Community Participation in Planning:



Community Participation in Planning:

Using GIS and Public Input

to Envision Urban Change in “Real Time”

By

Rob Krueger, Ph.D.*(

Jason Farmer*

Fabio Carrera, Ph.D.*

Daniel Benoit, AIA+

*Interdisciplinary and Global Studies, Worcester Polytechnic Institute, 100 Institute Road Worcester, Massachusetts 01609

+Benoit Reardon Architects, 284 Park Avenue, Worcester, Massachusetts 01609

#Corresponding Author

Krueger@wpi.edu

508.831.5110

Abstract

Community participation in planning is politically charged and often leaves citizens wondering about the relevance of their input in the decision making process. As part of a Massachusetts program designed to promote community planning in the areas of housing, open space, economic development and transport, we developed and piloted a GIS-based decision tool that enables interested groups, private and public alike, to visualize in real time the implications of their planning decisions at a variety of community scales. Our paper presents the tool and the findings of our preliminary efforts to employ the tool.

Introduction: Engaging the Community in Urban Change

Worcester, Massachusetts (population 172,642) is New England’s third largest city (behind Boston and Providence, Rhode Island). Like many of the “satellite” cities around Boston, Worcester played a key role in developing and sustaining the industrial revolution in early US history. Worcester, in particular, was an industrial powerhouse from the 1840s to the 1920s, giving birth to many technological innovations, from barbed wire to the birth control pill. Also like many of these cities, Worcester is searching for its post-industrial identity. In 1950, the City’s population hit its zenith at just over 200,000. Since then, the City’s economy has remained stagnant and its population in decline. This is not to say that Worcester’s economy hasn’t evolved with the Region’s. It has.

In the 1980s the biotech industry established roots in Worcester on the strength of Worcester Polytechnic Institute, Tufts Veterinary School and the University of Massachusetts Medical Center. Since then the industrial cluster has grown but been overshadowed by economic activity to the East, toward Boston. Health care is another of the City’s major post-industrial employers. One sector that has excelled in Worcester’s recent history is the housing market. Indeed, in the first quarter of 2002 Worcester had the second hottest housing market in the United States. Data shows that the market is driven primarily by people moving out of high priced Boston [1](RKG Associates 2003). The cost of real estate was only one factor, however. Two other key factors that precipitated the exodus to Worcester were: 1) the renovation of Worcester’s Union Train Station which brought expanded commuter rail service between the two cities, and 2) hi-tech industry moving west of Boston, beyond the 128 beltway, to the Interstate 495 corridor. As these changes in the economy affect the patterns of economic development they also have implications for the urban landscape. For example, some data suggest that Worcester is the 25th most sprawled city in the country (Flint 2002). Though, as Figure 1 illustrates, the interest in Worcester’s triple decker stock suggests an interest in high density living. In addition, the influx of middle- and upper-middle class refugees from Boston have transformed Worcester’s neighborhoods, creating both opportunities for new business as well as disrupting 150 year old community fabrics. But what about these changes? Can they be managed? More importantly, are they in accord to the vision of current Worcester residents? Finally, how can we know what these visions are and whether they reflect the current ongoing market changes?

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The purpose of this paper is to report our efforts to assist the city in its management of these changes. In particular, we present preliminary findings from pilot tests of our Interactive Visualization Tool (or InVsT) which brings together open space, housing and economic development data with current land use maps and suitability criteria so city officials as well as the public can see in real time the implications of their community development plans and decisions. We hope this initial effort to link these data sources will enable the city administration to make more effective and more equitable development decisions as well as empower the public to insert its perspective into planning decisions.

The remainder of the paper unfolds as follows: first we discuss some of the relevant background of the project and goals. Next, through a case study we show the process of developing suitability maps for Worcester, Massachusetts. Third, we present the InVsT tool. Finally, before concluding we share some findings of our pilot tests.

Community Planning, Suitability and Public Participation

This project was initiated as part of an effort by the Commonwealth of Massachusetts to encourage communities to balance quality of life issues and access to affordable housing in times of rapid economic expansion. Initiated in 2000, Executive Order 418, which was promulgated by Governor Paul Cellucci, sought to provide financial assistance to all 351 towns and cities in the Commonwealth to examine tensions among housing, economic and open space needs. The general purpose behind the initiative was to engender local conversations among citizens to explore possible community futures based on scenarios involving current local zoning ordinances. One particular objective of the Order, which is what inspired the InVsT program, was for cities and towns to develop suitability maps for siting housing and economic development and preserving open space.

“Suitability” was based on criteria established by consultants and confirmed through a public participation process. These criteria and their implications for people’s lives are often abstract, difficult to picture. Furthermore, when the public does change the suitability criteria consultant follow-up is unaffordable and people’s schedules often make it prohibitive. Our goal was to present our “objective” suitability criteria to the public, have them deliberate on them, and then show them the results of their deliberations in real time. In this case, follow up was unnecessary because they received feedback through the course of the public meeting.[2] Figure 2 provides graphic representation of our process.

INSERT FIGURE 2 HERE

There is not space available here to describe the process and data collection methodology in total (For more a more comprehensive review see Benoit, et al 2004) (Hamir, et al 2003); Farmer et al 2003); (Zarr, et al 2003). In the next section we seek to overview our process of data collection and database development by focusing on the housing component of our study.

A Community Developing Plan for Worcester: Housing Suitability

The background sought to generally describe the data and information needed for the project. In this section we describe a subset of our process, the housing suitability analysis. The housing analysis was meant to start from a thorough housing inventory, which was not available for the City of Worcester. We were nonetheless able to develop a housing market profile and typology based on a recent study conducted by a consulting firm on behalf of the City (RKG Associates 2002). Using the MacConnell coding scheme, we classified Worcester’s housing typologies by parcel. Unfortunately, the Worcester Assessor’s data does not explicitly describe land use, though it contains a useful description of the building. In all, the Worcester parcel dataset categorizes buildings with 103 different descriptors. Single-family homes are the most numerous (23,075), followed by triple-deckers (5,046), then by two-family homes (3,780). Compared to other major New England cities, Worcester seems to have more single-family homes and more triple-deckers, with relatively few two-family dwellings and a moderate amount of multifamily dwellings (see Figure 3). Despite the difficulties with classification, we were able to analyze the housing suitability for two fundamental types of dwellings: single family and multi-family. We also considered the suitability of parcels as sites for housing for the elderly or for people with special needs.

INSET FIGURE THREE HERE

To simplify the visualization of the data, the suitability analysis for housing was divided into three sub-categories: single-family, multi-family and special needs and elderly housing. The principal suitability criteria that were brought to bear on the housing suitability calculations were[3] [4]: 1) lot size (smallest and largest more suited for multi), 2) accessibility (multifamily and special needs require better access); 3) deficit (for elderly housing only), and 4) proximity to open space (more important for high density multifamily).

Map 1 shows the suitability analysis for housing in Worcester. The map shows the suitability map for multi-family houses (green color in map below) clustered around downtown and along major arteries, with single-family homes filling the in-between spaces (red color). Note: current zoning was eliminated from the weighted criteria. Why? Because we did not wish to constrain future land use decisions based on current zoning ordinances. Also, keep in mind that the colors show only the highest suitable use. Numerically, the second highest use may be very close to the most suitable use. On the other hand, the unsuitable uses should be fairly clear, so these tools are primarily useful to identify sets of suitable uses versus unsuitable ones. Once a particular parcel is assigned one of the more suitable uses, surrounding parcels may become suddenly less suited for their topmost use. For instance, if a particular parcel was selected to be the site of a new elderly housing project, any additional parcels in the same census tract that had been earmarked for potential elderly housing might need to be re-assigned to the next highest suitable use.

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Though by no means a “silver bullet,” suitability analysis does provide a powerful tool for screening potential uses in the early stages of planning. It also provides enough information to guide rezoning effort and it helps to focus limited resources on important situations that may be the target of incentive programs. Yet, our suitability criteria and analysis took place largely in a vacuum. An important part of the project, and our own philosophy, was that these criteria must be deliberated by the public. Above we identified some of the problematic aspects of public planning (cost and time, to name two), so how could we engage the public in a meaningful way and let them visualize their efforts without taking more of their time. To accomplish this goal we created InVsT.

The Interactive Visualization Tool or “InVst”

To facilitate public input into these suitability maps, and future planning activities, we developed a computerized tool that would interact with the three databases we had developed for Housing, Open Space and Economic Development and allow a dynamic modification of the relative importance of each set of criteria associated with each of the three main areas of study. The tool also produced results in “real time” so that citizens engaged in the planning process could see immediately the implications of their land use decisions.

We identified a list of criteria culled from planning texts and interviews with professionals, but filtered by how feasible it was to obtain the data necessary to adequately “measure” each criterion, directly or by proxy. After the criteria were selected and filtered, we were left with seven factors for the analysis related to the three main types of housing considered, seven factors for the assessment of economic development suitability across the four broad business segments we analyzed, and eight factors for the identification of suitable sites for the three types of open space.

We set up three independently-modifiable “lookup” tables wherein we recorded the scores the focus group participants assigned to each of the relevant criteria (see Figure 4). The first completed version of the tool was built using Microsoft Access® for both the calculations and the data storage. To calculate the suitability after modifying the data, a number of macros would run a sequence of queries that would cumulatively produce the end result.

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The databases include data that have been pre-processed to reflect some of the useful measures dictated by the analyses. For example, a number of spatial queries involving buffers of varying widths were used to assign a proximity value to each parcel vis-à-vis parks. These spatial queries would typically be at our disposal without much additional information, since they are based on the geographical characteristics of the GIS objects.

The next generation of the system was written in Java™ to add more power and flexibility (see Figure 5). Adding a new criterion is as simple as adding another row in the criteria lookup table, and separately providing the data necessary. Some criteria, however, may be based on knowledge collected from government databases – such as the US census, or the city’s real estate tax assessments – so these would need to be manipulated to suit the desired analysis.

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The interactive visualization tool allowed us to conduct visioning sessions in a more constructive manner, which in turn allowed us to progressively refine the delicate balances of weights and scores that led to the development of our final suitability maps.

Pilot Testing InVsT

This section summarizes the information and opinions gleaned from three focus groups comprised of individuals who have direct knowledge of open space, housing and economic development issues in general, and Worcester, in particular. The synthesis represented here was not intended to be representative of Worcester’s population. Instead it reflects the views of those participants in the focus groups. Despite this report’s limited scope, it represents a process that could be easily replicated and executed in the community at large. The participants were asked to assess the WPI team’s suitability criteria and also pilot the use of the InVsT tool. Findings from the focus groups are presented below.

The composition of the focus groups was varied; particular occupation types did not populate a particular group. The focus population was derived from a convenience sample–various lists from local organizations, non-profit and government alike, were used to develop our population. In addition, we identified key individuals whose perspective we believed would inform the process. In total, our population sample included over 200 names from economic development, business, non-profit and community based organizations, and environmental groups. From this sample we randomly sampled 35 people to participate in the focus groups. Prospective participants were contacted by Brian Carlson, an intern working for Congressman McGovern’s office. Carlson was provided a phone script that described the focus groups and locations. The focus groups were divided into three segments: 1) a brief overview, 2) a discussion and ranking of suitability and 3) presentation the maps altered by community input.

Focus Group Findings

Within each of the three themes there was a consensus among focus group participants that Worcester’s zoning ordinances must be changed to reflect whatever values are determined through these focus groups. Every person recognized the importance of zoning yet felt that current zoning remains insufficient to protect the values of Worcester’s citizens. There is not room to present and discuss all the findings here. We will present the suitability criteria for economic development suitability criteria as well as the feedback on the InVsT tool (for further information on the findings please see (Benoit, et al 2004).

Economic Development Suitability Criteria

The Economic Development Suitability Criteria were deliberated by the focus group participant. The criteria gleaned from planning journals and other sources utilized by the research team are presented on the left column of Table 1 (below) and those raised by the participants are in the right hand column. As expected the team did not capture all the factors the community feels are important. Suggestions can be broken down into two main categories: analytical and data driven. Bullets one and three represent analytical elements. For example, these suggestions would have the analysis take on a more spatial approach. The second bullet requires more data, in this case about the City’s telecommunications infrastructure. Data driven recommendations were the most prevalent and most interesting among the two categories. Some are feasible, others not, and some could be developed over time. The process did provide the opportunity to explore these challenges with the participants.

|Table 1 |

|Suitability Criteria for Economic Development |

| | |

|WPI team criteria: |Participant Comments: |

|Access to a bus stop or route |1. Link “clusters” spatially |

|Proximity to a police station |(e.g., Biotech) |

|Proximity to a fire station |2. Telecommunication network |

|Access to major arteries |3. Higher priority should be given to mixed |

|Access to highways |use (market and affordable housing and a range|

|Proximity to sewers |of business) |

|7. Access to railway | |

|8. Zoning | |

The Planning Tool

• Included in the discussion was a questionnaire that asked the participants to complete a simple ranking of the suitability. Each participant ranked these criteria from one to eight, with eight being the lowest suitability. During the discussion a research assistant input these rankings into the InVsT program. The program then adjusted the map to the average weights identified by the group. At the end of the session the updated maps were juxtaposed to the WPI maps (see Maps 2-5). The respondents were able to see the results of their deliberations in real time, discuss them, and make suggestions for improvements in a single meeting. The participants identified new suitability criteria, as discussed above, they suggested new applications such as at the neighborhood level rather than the city scale. It also enabled them to see the where current zoning regulations conflicted with their notions of a livable city.

INSERT MAPS 2-5 HERE

Next Steps

Overall, focus group participants were pleased to learn InVsT and InVsT process. For all its effort to reestablish an economic base for the City and region, it turns out that, right now at least, Worcester’s biggest opportunity is its relatively inexpensive housing. Whether driven by new biotechnology parks, hospital campuses or housing stocks, Worcester’s landscape is affected by these ongoing changes. There are also material changes in how current residents experience their city in their daily lives. Cities typically have two options during times of rapid, market driven change: 1) they can let it happen or 2) they can manage it. The latter resonates in Worcester’s City Administration. Tools need to be developed to make this process cost-effective, democratic, and useful for city planners and interest groups. The pilot study of the InVsT tool suggests that it may be an effective tool for envisaging ideas for Worcester’s possible futures.

Our data and focus group maps suggest that significant gaps exist in what the public wants to see in suitability criteria and the data to support it. Our work will continue to examine the macro-changes at the city-scale as well as the more localized neighborhood transformations. This will enable us to assess the data needs more thoroughly. In addition, we hope to conduct a needs analysis and feasibility study into what data will act as a proxy for some of these factors and its availability.

Acknowledgements:

The authors would like to thank Congressman James McGovern for lending us his intern, Brian Carlson, for this project. We’d like to thank Brian for coordinating the focus groups and providing a critical ear. The project would not have been possible without the effort of William Scanlan, Director of Community Development Assistance Program Manager at the Central Massachusetts Regional Planning Commission and Joel J. Fontane Director of Planning for the City of Worcester.

References:

Benoit, Daniel, Fabio Carrera, Jason Farmer and Rob Krueger. 2004. Worcester’s EO 418 Report: An action plan for community development. Sustainable Cities Research Group Working Paper SC-004.

Flint, A (2002) Group notes Worcester County’s sprawl Ranked 25th; Boston area 77th Boston Globe, This story ran on page B2 of the Boston Globe on 10/18/2002.

Hamir, Akrad, Nina Mallozzi, and Kate Traynor. 2003. Building a Better Future: Housing opportunities and suitability analysis for Worcester. Sustainable Cities Research Group Working Paper: SC-001.

Farmer, Jason, Jennifer Settle, Matthew St. Pierre, and Christopher Wall. 2003. Transportation and Open Space Suitability Analysis for the City of Worcester. Sustainable Cities Research Group Working Paper: SC-003.

RKG Associates. 2002. A Housing Market Study for Worcester, Massachusetts. Durham, New Hampshire.

Zarr, Joshua, Jessica Jajosky, and Christopher Moller. 2003. Economic Development Opportunities and Suitability Analysis for Worcester. Sustainable Cities Research Group Working Paper: SC-002.

Figure 1

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Figure 2 - Public Input Process

Figure 3

Figure 4

Figure 5

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Map 1 - Housing Suitability

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Map 2 - Best Practices

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Map 3 - Focus Group 1

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Map 4 - Focus Group 2

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Map 5 - Focus Group 3

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[1] Boston is the highest priced real estate market in the country.

[2] Of course follow-up would sometimes be required. We anticipate InVsT being used in a variety of city-wide and neighborhood planning processes.

[3] As was the case for the open space and transportation analyses, the choice of criteria is based in part on the availability of data to support the inclusion of each criterion. Spatial metrics that can be directly extracted from GIS – like size and proximity – are always available with a modicum of manipulation. Other, more complex proxies – such as accessibility – may require considerable computational efforts[4]. “Deficit” was probably the most sophisticated indicator that we were able to calculate based on available datasets. We did not pursue even more complex suitability factors, such as the homogeneity of the housing stock in the neighborhood, since such measures are impractical, if not impossible to even approximate with the typically available urban datasets.

6 Elderly housing was weighted according to the deficit that was calculated as the actual number of people over 65 in each of Worcester’s census tracts minus the number of beds in that tract that are already dedicated to elderly people.

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GIS

Mapping

Suitability

Rules

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InVsT

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Data

Public

Input

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