Structured Public Involvement™
Workshop
Helsinki City Auditorium
Kansakoulukatu 3
Helsinki, Finland
May 18, 2009
9 am-12 n...
John’s the One on the Left
Today
1. SPI as a Response to Public Participation Problems
– Large groups and complex questions
– John Rawls and the ‘Vei...
Press the Number That Best
Describes You
60%
40%
0%0%
Transporta... Electric U...
Elected Of... None of th...
1. Transport...
Years of Experience in Your Field
20%
0%
60%
20% 1. 1-5
2. 5-10
3. 10-15
4. More than 15
My Familiarity with ARS (Keypads)
N
everH
eard
ofIt
Seen,butNeverUsed
Participated
in
a
M
eeting
H
ave
U
sed
Ita
Little
H
...
SPI as a Response to Public Participation Problems
85% of Kentucky citizens believe the public should be
more involved in the project development process.
(Meeting Kentucky’...
The Arnstein Ladder: Degrees of Citizen Participation in Planning
(Arnstein 1969)
Manipulation
Therapy
Informing
Consultat...
The Arnstein Ladder: Degrees of Citizen Participation in Planning
(Arnstein 1969)
1. Where are we now?
2. Where should we ...
Where are we now?
M
anipulation
Therapy
Inform
ingConsultation
PlacationPartnership
Delegated
Pow
erCitizen
Control
0% 0% ...
Where should we be?
M
anipulation
Therapy
Inform
ingConsultation
PlacationPartnership
Delegated
Pow
erCitizen
Control
0% 0...
Manipulation
Therapy
Informing
Consultation
Placation
Partnership
Citizen Control
Delegated Power
Mean score ~3.7
Desired ...
3.5 4 4.5 5 5.5 6 6.5
Actual level
Desired level
The Professionals’ Conceit…
“We’re doing OK”
Breakdown of the Arnstein Gap for Professionals
3 4 5 6 7
American Planning
Association (2007)
Professional
Engineers (200...
Some observations on the Arnstein Gap
The public recognizes and wants expert domain
Professionals and public want the same...
• Professional skepticism of the justification for,
and the practicality of, including large
numbers of people in planning...
Partition the Decision Domain: current situation
Input from professionals
Input from public
Problem domain:
financial, tec...
Partition the Decision Domain: SPI model
Input from professionals
Input from public
Problem domain:
financial, technical,
...
• “D.A.D.” Method……. (O’Connor et. al. 2000)
• Disagreement Within Design Authority About Goals and
Priorities (Comeau et....
Structured Public Involvement: Foundational Assumptions
We work in a democratic polity and we are dealing with public
good...
Rawls and the ‘Veil of Ignorance’
John Rawls’ principles of justice
Rawls argues that self-interested rational persons beh...
John Rawls’ Principles of Justice/Fairness
Everyone has the same minimum set of liberties that do not invalidate
anyone el...
Justice Problem
• Distributive Justice is inherently unattainable
in transportation (and many other)
infrastructure projec...
Methodological Implications
This means in the context of Structured Public Involvement
1. Soliciting participation from al...
Functional Process
• Accommodate large numbers of participants.
• Give each equal voice.
• Make them anonymous, independen...
Unit 2: Session Planning, Design and Implementation
• What is SPI™? SPI™ performance
• Group Process Design: Questions and...
Representation Decision Modeling
Group Dialogic
Methods
Structured Public Involvement (SPI)
What is Structured Public Involvement or SPItm
SPItm delivers high performance evaluations from
stakeholders, project spon...
How do we achieve these goals?
Structured Public
Involvement:
preparation is
critical
The public sees this….
• Kentucky Transportation Cabinet (Planning, Environmental, Districts)
• Indiana DOT
• Arizona DOT (pilot study)
• FHWA : ...
Project Manager, State Transportation Agency (Bridge project 2005-07)
“For the state of Kentucky, as owner of the bridge, ...
Federal official (Bridge project 2005-07)
“I had never been through a process using this type of activity. This was very
t...
SPI Stakeholder satisfaction evaluations
0 1 2 3 4 5 6 7 8 9 10
Rural Highw ay improvement (KY, 2000)
Transit Oriented Dev...
Structured Public Involvement Design Process
How to convert principles of SPI™ into action
Structured Public Involvement Design Process
Using Casewise Visual Evaluation
BRIDGE DESIGN AESTHETICS
1
2
3
4
Vote For Your Favorite Bridge
Choice
One
Choice
Two
Choice
Three
Choice
Four
0% 0%0%0%
1. Choice One
2. Choice Two
3. Choi...
1
How Suitable Is...
Bridge 1
Very
Unsuitable
...
...
...
So-So
...
...
...Very
Suitable
0% 0% 0% 0% 0%0%0%0%0%
1. Very Unsu...
2
How Suitable Is...
Bridge 2
Very
Unsuitable
...
...
...
So-So
...
...
...Very
Suitable
0% 0% 0% 0% 0%0%0%0%0%
1. Very Unsu...
3
How Suitable Is...
Bridge 3
Very
Unsuitable
...
...
...
So-So
...
...
...Very
Suitable
0% 0% 0% 0% 0%0%0%0%0%
1. Very Unsu...
4
How Suitable Is...
Bridge 4
Very
Unsuitable
...
...
...
So-So
...
...
...Very
Suitable
0% 0% 0% 0% 0%0%0%0%0%
1. Very Unsu...
0
0.2
0.4
0.6
0.8
1
How Suitable Is...
Basics of Questions and Polling
• Nature of Question Should be Clear
– Cost versus Appeal versus Other Factors?
• Avoid “Y...
Scoring Summary and Standard
Deviation by Groups
Representation Strategies
• Goal is to Assure Competent Responses from
Group
• May Use Data, Photos, Videos, GIS, etc.
• U...
Item:
Image 1
Positives - Looks like Bardstown road, the openness, trees, plaza is neat with the commercial, mixed use,
it...
7.8
Example:
Community Planning
Green Space
Single Family
Townhouses
Multi - Family
Commercial
Mixed - Use
Scenario 10
Scenario 10
Decision Support Modeling
• How Does Data Become Incorporated Into
Project?
• Simple Comparative Scoring
• Multiple Criter...
Innovative Decision Support Tools
• Analytic Hierarchy
– Allows Limited Preference Analysis Data to be
Comparatively Organ...
Dress This Man
2 Jackets x 3 pants x 2 shirts x 3 ties = 36 combinations
5 3 3 3 3
5 3 1 1 3
5 7 5 1 3
8 7 5 3 3
9 8 5 3 3
CAsewise Visual Evaluation (CAVE)
Decision Support
LOW
LOW
HIGH
HIGH
Following Modules:
• Land Use
• TOD Design
• Routing Problem
• Major Bridge Design
• Nuclear Industrial Cleanup and Re-Use
Example:
Community Planning
Planning Problem
• How do people’s judgments articulate with different
“kinds” of developments?
• Distinguishing Propertie...
Green Space
Single Family
Townhouses
Multi - Family
Commercial
Mixed - Use
Scenario 1
Scenario 1
Green Space
Single Family
Townhouses
Multi - Family
Commercial
Mixed - Use
Scenario 10
Scenario 10
Describing Development Patterns
Parameters Value and Meaning
Low Medium High
Mix of Housing Types 80-100% Single
Family De...
Mix Housing Types Mix Building/Land Use Greenspace Walkability Street Connectivity
LOW MED HIGH LOW MED HIGH LOW MED HIGH ...
Housing Mix (HOU) = Var Land Use Mix (BLU) = Var
Greenspace (GRN) = Low
Sidewalk Ratio (ACT) = Low Street Connectivity (CO...
Housing Mix (HOU) =Var Land Use Mix (BLU) = Var
Greenspace (GRN) = Low
Sidewalk Ratio (ACT) = High Street Connectivity (CO...
Housing Mix (HOU) = Var Land Use Mix (BLU) = Var
Greenspace (GRN) = Med
Sidewalk Ratio (ACT) = High Street Connectivity (C...
TOD Design
Architects’ Design Language
Height: (L, LM, M, MH, H) Low-rise,
low-medium, mid-rise,
medium-high, high-rise
Typology: (C,...
Item:
Image 1
Positives - Looks like Bardstown road, the openness, trees, plaza is neat with the commercial, mixed use,
it...
Item:
Image 10
Positives - Playground (residential), Patios & Balconies
Negatives - Looks disposable, Parking detracts, To...
First Scoring
Second Scoring
Output Preference Surface: Height v Density
7.8
Routing Problem
New Transmission Line:
Somerset to London
New Transmission Line:
Somerset to London
Real-time Data Collection
Real-time Data Collection
Landscape Features
Subject to Physical Damage
• Wildlife management area
• National Forest
• Wetland
• Archaeological feat...
Significance for Physical Damage:
Power and Non-Power ProfessionalsSubject to Physical Damage
0
5
10
15
20
25
30
W
ildlife...
Features Subject to
Visual and Proximity Impacts
• Human Habitation
• School
• National Properties Register
• Hospital
• C...
Non-Point Features
• Electric Fields
• Magnetic Fields
• Radio Frequency
Interference
• Audible Noise
• Visual Impacts
300...
Significance for Visual / Proximity Impacts: Power and
Non-Power Professionals
0
5
10
15
20
25
30
Human
Habitation
School ...
Features Affecting Constructability
• Strip or shaft mines
• Public water supply
• Airport
• Sewage treatment
• Pipeline
•...
Construction Costs
Construction Feature Multiply base cost by
Angle of turn
16-30o 1.1
30-90o 1.2
Grade
5-30% 1.0 + grade(...
Most Important Landscape Features
Airport
Superfund or other EPA Project Site
Military installation
National and State Par...
Important Landscape Features
Archaeological feature
National Properties Register
High land cost
Bodies of water
Dams
Natio...
Reverse Viewshed Analysis
Visualization
Source: DOE/EIS-0325, Jan. 2003
Impact of Color Value on Visual Impact
Color + Complexity
Color + Simplicity
Nuclear Industrial Site Cleanup and Re-Use
TVA
WKWMA
DOE
DOE
leased to
WKWMA
DOE
Security
fence
PGDP Future Vision Process
Stakeholder
Interviews
CBPC SPI
Stakeholder
Community
Meeting (s)Stakeholder
Focus Groups
Futur...
Example Scenario Matrix
Future Vision Categories Scenario
1
Scenario
2
Scenario
3
Scenario
4
Land Use
a. Nuclear Industry
...
Example Scenario Fact Sheet
Impacts:
Health
Economic
Environmental
Trends:
Energy Needs
Economic
Environmental
Uncertainti...
Structured Public Involvement
Future Vision
Scenarios
Fact Sheets
Future Sate
Visualizations
Future State
Visualizations
D...
CAsewise Visual Evaluation (CAVE)
Fuzzy Knowledge Builder
Optimal Solution
5 3 3 3 3
5 3 1 1 3
5 7 5 1 3
8 7 5 3 3
9 8 5 3...
Myths of Public Involvement
1. “difficult to have consensus without leadership”
(CORP speaker, May 2007)
2. “without leade...
Myths about Public Involvement in Planning
“in this environment, it is impossible to involve
people” (CORP speaker, May 20...
Myths about Public Involvement in Planning
“the public are uninformed” (CORP panelist, Feb 2004)
The public may not have e...
Myths about Public Involvement in Planning
“without leadership, participation is impossible”
(CORP speaker 2007)
Participa...
Myths about Public Involvement in Planning
“people don’t know what they want” (Planning
meeting participant, 2006)
People’...
Myths about Public Involvement in Planning
“difficult to have consensus without leadership” (CORP
speaker, May 2007)
Conse...
• “..there has been little attempt to develop [more
general] theories within the context of
transportation projects, possi...
• “..there has been little attempt to develop [more
general] theories within the context of
transportation projects, possi...
Methodological Suggestions from Transportation Literature
Methodological Suggestions from Transportation Literature
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
Structured Public Involvement™ workshop Helsinki May 2009
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Structured Public Involvement™ workshop Helsinki May 2009

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Structured Public Involvement workshop hosted at Helsinki City Auditorium, May 2009. Contains slides showing Arnstein Gap, overview of SPI process design, and summary results for various large civil infrastructure projects 1999-2008.

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Structured Public Involvement™ workshop Helsinki May 2009

  1. 1. Structured Public Involvement™ Workshop Helsinki City Auditorium Kansakoulukatu 3 Helsinki, Finland May 18, 2009 9 am-12 noon Dr. Ted Grossardt Lexington, Kentucky, USA Dr. Keiron Bailey Tucson, Arizona, USA Mr. John Ripy Lexington, KY, USA
  2. 2. John’s the One on the Left
  3. 3. Today 1. SPI as a Response to Public Participation Problems – Large groups and complex questions – John Rawls and the ‘Veil of Ignorance’ – Translating Justice/Fairness to Process Rules 2. SPI Session Planning, Design, and Implementation – What is SPI? Performance of SPI – Group Process Design: Questions and Polling – Representation Strategies – Decision Support Tools – Comparison to Some Current Practices 3. Case Studies (Your choice) – Large Bridge Design – Small Area Design for Light Rail Station – Land Development Planning – Highway/Electric Transmission Line Corridor Planning – Nuclear Industrial Site Cleanup and Future Uses
  4. 4. Press the Number That Best Describes You 60% 40% 0%0% Transporta... Electric U... Elected Of... None of th... 1. Transportation Professional 2. Electric Utility Professional 3. Elected Official 4. None of the above
  5. 5. Years of Experience in Your Field 20% 0% 60% 20% 1. 1-5 2. 5-10 3. 10-15 4. More than 15
  6. 6. My Familiarity with ARS (Keypads) N everH eard ofIt Seen,butNeverUsed Participated in a M eeting H ave U sed Ita Little H ave O urO w n System 0% 0% 0%0%0% 1. Never Heard of It 2. Seen, but Never Used 3. Participated in a Meeting 4. Have Used It a Little 5. Have Our Own System
  7. 7. SPI as a Response to Public Participation Problems
  8. 8. 85% of Kentucky citizens believe the public should be more involved in the project development process. (Meeting Kentucky’s Transportation Needs and Priorities: Citizen’s Perceptions and Recommendations. KTC-05-23/TA12-04-1F, p. 72)
  9. 9. The Arnstein Ladder: Degrees of Citizen Participation in Planning (Arnstein 1969) Manipulation Therapy Informing Consultation Placation Partnership Delegated Power Citizen Control Degrees of citizen power Degrees of tokenism Nonparticipation 8 7 6 5 4 3 2 1
  10. 10. The Arnstein Ladder: Degrees of Citizen Participation in Planning (Arnstein 1969) 1. Where are we now? 2. Where should we be?
  11. 11. Where are we now? M anipulation Therapy Inform ingConsultation PlacationPartnership Delegated Pow erCitizen Control 0% 0% 0% 0%0%0%0%0% Mean = 1. Manipulation 2. Therapy 3. Informing 4. Consultation 5. Placation 6. Partnership 7. Delegated Power 8. Citizen Control
  12. 12. Where should we be? M anipulation Therapy Inform ingConsultation PlacationPartnership Delegated Pow erCitizen Control 0% 0% 0% 0%0%0%0%0% 1. Manipulation 2. Therapy 3. Informing 4. Consultation 5. Placation 6. Partnership 7. Delegated Power 8. Citizen Control Mean =
  13. 13. Manipulation Therapy Informing Consultation Placation Partnership Citizen Control Delegated Power Mean score ~3.7 Desired level ~6.1 Arnstein Gap The Arnstein Gap N > 1000, various public and professional forums in the U.S.
  14. 14. 3.5 4 4.5 5 5.5 6 6.5 Actual level Desired level The Professionals’ Conceit… “We’re doing OK”
  15. 15. Breakdown of the Arnstein Gap for Professionals 3 4 5 6 7 American Planning Association (2007) Professional Engineers (2007) Local planners/professionals in KY (2006) Transportation Research Board (2006)
  16. 16. Some observations on the Arnstein Gap The public recognizes and wants expert domain Professionals and public want the same level of participation BUT A Gap exists. The public would like a greater degree of participation. HOW can we close the Arnstein Gap?
  17. 17. • Professional skepticism of the justification for, and the practicality of, including large numbers of people in planning and design • Bad experiences on the part of the public cause hostility and suspicion. This causes professionals to fear public engagement. • Professionals seek to limit public involvement Factors that Contribute to the Arnstein Gap
  18. 18. Partition the Decision Domain: current situation Input from professionals Input from public Problem domain: financial, technical, legal, aesthetic Degrees of citizen power Degrees of tokenism Nonparticipation 8 7 6 5 4 3 2 1
  19. 19. Partition the Decision Domain: SPI model Input from professionals Input from public Problem domain: financial, technical, legal, aesthetic Degrees of citizen power Degrees of tokenism Nonparticipation 8 7 6 5 4 3 2 1
  20. 20. • “D.A.D.” Method……. (O’Connor et. al. 2000) • Disagreement Within Design Authority About Goals and Priorities (Comeau et. al. 2000) • Vague Charge to Consultant (Behroozi 2000) • Limited Range of Design Options (Unsworth 1994) • Public Distrust of Motives (Bailey and Grossardt 2005) • Difficult to Gather Relevant Information (Ewing 2001) • Public Unhappiness with Results (Booth and Richardson 2001) • Awkward Methods for Response (Lidskog et. al. 1999) • Public Embarrassment for Agencies (popular press) • Recurring Questions about Legitimacy (Maier 2001) Classic Problems with Unstructured Public Involvement
  21. 21. Structured Public Involvement: Foundational Assumptions We work in a democratic polity and we are dealing with public goods i.e. infrastructure, using public money ($88 billion in 2001, Bureau of Transportation Statistics). Principles of justice apply (Rawls 1971: A Theory of Justice; derived from Von Neumann 1947: A Theory of Games)
  22. 22. Rawls and the ‘Veil of Ignorance’ John Rawls’ principles of justice Rawls argues that self-interested rational persons behind the “Veil of Ignorance” would choose two general principles of justice to structure society in the real world: 1) Principle of Equal Liberty: Each person has an equal right to the most extensive liberties compatible with similar liberties for all. (Egalitarian.) 2) Difference Principle: Social and economic inequalities should be arranged so that they are both (a) to the greatest benefit of the least advantaged persons, and (b) attached to offices and positions open to all under conditions of equality of opportunity.
  23. 23. John Rawls’ Principles of Justice/Fairness Everyone has the same minimum set of liberties that do not invalidate anyone else’s same right. Inequalities must meet two conditions: everyone is equally likely to be subject to them, and they must provide the greatest benefit to the least advantaged. (Maximin) Distributive Aspect Ratio of positive and negative impacts Inherent property of public infrastructure and design Environmental Justice Procedural Aspect Methods by which decisions are made. Access Aspect Who is included in decision-making process.
  24. 24. Justice Problem • Distributive Justice is inherently unattainable in transportation (and many other) infrastructure projects. • SPI seeks to deliver Procedural and Access Justice to mitigate Distributive Injustice.
  25. 25. Methodological Implications This means in the context of Structured Public Involvement 1. Soliciting participation from all representative stakeholder groups and public. 2. Identifying and including all criteria of significance to all parties. 3. Establishing an agreed-upon weighting scheme for criteria among stakeholder groups. 4. Using geovisual/geospatial methods as part of a participatory decision support system 5. Facilitating participation of disadvantaged groups through distributed outreach. 6. Revisiting all groups with interim conclusions to allow iterative evaluation.
  26. 26. Functional Process • Accommodate large numbers of participants. • Give each equal voice. • Make them anonymous, independent, and diverse. • Explain general problem clearly. • Solicit their input efficiently, transparently. • Have a process that fits the input into decision process. • Do it rapidly. – (Send them home in 2 hours or less.)
  27. 27. Unit 2: Session Planning, Design and Implementation • What is SPI™? SPI™ performance • Group Process Design: Questions and Polling • Representation Strategies • Decision Support Tools
  28. 28. Representation Decision Modeling Group Dialogic Methods Structured Public Involvement (SPI)
  29. 29. What is Structured Public Involvement or SPItm SPItm delivers high performance evaluations from stakeholders, project sponsors and professionals. It streamlines public involvement, reduces process irregularity and increases defensibility and sustainability of decisions. It does so because it is theoretically strong and it has been improved over ten years of applications. 25-33% of performance of SPI is derived from the use of the electronic polling system; what about the rest?
  30. 30. How do we achieve these goals? Structured Public Involvement: preparation is critical The public sees this….
  31. 31. • Kentucky Transportation Cabinet (Planning, Environmental, Districts) • Indiana DOT • Arizona DOT (pilot study) • FHWA : TCSP, FTA, NCHRP • National Science Foundation • National Academies of Science • Michael Baker Jr. Inc. • Wichita State U. • LexTran (Lexington) • Transit Authority of River City (Louisville) • Bluegrass ADD • Jeffersonville, IN • Woodford County, KY • Jessamine County, KY • Parsons Transportation • Lochner and Associates • Wilbur Smith and Associates • Lardner-Klein Landscape Architects • Burns and McDonnell Engineering Some SPI Partners
  32. 32. Project Manager, State Transportation Agency (Bridge project 2005-07) “For the state of Kentucky, as owner of the bridge, the polling process proved to be an efficient way to get the thoughts from the public that we were after. Lead engineer (Bridge project, 2007) “The polling process used in the Louisville Bridge project gave us more specific feedback than ever before…This way, more vocal contingents at public meetings can’t dominate the debate. People get excited about it, because they see that their participation is real.” Resident of minority neighborhood (Transit-Oriented Development, 2002) “I’ve never seen this level of public involvement before” Resident of minority neighborhood (Transit-Oriented Development, 2002) “I wish my neighbors were here” Resident of retirement community (Noisewall Design 2006) “Thank you. Your team is doing a good job” Evaluation and commentary from clients, partners, project managers and citizens
  33. 33. Federal official (Bridge project 2005-07) “I had never been through a process using this type of activity. This was very transparent, very open, available to all stakeholders. There’s a lot more credibility from the public’s perspective this way.” Federal official (Bridge project 2005-07) “We were very impressed. The polling process gave a true picture of what the public liked and didn’t like and the final designed reflected that. We thought the process was excellent.” “I was amazed by how accurately this process predicted the public’s wishes.” “When you see members of the public after they’ve seen their comments incorporated, they’re excited. There’s a sense among them that, ‘I counted.’” Evaluation and commentary from clients, partners, project managers and citizens
  34. 34. SPI Stakeholder satisfaction evaluations 0 1 2 3 4 5 6 7 8 9 10 Rural Highw ay improvement (KY, 2000) Transit Oriented Development (KY, 2002) Noisew all Design (KY, 2004) Noisew all Design (AZ, 2006) Bridge AAT (KY, 2005) Bridge Meeting 1 (KY, 2005) Bridge Meeting 2 (KY, 2005) Bridge Meeting 3 (KY, 2005) Bridge Meeting 4 (KY, 2005) Bridge Meeting 5 (KY, 2005) Land Use Planning (KY, 2005) Bypass study (KY, 2008) Bridge Meeting (KY, 2007) Bridge Meeting (KY, 2007) Mean satisfaction with SPI Processes
  35. 35. Structured Public Involvement Design Process How to convert principles of SPI™ into action
  36. 36. Structured Public Involvement Design Process Using Casewise Visual Evaluation
  37. 37. BRIDGE DESIGN AESTHETICS 1
  38. 38. 2
  39. 39. 3
  40. 40. 4
  41. 41. Vote For Your Favorite Bridge Choice One Choice Two Choice Three Choice Four 0% 0%0%0% 1. Choice One 2. Choice Two 3. Choice Three 4. Choice Four
  42. 42. 1
  43. 43. How Suitable Is... Bridge 1 Very Unsuitable ... ... ... So-So ... ... ...Very Suitable 0% 0% 0% 0% 0%0%0%0%0% 1. Very Unsuitable 2. ... 3. ... 4. ... 5. So-So 6. ... 7. ... 8. ... 9. Very Suitable Mean =
  44. 44. 2
  45. 45. How Suitable Is... Bridge 2 Very Unsuitable ... ... ... So-So ... ... ...Very Suitable 0% 0% 0% 0% 0%0%0%0%0% 1. Very Unsuitable 2. ... 3. ... 4. ... 5. So-So 6. ... 7. ... 8. ... 9. Very Suitable Mean =
  46. 46. 3
  47. 47. How Suitable Is... Bridge 3 Very Unsuitable ... ... ... So-So ... ... ...Very Suitable 0% 0% 0% 0% 0%0%0%0%0% 1. Very Unsuitable 2. ... 3. ... 4. ... 5. So-So 6. ... 7. ... 8. ... 9. Very Suitable Mean =
  48. 48. 4
  49. 49. How Suitable Is... Bridge 4 Very Unsuitable ... ... ... So-So ... ... ...Very Suitable 0% 0% 0% 0% 0%0%0%0%0% 1. Very Unsuitable 2. ... 3. ... 4. ... 5. So-So 6. ... 7. ... 8. ... 9. Very Suitable Mean =
  50. 50. 0 0.2 0.4 0.6 0.8 1 How Suitable Is...
  51. 51. Basics of Questions and Polling • Nature of Question Should be Clear – Cost versus Appeal versus Other Factors? • Avoid “Yes-No” Questions – Use Continuous Scale – Use Multiple Criteria • Input is Usually Evaluative, Not Decisional – Contributes to Overall Project in Specific Way – ‘Partnership’
  52. 52. Scoring Summary and Standard Deviation by Groups
  53. 53. Representation Strategies • Goal is to Assure Competent Responses from Group • May Use Data, Photos, Videos, GIS, etc. • Use Minimum Necessary to Achieve Good Feedback • Save Sophisticated Expensive Material for Proper Time: Detailed Work, Fine Distinctions
  54. 54. Item: Image 1 Positives - Looks like Bardstown road, the openness, trees, plaza is neat with the commercial, mixed use, it fits the neighborhood, the brickwork, Multi-Use, Green space, Pedestrian Friendly, Nice Blend of Old & New Negatives - Like to see more brick, narrow street, parking availability, traffic looks tight, Where is the rail? First Vote: Second Vote:
  55. 55. 7.8
  56. 56. Example: Community Planning
  57. 57. Green Space Single Family Townhouses Multi - Family Commercial Mixed - Use Scenario 10
  58. 58. Scenario 10
  59. 59. Decision Support Modeling • How Does Data Become Incorporated Into Project? • Simple Comparative Scoring • Multiple Criteria-Weighted Evaluations • Used to Feed Spatial Analytic Tools to Answer ‘Where’ Questions • Used to Feed/Generate Robust Models of Group Preference
  60. 60. Innovative Decision Support Tools • Analytic Hierarchy – Allows Limited Preference Analysis Data to be Comparatively Organized – Useful for Ranking Large Sets of Complex Items • Eg. Multiple data layers in GIS • Fuzzy Set Analysis – Allows Preference Data for a Small (5-10%) Subset to Inform Preference for the Remainder of the Solution Domain – Adapted for Sparse Data and Non-Linear Multi-Variable Problems – Allows Complex Problems to be Covered by Analyzing Small Portion of Hundreds of Possible Solutions
  61. 61. Dress This Man 2 Jackets x 3 pants x 2 shirts x 3 ties = 36 combinations
  62. 62. 5 3 3 3 3 5 3 1 1 3 5 7 5 1 3 8 7 5 3 3 9 8 5 3 3 CAsewise Visual Evaluation (CAVE) Decision Support LOW LOW HIGH HIGH
  63. 63. Following Modules: • Land Use • TOD Design • Routing Problem • Major Bridge Design • Nuclear Industrial Cleanup and Re-Use
  64. 64. Example: Community Planning
  65. 65. Planning Problem • How do people’s judgments articulate with different “kinds” of developments? • Distinguishing Properties of Developments? – Housing Mix – Land Use Mix – Walkability – Street Network Connectivity – Greenspace
  66. 66. Green Space Single Family Townhouses Multi - Family Commercial Mixed - Use Scenario 1
  67. 67. Scenario 1
  68. 68. Green Space Single Family Townhouses Multi - Family Commercial Mixed - Use Scenario 10
  69. 69. Scenario 10
  70. 70. Describing Development Patterns Parameters Value and Meaning Low Medium High Mix of Housing Types 80-100% Single Family Detached 70-80% SFD App. 50% SFD Mix of Land Uses 0-10% Commercial/ Retail 10-20% C / R 20-30%+ C / R Proportion of Greenspace 0-4% Total Area, excluding pavement 5-10% of Total Area 11-15% + of Total Area Non-Auto: Ratio of Sidewalk Area to Roadway 0-10% of Surface is Sidewalk 11-20% of Surface is Sidewalk 20-30% of Surface is Sidewalk Connectedness: Avg. # of Intersection Spokes (3-4) 3 - 3.1 3.1 – 3.3 3.3 – 3.6
  71. 71. Mix Housing Types Mix Building/Land Use Greenspace Walkability Street Connectivity LOW MED HIGH LOW MED HIGH LOW MED HIGH LOW MED HIGH LOW MED HIGH 1 x x x x x 2 x x x x x 3 x x x x x 4 x x x x x 5 x x x x x 6 x x x x x 7 x x x x x 8 x x x x x 9 x x x x x 10 x x x x x 11 x x x x x 12 x x x x x Some Possible Development Patterns
  72. 72. Housing Mix (HOU) = Var Land Use Mix (BLU) = Var Greenspace (GRN) = Low Sidewalk Ratio (ACT) = Low Street Connectivity (CON) =Low 1 Low High High Low High
  73. 73. Housing Mix (HOU) =Var Land Use Mix (BLU) = Var Greenspace (GRN) = Low Sidewalk Ratio (ACT) = High Street Connectivity (CON) =Med 9
  74. 74. Housing Mix (HOU) = Var Land Use Mix (BLU) = Var Greenspace (GRN) = Med Sidewalk Ratio (ACT) = High Street Connectivity (CON) =High 4
  75. 75. TOD Design
  76. 76. Architects’ Design Language Height: (L, LM, M, MH, H) Low-rise, low-medium, mid-rise, medium-high, high-rise Typology: (C, L, B, A) Courtyard, linear, block, assembly of parts Density: (L, M, H) Low, medium, high Open space: (S, P, C) Sidewalk, public plaza, central courtyard
  77. 77. Item: Image 1 Positives - Looks like Bardstown road, the openness, trees, plaza is neat with the commercial, mixed use, it fits the neighborhood, the brickwork, Multi-Use, Green space, Pedestrian Friendly, Nice Blend of Old & New Negatives - Like to see more brick, narrow street, parking availability, traffic looks tight, Where is the rail? First Vote: Second Vote:
  78. 78. Item: Image 10 Positives - Playground (residential), Patios & Balconies Negatives - Looks disposable, Parking detracts, Too plain, Lacks Arch detail First Vote: Second Vote:
  79. 79. First Scoring
  80. 80. Second Scoring
  81. 81. Output Preference Surface: Height v Density
  82. 82. 7.8
  83. 83. Routing Problem
  84. 84. New Transmission Line: Somerset to London
  85. 85. New Transmission Line: Somerset to London
  86. 86. Real-time Data Collection
  87. 87. Real-time Data Collection
  88. 88. Landscape Features Subject to Physical Damage • Wildlife management area • National Forest • Wetland • Archaeological feature • Prime farmland • Springs • Streams • Sinkholes • Caves • High poverty levels • Indian tribe land • National and State Park • Cemetery
  89. 89. Significance for Physical Damage: Power and Non-Power ProfessionalsSubject to Physical Damage 0 5 10 15 20 25 30 W ildlife m anagem entareaN ationalForest W etland ArchaeologicalfeaturePrim e farm land Springs Stream s Sinkholes C aves H igh poverty levelsIndian tribe land N ationaland State Park C em etery Global Impedance Values Power Professionals' Impedance Values Non-Power Professionals' Impedance Values
  90. 90. Features Subject to Visual and Proximity Impacts • Human Habitation • School • National Properties Register • Hospital • Church • Wild and scenic river • Public campground • Threatened and endangered habitat • Picnic area • Golf course
  91. 91. Non-Point Features • Electric Fields • Magnetic Fields • Radio Frequency Interference • Audible Noise • Visual Impacts 300 200 100 0 100 200 300 0 2 10 4 4 10 4 6 10 4 8 10 4 0.001 0.0012 0.0014 Distance -Feet Magnetic-Field(m-T) BCP d 0( ) BCE d 0( ) BC d 0( ) d
  92. 92. Significance for Visual / Proximity Impacts: Power and Non-Power Professionals 0 5 10 15 20 25 30 Human Habitation School National Properties Register Hospital Church Wild and scenic river Public campground Threatened and endangered habitat Picnic area Golf course Global Impedance Value Power Professionals' Impedance Non-Power Professionals' Impedance
  93. 93. Features Affecting Constructability • Strip or shaft mines • Public water supply • Airport • Sewage treatment • Pipeline • Railroad • Dams • Powerline crossing • Hazmat site • Landfills • Military installation • 15 - 25% slope • 10-15% slope • 5 - 10% slope • Rock base • Water tower • Oil and gas wells • Water treatment station • Mixed/unknown base • Floodplain • Soil resistance • Forested • High land cost • Lightning risk • Radio or TV tower • Superfund or other EPA Project Site • Bodies of water e.g. river, lake
  94. 94. Construction Costs Construction Feature Multiply base cost by Angle of turn 16-30o 1.1 30-90o 1.2 Grade 5-30% 1.0 + grade(%)/100 Vegetation Light forest (accessible by truck) 1.05 Heavy forest (not accessible by truck) 1.2
  95. 95. Most Important Landscape Features Airport Superfund or other EPA Project Site Military installation National and State Park Hazmat site Threatened and endangered habitat Strip or shaft mines Oil and gas wells Wild and scenic river
  96. 96. Important Landscape Features Archaeological feature National Properties Register High land cost Bodies of water Dams National Forest School Wetland Radio or TV tower Landfills Wildlife area 15 - 25% slope
  97. 97. Reverse Viewshed Analysis
  98. 98. Visualization Source: DOE/EIS-0325, Jan. 2003
  99. 99. Impact of Color Value on Visual Impact
  100. 100. Color + Complexity
  101. 101. Color + Simplicity
  102. 102. Nuclear Industrial Site Cleanup and Re-Use
  103. 103. TVA WKWMA DOE DOE leased to WKWMA DOE Security fence
  104. 104. PGDP Future Vision Process Stakeholder Interviews CBPC SPI Stakeholder Community Meeting (s)Stakeholder Focus Groups Future Vision Advisory Panel (Representatives Drawn from Stakeholders) UK/KRCEE Assessment Protocol/ Scenario Triggers Scenario Matrix Community Future Vision Community Based Participatory Communication (CBPC) Structured Public Involvement (SPI) Community Preference Model Review Refinement Review Refinement Review Refinement Data/ Technical Support Data/ Technical Support Data/ Technical Support Input/Feedback Input/Feedback Input/Feedback Case wise Visual Evaluation (CAVE)
  105. 105. Example Scenario Matrix Future Vision Categories Scenario 1 Scenario 2 Scenario 3 Scenario 4 Land Use a. Nuclear Industry : z. Residential Apartments Waste Disposal a. On-site b. Partial c. Off-site Groundwater a. Water Policy & Active Treatment : z. Monitoring & Enhanced Inst. Controls Surface Water a. Monitoring : z. Sedimentation Basins/Removal
  106. 106. Example Scenario Fact Sheet Impacts: Health Economic Environmental Trends: Energy Needs Economic Environmental Uncertainties: Funding Regulations Demographics
  107. 107. Structured Public Involvement Future Vision Scenarios Fact Sheets Future Sate Visualizations Future State Visualizations Discussion Vote on Scenarios
  108. 108. CAsewise Visual Evaluation (CAVE) Fuzzy Knowledge Builder Optimal Solution 5 3 3 3 3 5 3 1 1 3 5 7 5 1 3 8 7 5 3 3 9 8 5 3 3 Sampled Scenarios Modeled Scenarios Selected Scenario(s)
  109. 109. Myths of Public Involvement 1. “difficult to have consensus without leadership” (CORP speaker, May 2007) 2. “without leadership participation is impossible” (CORP speaker, May 2007) 3. “the public are uninformed” (CORP panelist, Feb 2004) 4. “in this environment, it is impossible to involve people” (CORP speaker, May 2007) 5. “people will never be satisfied” (Planner, 2005)
  110. 110. Myths about Public Involvement in Planning “in this environment, it is impossible to involve people” (CORP speaker, May 2007). It is only impossible if there is no analytic method or if the will to include citizens is lacking. Citizen preferences and professional design practice must be brought into genuine dialog: even if it is ideologically unpalatable to professionals.
  111. 111. Myths about Public Involvement in Planning “the public are uninformed” (CORP panelist, Feb 2004) The public may not have expert knowledge of structural properties, but they know their cultural, visual and financial preferences. In democratic societies where public money is being spent, this claim should not be used to exclude their participation. Their opinion should be respected to the greatest feasible extent.
  112. 112. Myths about Public Involvement in Planning “without leadership, participation is impossible” (CORP speaker 2007) Participation occurs without political or professional leadership. However, tame participation, i.e. participation that agrees with expert opinion, is only possible through a certain kind of leadership.
  113. 113. Myths about Public Involvement in Planning “people don’t know what they want” (Planning meeting participant, 2006) People’s preferences appear opaque because they aren’t being asked…..or because they’re not participating because they’re not being listened to….or because the professionals lack analytic methods to help them understand what people mean.
  114. 114. Myths about Public Involvement in Planning “difficult to have consensus without leadership” (CORP speaker, May 2007) Consensus is not a useful goal in large-scale planning projects. Achievement of consensus is only possible through deployment of power: silencing of opposing views, exclusion of certain groups from participation. Does nonconsensual planning mean morally or practically inferior planning?
  115. 115. • “..there has been little attempt to develop [more general] theories within the context of transportation projects, possibly because systematic public involvement is a relatively recent development in this field.” (Barnes and Langworthy 2004:8-9) Methodological Suggestions from Transportation Literature
  116. 116. • “..there has been little attempt to develop [more general] theories within the context of transportation projects, possibly because systematic public involvement is a relatively recent development in this field.” (Barnes and Langworthy 2004:8-9) Methodological Suggestions from Transportation Literature
  117. 117. Methodological Suggestions from Transportation Literature
  118. 118. Methodological Suggestions from Transportation Literature

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