Benjamin L. Blandford

Planning, Technology, and Legitimacy: Structured Public Involvement in Integrated Transportation and Land-Use Planning in the United States

The authors have measured an Arnstein gap, that is, a significant difference between desired and actual levels of citizen participation in planning processes. This Arnstein gap exists because even well-intentioned professionals have an unrealistic expectation of achieving consensus across large planning scales. Further, it is often hoped or believed that technologies of representation will somehow accomplish consensus. The authors argue this is not possible without developing a stronger theoretical framework for their deployment in planning in democratic societies. The purpose of this research is to move the public closer to the center of the public infrastructure planning and design process in a productive, efficient, and more satisfactory manner, that is, to close the Arnstein gap. The authors adapt a participatory framework, called structured public involvement (SPI), for integrating visualization and geospatial technologies into large-scale public involvement in planning domains. The authors discuss how SPI using the casewise visual evaluation method is applied in collaboration with planners. A case study is presented of integrated transportation and land-use planning for an Indiana city. The results demonstrate that SPI achieves high levels of stakeholder satisfaction in addition to providing high-quality planning and design guidance for professionals.

Casewise Visual Evaluation for High-Performance Collaborative Visioning of PGDP Nuclear Enrichment Plant End State

This article describes the adaptation of the authors’ Structured Public Involvement, or SPI, framework for community involvement in the end-state visioning process for the PGDP facility. The SPI framework is designed to elicit community values and provide access to these as a decision support system for the development of feasible, legitimate, and durable end-state management plans. This SPI protocol is designed around community evaluation of visualizations. Key properties of visual evaluation methods for large group visualization are discussed and the Casewise Visual Evaluation method is outlined. CAVE uses a fuzzy logic based neural network modeling approach to build a knowledge base for community preferences across all feasible end-state scenarios. The potential PDGP end-state land-use properties developed from focus group work are integrated into a sample range of dynamic visualizations and the sampling protocol is described. Preliminary results will be presented at the conference.

Integrated Transportation and Land Use Scenario Modeling by Visual Evaluation of Examples: Case Study of Jeffersonville, Indiana

Transportation and land use planning are generally poorly coordinated, and the preferences of the general public are not well integrated into either activity. Appropriate land use patterns that meet the needs and desires of the public and the public sector are difficult to develop because of their extreme complexity and potential for disproportionate impacts on citizens. A structured public involvement protocol was developed to allow large groups of citizens to participate efficiently and effectively in the comprehensive planning process for a moderate-sized town in Indiana and to help in partially overcoming this problem. CommunityViz was used as the visualization tool to help residents understand better the differences between potential land development patterns. Fuzzy set modeling was used to derive the complex interplay of development pattern properties that were most and least preferred by citizens. The development patterns varied by percentage mixture of housing types, percentage mixture of land use types, percentage given over to greenspace, ratio of sidewalk to total paved area, and connectivity of the road network. These five parameters were chosen as the most useful and fundamental measures of differences between development patterns. Citizens’ preferences were derived on that basis. Public input for this town was successfully modeled. Resulting preference patterns were made available to city planners for use in updating their comprehensive plan. This research demonstrates a practical way to involve citizens in an orderly, useful manner in questions of joint transportation and land use planning.

Snow and Ice Removal Route Optimization in Kentucky

This research describes a geographic information system-based methodology developed for the Kentucky Transportation Cabinet (KYTC) to improve the efficiency of Kentucky’s snow and ice removal progr...

Transportation System Vulnerability and Resilience to Extreme Weather Events and Other Natural Hazards Report for Pilot Project - KYTC District 1

This researchs objective is to assist the Kentucky Transportation Cabinet (KYTC) in its efforts to develop strategies to address natural hazard vulnerabilities and improve the resiliency of Kentuckys transportation infrastructure. Recent federal legislation calls for state transportation agencies to develop a risk-based asset management plan for National Highway System (NHS) assets that includes consideration of natural hazards. Similarly, the Federal Highway Administration (FHWA) calls for state transportation agencies to identify potential vulnerabilities associated with extreme weather events and climate change, and to incorporate these findings into transportation planning, design, and maintenance practices. This report consists of two parts: (1) An overview of vulnerability assessments and natural hazards for KYTC. This is intended to inform and guide transportation system vulnerability assessments for Kentucky. (2) Pilot vulnerability assessment for the NHS in KYTC District 1. The District 1 pilot adopts a framework for conducting the assessment for particular locations. Lessons learned from the District 1 pilot project will direct future assessments in the remaining KYTC districts.

An Intermodal Network Model of Coal Distribution in the United States and Its Economic Implications for the Inland Waterway System

This paper describes a geographic information system (GIS)-based intermodal network model for the shipment of coal in the United States. The purpose of this research was to investigate the role played by railways, waterways, and highways in the movement of coal from its source area to point of use, and to highlight the implications these movements have for the U.S. economy. The project team modeled coal movements across the U.S. intermodal transportation network using the Energy Information Administration’s 2010 data, which provided detailed origin, destination, primary mode, and volume information for coal shipments. The model identifies the optimum routes for coal shipments based on a rate structure that accounts for the relative costs of shipping by each of the modes. The model, as well as available statistics, reveals the dominance of coal mined from the Powder River Basin. Compared to other sources— principally, the Appalachian Basin — coal from Mountain West is significantly less expensive, thus giving it a significant comparative advantage. Both Texas and Illinois, the two largest coal consumers by state, obtain virtually all of their coal from the West or from within state. Appalachian Basin coal serves domestic and export markets primarily in the East and Southeastern U.S. Only the Ohio River provides significant movement of Central Appalachian Basin coal to the west and south. Although this modeling relies on 2010 data, a look at more recent trends in coal prices and mining indicate that the Powder River Basin continues to dominate, while production and industry employment have steadily declined in the Appalachian Basin. The shift away from coal and toward natural gas as a primary energy source argues for the region’s coal extraction industries remaining in a depressed state, which could produce negative economic consequences for transportation industries. Carrier and port facilities will need to adopt a more diversified shipping portfolio to accommodate for these losses. It is possible that the loss of coal will open up opportunities for other commodity shipments on the inland waterways. This modeling demonstrates the potential for such integrated models to accommodate energy-related or similar data, and serves as a tool for freight planners in identifying energy transportation corridors of significance. It could potentially be used to analyze the movement of other commodities, which could let industry stakeholders identify new markets to tap into. Further, the model and analysis can help inform Moving Ahead for Progress in the 21st Century Act (MAP-21) related efforts to develop a National Freight Network and National Freight Strategic Plan.

Intermodal Network Model of Coal Distribution in the United States

This paper describes an intermodal network model based on the geographic information system for the shipment of coal in the United States. The research contributes to a better understanding of a portion of the energy transportation system and how rail, water, and highway are integrated to deliver energy goods. Coal movements were modeled across the network with the Energy Information Administrations 2010 data, providing detailed origin, destination, primary mode, and volume information for coal movements in the United States. The model identifies the optimum routes for coal shipments on the basis of a rate structure that accounts for the relative costs of shipping by each of the modes. The model results reveal the wide distribution of Powder River Basin coal, with a market area that reaches across the West and the Midwest. Both Texas and Illinois, the two largest coal consumers by state, derive virtually all their coal from the West or from within state. Appalachian Basin coal serves domestic and export markets primarily in the east and southeastern United States. Only the Ohio River provides significant movement of Central Appalachian Basin coal to the West and the South. The presented research demonstrates the potential for integrated models to accommodate energy-related or similar data. The model is a tool freight planners can use to identify energy transportation corridors of significance. Results from this model can inform efforts related to the Moving Ahead for Progress in the 21st Century Act for developing a national freight network and a national freight strategic plan.

Expert Systems Model for Kentucky Arrow Darter Habitat in the Upper Kentucky River Basin

This study presents a geographic information system (GIS)-based predictive habitat suitability model for the Kentucky arrow darter (Etheostoma spilotum), a fish species of the upper Kentucky River system that is a candidate for federal listing by the U.S. Fish and Wildlife Service. Five habitat factors were identified by experts for modeling the habitat: gradient, canopy coverage, land cover, riparian zone width, and stream order. Using a GIS, values for the five habitat factors were calculated and then combined for all stream segments of the upper Kentucky River system at 100-m intervals. Habitat factor combinations were assigned an overall habitat suitability rating using a weighted calculation system derived through input from aquatic biologists. The resulting model was tested against presence data using locational modeling statistics. A total of 97.33 percent of occurrences were located in the two higher rated categories of habitat suitability. Only two occurrences were located on stream segments of the two lower rated categories of habitat suitability, and neither of these were in the lowest rated category. Whereas model accuracy was high, model precision was moderate, as 61 percent of stream segments were categorized by the model as suitable habitat.

A GIS-Based Expert Systems Predictive Habitat Model for Threatened and Endangered Species: Case Study Using Kentucky Arrow Darter

This study presents a Geographic Information Systems (GIS)-based predictive habitat suitability model for the Kentucky arrow darter (Etheostoma spilotum), a fish species of the upper Kentucky River basin that is a candidate for federal listing by the U.S. Fish and Wildlife Service. The model is based on previous work: the development of a similar predictive model for identifying the habitat of the blackside dace, a threatened minnow species of the upper Cumberland River basin in Southeastern Kentucky. The research describes a weighted, rules-based system which incorporates expert knowledge about habitat preferences for the arrow darter. For this model, five habitat factors were identified by experts as essential to modeling the habitat: stream gradient, canopy coverage, land cover, riparian zone width, and stream order. Using a GIS, the five habitat factors were parameterized and combined across the entire Kentucky River basin stream network. Experts evaluated combinations of habitat factors to determine habitat suitability. Using locational modeling statistics, the resulting model was tested against known Kentucky arrow darter occurrences. The analysis demonstrated successful identification of streams where the arrow darter was likely — and unlikely — to exist. Model results could be useful to transportation planners, particularly when determining sensitive landscape that could be impacted by transportation planning processes. This model may help planners save money on habitat mitigation when transportation initiatives take place in known unsuitable arrow darter habitats. A GIS model similar to the one developed in this study may be applicable to other endangered species.

Integrated Freight Network Model: A GIS-Based Platform for Transportation Analyses

The models currently used to examine the behavior transportation systems are usually mode-specific. That is, they focus on a single mode (i.e. railways, highways, or waterways). The lack of integration limits the usefulness of models to analyze the intermodal movement of freight. This project developed a geographic information system (GIS)-based model of the three primary surface modes as well as intermodal connections. The resulting Integrated Freight Network Model (IFNM) accommodates highly detailed information about shipping costs, transfer costs, traffic volumes (including non-freight auto traffic), and network interconnectivity properties. As a proof of concept, the research team conducted an exploratory analysis that asked what the potential impact would be to Kentucky highways if approximately half of the freight currently transported by barges on the Ohio River were shifted onto trucks. Coal-haul roads in the northeastern and western part of Kentucky would be particularly hard hit by a broad scale modal shift. The IFNM highlighted that roads emanating from the Western Coalfields would experience explosive growth in freight transport, with the proportion of trucks relative to overall traffic significantly increasing. Applying the IFNM to a range of freight-related transportation questions could greatly enhance system efficiencies and positively impact local economies and environments.