risk-based analysis of needs for transportation corridor protection

presented at

SRA 2007 Annual Meeting

presented by

Alexander S. LinthicumDr. James H. LambertCenter for Risk Management of Engineering Systems

website

http://www.virginia.edu/crmes/corridorprotection

December 12, 2007San Antonio, TX

Risk-Based Analysis of Needs forTransportation Corridor Protection

2

Overview

• Introduction

• Background

• Methodology

• Case Study

• Conclusions

Likelihood ofLand Development

Very Low

Low

Med

High

Introduction

4

Motivation

• Over 9000 miles of interstate and primary roads in VA

• Increasing vulnerability to development activity

• Escalating land values affects right of way acquisition

• Desire to avoid unnecessary congestion and costly retrofits

• VDOT must anticipate future development in corridors and take timely action: Corridor Protection– Pre-purchase right-of-way– Obtain easements, developer proffers– Access management

5

Problem Statement

Develop a repeatable, data-driven, GIS-based methodology to identify and

prioritize countywide corridors in need of corridor protection.

Test the methodology in

Fauquier County, VA.

6

Project Steering Committee

Background

8

Corridor Protection

• Potential fiscal and social benefits• Many stakeholders• Methods

– Access management– ROW acquisition

• Legal issues

Sources: (Williams and Frey, 2003; Armour, Rose, Butler, and Waters, 2002; Corridor Capacity Preservation Program, 2002; Stokes, Russell, and Vellanki, 1994; Perfater, 1989; Kamprath and Miller, 2004)

9

Access Management

• Safety• Congestion• Network design• Effects on businesses• HB 2228

Sources: (Plazak and Preston, 2005; Fifth National Conference on Access Management, 2005; NCHRP Synthesis 289, 2000; Bowman and Rushing, 1998; ODOT Access Management, 2004; Williams and Seggerman, 2004; NCHRP Synthesis 337, 2004)

ODOT Access Management Manual

10

Right of Way Acquisition

• Pressure to complete ROW

estimations• Lengthy acquisition process• Uncertainties with damages

and court costs• Uneconomic remnants• Common pitfalls

Sources: (Corridor Capacity Preservation Program, 2002; Barnes and Watters, 2002; Heiner and Kockelman, 2005; Williams, Zhou, and Hagan, 2004;)

http://www.ci.sandy.or.us

11

Risk Assessment and Management

• Risk Assessment (Kaplan and Garrick, 1981)– What can go wrong?– What are the likelihoods?– What are the consequences?

• Risk Management (Haimes, 2004)– What are the trade-offs?– What can be done?– What are the impacts of current decisions on future

options?

12

VAGovernor’s

PreparednessTeam

Methodology

Metrics

Quantitative RiskAnalysis

ComplexityInterconnect-edness

SurvivabilitySystems

Inter- & Intra-dependency

RiskIdentification

CommonDefinition

National Ground

IntelligenceCenter

FBI VDOT

JointProgram

Office

PCCIP

NationalScience

Foundation

DefenseThreat

Reduction Agency

Dept of Homeland

Security

US Army Corp. of

Engineers

US Army

I3P

NASA

Risk Assessment and Risk Management (cont.)

CRMES, 1987-Present

13

Risk Assessment and Risk Management (cont.)

Sources: Lambert and Turley (2005), Lambert et al. (2003), Lambert et al. (2006), Leung et al. (2004), Tsang et al. (2002)

Methodology

15

Overview of Methodology (cont.)

16

Overview of Methodology

CONSTRAINT FACTORS

Public land

Wetlands

Conservationeasements

Ag and forestalDistricts

INDICATORFACTORS

Population &employment

Centers

Vacant &undervalued

land

Transportation

17


18

Overview of Methodology (cont.)• UPLAN: A Versatile Urban Growth Model for Transportation

Planning (Johnston and Shabazian, 2002)

• Characterizing urban land capacity (Landis, 2001)

• Smart Land-Use Analysis: The LUCIS Model (Zwick and Carr, 2007)

• An approach for greenway suitability analysis (Miller et al., 1998)

• Forecasting exurban development to evaluate the influence of land use policies on wildland and farmland conservation (Merenlender et al., 2005)

19


20

Overview of Methodology

CONSTRAINT FACTORS

Public land

Wetlands

Conservationeasements

Ag and forestalDistricts

INDICATORFACTORS

Population &employment

Centers

Vacant &undervalued

land

Transportation

MANAGEMENTFACTORS

Access pointdensity

Landassessment

Utilities

Case Study

22

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections

9. Evaluate Alternatives

5. Scale Factors

1. Define Problem

23

Fauquier County

24

Front Royal

Manassass Park

Manassass

Warrenton

Culpeper

Fredericksburg

Fauquier

Loudoun

Culpeper

Stafford

Warren

Clarke

Prince WilliamRappahannock

US

-17

US-17

-55

-55

I-66

I-66

US-28U

S-2

9U

S-2

9

Fauquier County (cont.)

• Beyond D.C. suburbs• Rural character• Service Districts• Six major corridors

Corridor MilesUS-17 53.8PR-55 18.0I-66 Ramps 5.6I-66 43.8US-211 7.0US-28 13.7US-29 22.2Total 164.1

25


26


• 32,000 Parcels

27

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

28

Data Collection – Fauquier County

• Agricultural and Forestal Districts• National Heritage Resources• Urban Clusters• Parcels• Service District Boundaries• Parks and Schools

– Community Centers– Schools– Sports Complexes– State Parks– County Parks– Natural Areas

• Zoning Districts• Real Estate Assessments

29

Data Collection – Fauquier County

• Water and Sewer Coverage• 5’ Topographic Contours• Flood Areas• Easements

– BoS Commitments & Openspace– Historic Resources– Land Trust of Virginia (LTV)– Marsh Resources, Inc.– The Nature Conservancy– Purchase of Development Rights– Piedmont Environmental Council– VOF Easements & Owned Land

30

Data Collection – VDOT

• Employment locations• USFS National Forests• USPS National Parks• USFWS National Wildlife Refuges• USFWS National Wetlands Inventory• DCR State Natural Area Preserves and Parks• DCR State Forests• DGIF State Wildlife Management Areas• Local Conservation Lands• The Nature Conservancy Preserves• Private conservation lands• Private conservation easements• Environmental concerns / Superfund sites

31

Data Collection – VDOT

• Virginia Six-Year Improvement Program• Scenic Rivers• Scenic Roads• Smoothed Urban Clusters• Smoothed Urbanized Areas• MPO Areas• DoD Military Installations• NPS Scenic Easements• NPS Holding• VOF Openspace Easements• VOF Property• State Public Fishing Lakes• State Scenic Holdings• USFS Scenic Easements

32

Constraint:Protected Parcels

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

33

Constraint: Protected Parcels

ConservationEasements

Parks andSchools

Agricultural andForestal Districts

Source: Fauquier County Department of Community Development; VDOT TPMD

34

Indicator:Parcels Near

Major Corridors

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

35

Indicator: Parcels Near Major Corridors

36


1 mile

.25 mile0.25 miles

37


1 mile

.25 mile

1 mile

0.25 miles

38

Indicator:Parcels Near Intersections

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

39

Indicator: Parcels Near Intersections

Number of IntersectingCorridors

1

2

3

40

Indicator:Parcels Near Population

Centers

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

41

Indicator: Parcels Near Population Centers

42


Source: 2000 US Census

43


Persons / sq mi

0 - 300

301 - 867

868 - 1,834

1,835 - 3,145

3,146 - 5,141

44


Persons / sq mi

0 - 300

> 300

45

Winchester


Network Distance (miles)

5

10

25

40

Culpeper

46

0.011 0.002

0.020 0.348 0.051

0.022

0.002

0.003

0.055

0.047

1.0000.179

0.155

0.005 0.038 0.003

0.013

0.002


47

Indicator:Parcels Near Employment

Centers

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

48

Indicator: Parcels Near Employment Centers

49


Source: Virginia Employment Commission, 2006

2,375

17,500

150

30

5

Employees

50


51

Winchester

Culpeper


52


0.053

0.007

0.038

0.023

0.691

0.015

0.034

0.088

0.024

0.009

0.448

0.137

1.000

0.123

0.093

0.072

0.385

53

Constraint:Economically

UnsuitableParcels

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

54

Constraint: Economically Unsuitable Parcels

Improvement-to-land ratio

> 0.90 Not suitable

<= 0.90 Suitable

55

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

56

Scale Factors: Distance

Priority forCorridor Protection

5 Within 1 mile

10 Within 0.25 mile

57

Scale Factors: Intersections

3 One corridor

6 Two corridors

10 Three corridors

58

Scale Factors: Population Centers

1

2

3

4

5

6

7

8

9

10

59

Scale Factors: Employment Centers

1

2

3

4

5

6

7

8

9

10

60

Scale Factors: Parcels under Restriction

0 Restricted

1 Not Restricted

61

Scale Factors: Economically Unsuitable

0 Economically Unsuitable

1 Economically Suitable

62

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

63

Combine Factors

5 Within 1 mile

10 Within 1/4 mile

+ + + x x

3 One corridor

6 Two corridors

10 Three corridors

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

10

0 Restricted

1 Not Restricted

0 Economically Unsuitable

1 Economically Suitable

INDICATOR FACTORS

CONSTRAINT FACTORS

64

Combine Factors


Very Low

Low

Med

High

65

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

66

Six Fauquier Corridors

PR 55

US 17 US 28

I 66 R US 211

US 29

67

Six Fauquier Corridors

I 66 Ramps - 5.6 miles US 211 - 7.0 miles

ParcelsAcres

(K)Acres

(%)Land Val

($M)Avg Val per Parcel ($K)

Avg Val per Acre ($K) Parcels

Acres (K)

Acres (%)

Land Val ($M)

Avg Val per Parcel ($K)

Avg Val per Acre ($K)

Very Low 536 5.9 30 103 193 17 Very Low 2,649 5.7 50 510 193 89Low 30 1.9 10 16 521 8 Low 70 1.9 16 25 354 13Med 153 4.7 24 65 428 14 Med 167 2.5 22 54 326 22High 667 7.1 36 218 326 31 High 1,196 1.2 11 308 258 250

1,386 19.6 100 402 290 20 4,082 11.3 100 897 220 79

PR 55 - 18.0 miles US 28 - 13.7 miles

ParcelsAcres

(K)Acres

(%)Land Val



Acres (K)

Acres (%)

Land Val ($M)



Very Low 783 12.0 39 167 213 14 Very Low 1,670 4.1 19 225 135 55Low 239 6.8 22 79 332 12 Low 9 0.5 2 6 669 11Med 463 5.5 18 125 271 23 Med 737 10.1 46 128 174 13High 653 6.4 21 209 320 33 High 539 7.2 33 131 244 18

2,138 30.8 100 580 271 19 2,955 22.0 100 491 166 22

US 17 - 53.8 miles US 29 - 22.2 miles

ParcelsAcres

(K)Acres

(%)Land Val



Acres (K)

Acres (%)

Land Val ($M)



Very Low 6,725 27.0 38 1,226 182 45 Very Low 5,515 9.7 32 893 162 92Low 379 11.1 16 126 332 11 Low 371 2.5 8 42 112 16Med 1,182 21.5 30 348 294 16 Med 1,088 11.9 39 266 244 22High 2,218 11.0 16 663 299 60 High 1,323 6.2 20 432 326 70

10,504 70.6 100 2,362 225 33 8,297 30.4 100 1,632 197 54

68

Distribution of Corridor Priorities by AcreParcels within 1 mile of corridor centerline

69

Distribution of Corridor Priorities, Acres per Centerline MileParcels within 1 mile of corridor centerline A.

B.

A.

B.

70

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

Management:Access Point

Density

71

Management Factor: Access Points

I- 66I- 66

US

17

US 50

US 211

US

15

BU

S. U

S 1

5

US 17

US 50

US

17

US

17

PR 28

PR 55

PR 245

PR

215

PR 55

US-17

418 access points

Considerable uncertainty

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72

Management Factor: Access Points (cont.)

!(

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!(

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73

Management Factor: Access Points, US 28

0

2

4

6

8

10

12

14

16

0.5 1

1.5 2

2.5

Be

ale

ton

3.5 4

4.5 5

5.5

Mid

lan

d

6.5 7

7.5 8

8.5 9

Ca

lve

rto

n

Ca

lve

rto

n

10

.5 11

11

.5

Ca

tle

tt

12

.5 13

13

.5 14

Ac

ce

ss

Po

ints

Low Volume Access Points High Volume Access Points

74

Management Factor: Access Points, US 28

0

0.5

1

1.5

2

2.5

3

0.5

1.0

1.5

2.0

2.5

Bea

leto

n

3.5

4.0

4.5

5.0

5.5

Mid

land 6.5

7.0

7.5

8.0

8.5

9.0

Cal

vert

on

Cal

vert

on

10.5

11.0

11.5

Cat

lett

12.5

13.0

13.5

14.0

Pri

ori

ty S

core

0

1

2

3

4

5

6

Nu

mb

er o

f A

cces

s P

oin

ts

Priority Score High Volume Access Points

75

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

Management:Land

Assessment Value

76

Management Factor: Value per Acre, US 28

0

0.5

1

1.5

2

2.5

3

0.5

1.0

1.5

2.0

2.5

Bea

leto

n

3.5

4.0

4.5

5.0

5.5

Mid

land 6.5

7.0

7.5

8.0

8.5

9.0

Cal

vert

on

Cal

vert

on

10.5

11.0

11.5

Cat

lett

12.5

13.0

13.5

14.0

Pri

ori

ty S

core

0

2

4

6

8

10

12

14

16

18

Val

ue

per

Acr

e

Priority Score Value Per Acre (100Ks)

77

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

Management:Utilities

78

Management Factor: Utility Service Areas

Water Sewer

79

2. Collect Data

3. Identify Factors

4. Derive Factors

6. Combine Factors

7. Screen Results

8. Analyze Sections


5. Scale Factors

1. Define Problem

80

Evaluate Alternatives

• Field visits• Context sensitive corridor protection strategies

– ROW Acquisition– Land use controls / concessions– Network design

81

Evaluate Alternatives (cont.)

Discussion

83

Systems Design Process

• Disciplined methodology to approach emerging problems under conditions of uncertainty

84

Risk Assessment and Management• Recognized cross-disciplinary

framework

• Encourages strict problem definition– Risk of unforeseen development– “the transportation and land use

problem”

• Toolbox of risk modeling, assessment, and management techniques

• This thesis applied a conceptual risk framework

85

Suitability Analysis

• Applied to wide variety of problems and scales

• Relevant to predicting land development

• Use of GIS, data availability increasing

• Visual method intuitive, clearly communicates results

86

Challenges

• Suitability analysis model is not yet calibrated

• Scaling and weighting of factors– Roughly right or precisely wrong?

• Likelihood scores are relative and without units

But…

• Demonstrating a process and identifying factors are important research contributions

87

Contributions

• Approached identification of corridor protection needs systemically, including multiple perspectives

• Developed an approach using risk assessment and management and suitability analysis

• Collected and inventoried 80 Virginia datasets

• Identified and derived meaningful constraint, indicator, and management factor

Recommendations

89

Recommendation 1

• Results can effectively be communicated to County Board of Supervisors and Planning Commission

– Reinforce critical need to implement VDOT Safety Improvement Plan for crossovers along US 15/29

– Identify where land use management controls should restrict future access

Source: Rick Carr, Fauquier County, 10/18/2007

90

Recommendation 2

• Identification of what corridor sections should be protected must be followed with how corridor sections will be protected

– Several existing options• Access management• Land use controls• Police powers

– Enabling laws differ from state to state

91

Recommendation 3

• Methodology can assist counties and towns in complying with legislative acts

• HB 3202– Identifying suitability of urban development areas– Identifying Traffic Impact Fee Service Area

• HB2228/SB1312– Developing statewide access management standards

Source: Rick Carr, Fauquier County, 10/18/2007

92

Recommendation 4

• Rappahannock-Rapidan Regional Commission (RRRC) and other PDCs can apply the methodology at the regional level

– Insure more coordinated transportation/land use approach among member jurisdictions

– Provide GIS-based analysis to member jurisdictions that lack staffing capabilities to develop independent studies

93

Recommendation 5

• Methodology is flexible and can accommodate a variety of datasets

• Future efforts may include– Land use and zoning– Functional classification of corridors– Green infrastructure (VDCR)– Transportation infrastructure of additional modes such as

bike and pedestrian, rail, bus, and air– Out-of-county property owners

Source: Project Steering Committee, 10/18/2007; VDOT District Planners, 11/28/2007

Next Steps

95

Next Steps, Academic

• Refine scaling and weighting– Hierarchical Holographic Modeling (HHM)– Analytic Hierarchy/Network Processes (AHP/ANP)

• Expand risk management activities– Management indicators– Costs and benefits– Trade-offs– Visualization techniques

• Calibrate model– Building permits– Zoning amendments

96

Next Steps, Practical

• Repeat method at a regional scale, additional counties

• Refine training materials for new users

• Incorporate additional indicators– Zoning– Non-resident property owners– Building permits

• Explore web delivery options

Conclusion

98

Conclusion

This effort developed

a framework of

risk assessment and management

coupled with suitability analysis

as a method for identifying

protection needs in transportation corridors

99

Overview

• Introduction

• Literature Review

• Methodology

• Case Study

• Discussion

• Recommendations

• Next Steps


Very Low

Low

Med

High

100

Acknowledgements

Chad Tucker – VDOT, Transportation and Mobility Planning DivisionRobin Grier – VDOT, Transportation and Mobility Planning DivisionMarsha Fiol – VDOT, Transportation and Mobility Planning DivisionKim Spence – VDOT, Transportation and Mobility Planning DivisionKatherine Graham – VDOT, Transportation and Mobility Planning DivisionJohn Giometti – VDOT, Culpeper District Planning ManagerPaul Grasewicz – VDOT, Asset Management DivisionMelissa Barlow – VDOT, Asset Management DivisionMary Lynn Tischer – Office of Intermodal Planning and Investment, DirectorWayne Ferguson – Virginia Transportation Research CouncilRick Carr – Fauquier Planning Dept of Community Planning, Director Kimberley Fogle – Fauquier Planning Dept of Community PlanningTalmage Reeves – Fauquier County Dept of Economic DevelopmentKaren Henderson – Fauquier Chamber of CommerceMary Davis – Virginia Economic Development PartnershipJeff Walker – Rappahanock Rapidan PDC, Executive Director

101

Acknowledgements

Ben Mannell, VDOT, Transportation and Mobility Planning DivisionAllison Juarez, Fauquier County GIS DepartmentDan Stell, Fauquier County GIS DepartmentKristen Slawter, Fauquier County Dept of Community PlanningElizabeth Cook, Fauquier County Dept of Community PlanningRick Tambellini, VDOT, Transportation and Mobility Planning DivisionBryan Kelley, VDOT, Transportation and Mobility Planning DivisionIvan Rucker, FHWAChris Gist, UVA Digital Scholars LabYacov Haimes, Center for Risk Management of Engineering SystemsJoost Santos, Center for Risk Management of Engineering SystemsErika Evans, Center for Risk Management of Engineering SystemsKathy Tejano, Center for Risk Management of Engineering SystemsMembers of the Rappahannock Rapidan Regional Commission

Thank You!

James H. Lambert, Associate Director, CRMES

Raster Algebra

104

Raster

What is a raster?

Vector

0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 00 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 000 0 0 0 0 0 0 0 000 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 000 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 00 0 0 0 0 0 00 0 0 0 0 0 0 00 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 00 0 0 0 0 0

0 0 0 00 0 0 0

0 0 0

105

Raster Algebra

3 0 0

0 3 0

0 3

00

0

03

0

0

+3

3

0

0

6

0

=

3

3 3

33

3

106

Raster Algebra

3 0 0

0 3 0

0 3

00

30

03 3

0

0

+

0

20

2 3

0

1

1

1

=

x 1/3 x 2/3

3

107

Raster Algebra

3 0 0

0 3 0

0 33

3 2

0 1

12

11

21 2

2

1

108

University of Virginia Project Team

Jim Lambert

Alex Linthicum

Nilesh Joshi

Elmer Kim

Luke Kincaid

Stephanie Rash

Gavin Schmidt

109

Meetings, Presentations, Data Collection• 02/06/2007 – 1st Steering Committee Meeting, Project Kickoff (Culpeper)

• 03/12/2007 – Fauquier County Dept of Community Planning (Warrenton)

• 03/28/2007 – VDOT Transportation and Mobility Planning Department (Richmond)

• 04/25/2007 – Fauquier County Department of Community Planning (UVA)

• 05/07/2007 – Windshield Survey (Fauquier County)

• 05/17/2007 – 2nd Steering Committee Meeting (Charlottesville)

• 05/24/2007 – VTRC Transportation Planning Research Advisory Committee (Suffolk)

• 08/27/2007 – Fauquier County Dept of Community Planning (UVA)

• 08/30/2007 – VDOT Transportation and Mobility Planning Department (UVA)

• 09/12/2007 – VDOT Transportation and Mobility Planning Department (UVA)

• 10/18/2007 – 3rd Steering Committee Meeting (Culpeper)

• 11/15/2007 – Virginia’s Rural Transportation Planning Program Fall 2007 Workshop

• 11/28/2007 – Joint Planning Managers’ Meeting

• 12/12/2007 – Society for Risk Analysis Annual Meeting (San Antonio)

Alternative Scenarios

111

Considering Economic Suitability


Very Low

Low

Med

High

112

Ignoring Economic Suitability


Very Low

Low

Med

High

risk-based analysis of needs for transportation corridor protection

Documents

risk management cont

risk management haimes

gisbased methodology

smart landuse analysis

future development

presentrisk assessment

need of corridor protection

methodology infauquier