also in 1995, students in the Urban
Planning department used GIS to identify dilapidated structures in the Edgemont
neighborhood (www.eslarp.uiuc.edu/durp/UP419-S95/main.html). From these early
beginnings, Geographic Information Systems have become fully integrated into ESLARP
and the design process of its students.
Perhaps one of the greatest achievements for ESLARP and its GIS resources came
in 1996, when the first version of EGRETS was launched. EGRETS or the East St. Louis
Geographic Information Retrieval System (www.eslarp.uiuc.edu/egrets) was cutting-edge

Figure 1: An example of GIS being used as a design tool, not simply an analysis tool
technology when it first arrived and is still a valuable resource for East St. Louis GIS
information (refer to Appendix A for a step-by-step guide through this site).
While at EGRETS, one can view and download pre-packaged maps through the
Atlas section. The maps are categorized into varying geographic scales: neighborhoods,
city-wide, or county-wide. The Alta Sita, Emerson Park, and Landsdowne
neighborhoods have extensive lists of maps (refer to Appendix B). Included in the list
are general maps such as roads, lot boundaries, and building conditions. Yet, there are
also maps of much more specific items such as street drain existence, curb materials, and
trash conditions. It is a credit to ESLARP to have this type of precise information
available.

The visitor to this site also has the option to access raw data through the Store.
The ability to download the data layers themselves, allows the end user to customize the
information according to their needs. This is extremely helpful when the user is trying to
answer a specific question or create a different type of map than that available on the
website. Unfortunately however, not all of the data is offered through the Store. Here
one can only find specific neighborhood data for Alta Sita and the general layers for East
St. Louis and St. Clair County (refer to Appendix B). For the EGRETS website to be
truly powerful, all of the data should be made available. The ability to access all existing
data through a central site would be especially helpful to students working in the East St.
Louis studio.
Figure 2: ESLARP GIS webpage

There are several other sources of GIS data on the internet. Many of these are
listed on the ESLARP website (www.eslarp.uiuc.edu/gis/index.htm, Figure 2). TIGER
line files are developed by the Census bureau and contain important census information
as well as general data like roads, railroads, streams, etc. These are available for free
from the Geography Network website (www.geographynetwork.com/data/tiger2000).
For state and county-wide datasets, one can go to the Illinois Natural Resources
Geospatial Data Clearinghouse provided by the Illinois Department of Natural Resources
and the Illinois State Geological Survey (www.isgs.uiuc.edu/nsdihome/ISGSindex.html,
Figure 3). At this site, it is possible to download layers such as roads, railroads, wetlands
Figure 3: Illinois Natural Resources Geospatial Data Clearinghouse homepage

inventories, and municipal boundaries. This site also provides a link to the USGS Digital
Orthophoto Quadrangles (geographically referenced aerial photographs) for the state of
Illinois.
Aside from these sites, there are other GIS datasets available within ESLARP.
Many of these are a result of the Spring 2002 studio. Working in the South End
neighborhood for the first time, the students performed a Neighborhood Conditions
Survey (NCS). The NCS was developed by ESLARP and has also been used in the Alta
Sita, Edgemont, Emerson Park, and Landsdowne neighborhoods. The survey form is
available on the ESLARP website (www.eslarp.uiuc.edu/gis/ncs/training/Diction1.htm,
Figure 4). The purpose of the NCS is to record specific information about each
Figure 4: Excerpt from the ESLARP Neighborhood Conditions Survey form

individual parcel in the neighborhood. Information such as building conditions, trash
conditions, and the number of trees on each property is then input as the attribute data for
the parcel boundaries data layer. The NCS is very beneficial to the students because they
are able to create maps of the neighborhood based on vacant lots, landuse, building
materials, and many other categories.
Other datasets that were either generated or gathered by the Spring 2002 students
include: aerial photography of the neighborhood, a Digital Elevation Model (DEM),
elevation contours, and the mass transit routes (bus and light rail) (refer to Appendix C
for examples of this data). Many students used the aerial photography to increase the
realism of their maps and plans. It seemed that the residents also enjoyed the use if the
aerial photos because they were able to visualize the neighborhood from above and even
identify their own homes. The DEM provided provocative hillshade images that revealed
how the city of East St. Louis sits completely within the Mississippi River floodplain.
The elevation contours were generated from the DEM and were used to discover the low
areas of the neighborhood that could be prone to flooding during heavy rains. With this
information, it was possible to identify the actual properties that may be threatened by
flooding. Finally, the bus and light rail routes were provided by the Bi-State
Development Agency (www.bi-state.org) that manages St. Louis regional transit. This
data helped students adapt their landuse plans according to existing transit corridors.
DEVELOPMENT OF EXISTING DATA
ESLARP has many opportunities to develop and generate new layers of
information from the data that already exists. Some of this has already been performed.

As part of a Summer 2002 Independent Study, the author has examined the South End
NCS and produced several informative maps. Similar to the work developed for other
neighborhoods, these maps include:
• Existing Building Conditions – identify structures for demolition
• Unoccupied Existing Buildings – identify resale/rental opportunities
• Fire Damaged Buildings – identify any patterns or a large fire event
• Trash Conditions – identify properties in need of cleanup
• Existing Landuse – identify opportunities for new development
• Plant Growth in Right of Way – identify walks in need of cleanup
• Street Trees in Right of Way – identify streetscaping or lack thereof
• Existing Trees on Properties – identify properties with a valuable amenity
• Materials of Existing Buildings – identify upcoming maintenance problems
• Recent Improvements on Buildings – identify responsible homeowners
• Height (# of stories) of Buildings – can lead to a 3D spatial representation
• Property conditions – identify problem lots and responsible homeowners
All of these maps were produced by selectively displaying different attributes of the NCS
data layer. They have been saved as 8.5”x11” JPEG images and as individual ESRI
ArcMap documents.
The author has also downloaded several of the TIGER line files created from the
2000 Census. The roads, railroads, streams, lakes, census blocks, municipal boundaries,
and county boundary files have been gathered for St. Clair and Madison Counties in
Illinois. Additionally, all of these files except for the census blocks have been
downloaded for St. Louis City and County, St. Clair County, and Jefferson County in
Missouri.
One exciting tool of GIS that could be used with existing data is the Network
Analyst. This allows the user to predict the amount of time required to travel between

two points along a network, generally a road layer. The analyst also can generate service
areas out from or in to a specific point. A good example of this is a fire station. Network
Analyst can predict the area serviced within 2, 5, or 10 minutes of the station along the
road network. Another example is the area served by a supermarket (Figure 5). How
much of an area can reach the supermarket within 5, 10, or 15 minutes Using this tool
would require some data development of the roads layer, however the core information
exists. One would simply need to add the speed along different types of roads to the data
attribute table. Generally, speed limits are not a very good indicator however because
stops and traffic effects need to be incorporated into the speed estimate. ESLARP could
use the Network Analyst to find travel times to different goods and services needed by
the residents and areas serviced by the police and fire departments. This could result in
landuse master plans that are better informed and truly meet the needs of residents.
Existing data could also be used to create a building outlines layer. This could be
done relatively easily using the aerial photography that is now available. Digitizing the
building outlines would be relatively simple and not require an extraordinary amount of
time. However, this dataset would be especially helpful to the studio during the design
stages. As the ESLARP studio continues to work in the South End, the designs generated
will move from the master plan level down to the individual site plan. Having the lot
lines and property boundaries are helpful for overall planning, but they do not provide
precise enough information for site design. Building outlines will help make this jump in
scale possible. Additionally, a building outlines layer in combination with NCS data
would make it possible to generate 3D scenes of the neighborhood and proposed designs.

Travel Times to Existing Supermarkets
Figure 5: This example of the Network Analyst shows how various zones can be delineated according to the
travel time to or from a specific point. This figure shows the travel zones to existing supermarkets in shades of
gray, then overlaid by a color landuse layer.

This would be a great visual tool for residents to see how different designs would affect
the spatial nature of their neighborhood.
OPPORTUNITIES FOR NEW DATA
ESLARP also has the capability to develop many new layers of data and
information. Closely related to the Network Analyst is the Address Matching tool.
Again, this tool uses the roads data layer and can pinpoint any address that is entered. At
first glance, this may not seem like a very useful item. However, this could be a valuable
way to map crime statistics (Ceccato and Snickars, 2000). Many residents of the South
End complained of crime in the area. If a log of crimes could be obtained from the police
department, then a data layer could be created based on where these crimes took place.
This would result in a useful dataset with the ability to represent crime rates spatially.
Crime data could then be examined against many other types of neighborhood
information. One could use this layer and the Network Analyst together to ask the
question: Do more crimes happen in areas that are not quickly or easily serviced by the
police The results of this study could certainly affect the placement of police services in
a new master plan.
An interesting area of current research is the development of resident-generated
GIS or “Bottom-Up GIS” (BUGIS) (Talen, 2000, p.280). BUGIS attempts to reverse the
role of the resident in the GIS process. Typically, the resident is “informed” of their
situation by GIS experts in a top-down fashion. However, with BUGIS it is the resident
that informs and provides the foundation for the GIS data. A primary focus of BUGIS is
to integrate local knowledge and qualitative data into the GIS layers (Talen, 2000).

This approach can have several positive effects on the community and its
development process. First, it can facilitate interaction between residents and open a
dialogue about the area’s problems, opportunities, and expectations. Furthermore, the
ability of the residents to present their perceptions in a dynamic and visual way may
increase neighborhood participation in planning decisions. It is possible that it could
provide a greater sense of empowerment to both the neighborhood and the individual
because it is their voice that is being heard and utilized (Talen, 1999).
During the Spring 2002 studio, this type of resident information was recorded
through the Cognitive Mapping and SWOT (Strengths, Weaknesses, Opportunities,
Threats) Analysis exercises. However, it was never translated into a GIS format.
Furthermore, the author believes that these types of exercises should be taken to the next
level in order to generate truly useful information. For example, a resident describing the
trees of the neighborhood as a strength is not as beneficial as them explaining which trees
are important and where they are located.
There are several types of layers that could be created from a resident-generated
GIS activity. Residents could describe strong points of the neighborhood such as areas
they feel are safe, paths they follow to work or school, parks that people use and who
uses them, and streets they feel have improved over time. It is also important to record
information about some of the issues of the area like loitering youths, streets people avoid
due to traffic or crime, and localized flood zones. One of the advantages of GIS is that
information, such as age, sex, race, and income, about the residents supplying the
descriptions could be incorporated into the layer. This could yield insight into

neighborhood social dynamics. For example, it would be possible to observe if older
residents avoid different areas or travel different paths than the younger residents.
There are two basic ways that resident GIS information could be gathered, either
through hand drawn maps or a questionnaire. In both cases, the process of transferring
the raw data into a GIS format would be time consuming. Ideally, a computer with GIS
would be used to record the information in real-time. Unfortunately, this can be both
expensive and difficult in terms equipment, personnel, and proper facilities (Al-
Kodmany, 2001). Another issue that can occur in resident-generated data is the risk of
overrepresentation of certain groups (Ceccato and Snickars, 2000). This would most
certainly occur if the data gathering were performed only at neighborhood meetings. For
example, younger residents are typically not present at these meetings and in order to
obtain a true sample of the collective feelings of the residents they would need to be
included in the process.
One final type of new data that could be developed by ESLARP is a database of
images linked to GIS layers. The Chicago Imagebase Project was a pioneer in using GIS
to organize images according to their geographic location. Researchers associated with
the project believed that this framework would allow users to easily understand and
orient themselves to the spatial layout of their neighborhood (Al-Kodmany, 2001).
Digital images can easily be linked to either an existing data set or a newly created file.
The advantage of linking to a new layer is that important information about the image
could be stored within that layer. Items such as the date, time, direction, and subject of
the photo could be integrated into the file. Through the use of scripts within the GIS
environment, it could then be possible to run image-based queries of the data (Al-

Kodmany, 2001). An example would be, “show me pictures of clean vacant lots and
where they are located on the map.”
Geographically referenced photographs of the South End neighborhood would be
a tremendous resource for the students of the ESLARP studio. Not only could they
refresh their memories of specific areas, but design sketches and altered images could be
put back into GIS as part of a final presentation. This would be an exciting way to
organize design proposals from the studio, especially if put into a web-based format.
Designs proposals would then be accessible to residents, other students, and the public at
large.
INTEGRATION INTO THE ESLARP STUDIO
GIS should play a significant role in the ESLARP studio. It has the ability to
overlay and manipulate data such that new information becomes apparent and certain
questions can be answered. It is the author’s opinion that one of the simplest layers to
generate and possibly the most helpful to students is the image database. The studio
makes several field trips down to East St. Louis and it would be very easy to have a
group of students take photographs for part of one day. Equipped with digital cameras,
the students could cover the neighborhood in a relatively short period of time. Using a
map and a data form of some kind, they could record the number of the photo, exactly
where it was taken, the direction, date, time, and subject. Different students could
concentrate on different subjects. This would minimize any overlap and would allow for
several different image-based data layers to be created. For example, there could be a
layer that had street images, another with vacant lot images, and still another with

deteriorated housing images. Regardless of the subjects decided upon, these photos
would be an extremely valuable resource to the students. The actual creation of the data
layers would be somewhat time consuming, but the benefits would be worth the effort.
Certainly the resident-generated GIS layers could also be incorporated into the
studio. Door to door interviews or even a mail-based questionnaire would provide
excellent data. There could be some sort of exercise created for use at a SENDO meeting
also. The major issue involved with this is the time required to transfer all of the
information into a GIS dataset. Digitizing hand drawn maps is tedious work and
converting descriptions into a spatial representation can be very difficult. Yet, the author
believes that through group work and the division of responsibilities, it would be possible
to create this type of data. It would again be very beneficial and would hopefully lead to
more intelligent design decisions.
It should be mentioned that the author has created a CD for the students of the
ESLARP studio. This CD contains all of the existing data layers that are available for the
South End, including those generated and downloaded during Summer 2002. The author
will also be creating a booklet of full color maps showing the information that has been
derived from the South End NCS. The layout template used for these maps will be
included on the CD such that any future documents could use the same format.
CONCLUSION
The East St. Louis Action Research Program has an excellent foundation of GIS
data and several opportunities to develop its GIS capabilities in the future. Much of the
existing data is available through the ESLARP website and EGRETS. The EGRETS

website could become an even more powerful and useful clearinghouse of East St. Louis
GIS data if more layers are made available. Also, as more current datasets become
available through the Census Bureau, Federal Emergency Management Association
(FEMA), and other sources, ESLARP should continue to update its information. This
will provide residents, students, and staff with the most current data available, hopefully
resulting in the most informed decisions possible.
Using existing GIS layers, ESLARP can generate new and exciting insight into
the dynamics of East St. Louis neighborhoods. Terrain models and elevation contours
can help identify properties in danger of flooding or perhaps areas suitable for open
space. GIS tools such as Network Analyst and Address Matching can be used to create
maps of service areas, travel times, crime statistics, and many other items. Aerial
photography can serve as the source to create a building outlines layer. This will become
increasingly useful to students as the ESLARP studio continues to refine its design
proposals and bring them to more detailed level.
New datasets like image-based GIS and “Bottom-Up” GIS embody exciting new
opportunities to integrate student involvement and local area knowledge into a realistic
spatial framework. Image layers can aid in the student design process and provide a new
way of presenting design proposals. Resident-generated GIS contains numerous
possibilities for not only beneficial datasets, but also neighborhood interaction and
participation.
Furthermore, students can and should be involved in the creation of these GIS
datasets. This involvement could mean taking photographs, drawing maps with residents,
tallying the results of a questionnaire, or digitizing new layers. Yet in all cases, the

esults of their hard work will be a set of valuable information that can be used well into
the future. ESLARP has the ability to use GIS as a very powerful tool…a tool that can
help create well-informed design solutions that embrace the true needs of East St. Louis
residents.

REFERENCES
Al-Kodmany, Kheir. (2001). “Bridging the Gap Between Technical and Local
Knowledge: Tools for Promoting Community-Based Planning and Design.”
Journal of Architectural and Planning Research, 18(2): 110-130.
Ceccato, Vania A. and Folke Snickars. (2000). “Adapting GIS Technology to the Needs
of Local Planning.” Environment and Planning B: Planning and Design, 27(6):
923-937.
East St. Louis Action Research Project Website – www.eslarp.uiuc.edu
Geography Network Website – www.geographynetwork.com
Hanna, Karen C. (1999). GIS for Landscape Architects, ESRI Press, Redlands, CA.
Illinois Natural Resources Geospatial Data Clearinghouse Website –
www.isgs.uiuc.edu/nsdihome/ISGSindex.html
Talen, Emily. (1999). “Constructing Neighborhoods from the Bottom Up: the Case for
Resident-Generated GIS.” Environment and Planning B: Planning and Design,
26(4): 533-554.
__________. (2000). “Bottom-Up GIS: A New Tool for Individual and Group
Expression in Participatory Planning.” Journal of the American Planning
Association, 66(3): 279-294.