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.

Environmental justice (EJ), in the form of distributional justice, is mandated by a 1994 Executive Order. However, EJ is not easily achieved. EJ research can be divided into identification and mitigation strategies. EJ mitigation strategies intersect with public involvement, which in transportation has a long, and often controversial, history. This paper examines how a philosophy based on John Rawls’ theories of procedural justice and access to justice can address the need to achieve distributional justice. To improve procedural justice, the authors examine how effective large-group processes can deliver high-performance public involvement. Methodological barriers and the role of technologies such as electronic polling and visualization are discussed. The authors propose four process metrics for public involvement. On the basis of data on structured public involvement projects, the authors argue that such processes enhance procedural justice and thereby address specific EJ aims. These data illustrate that realizing this potential improvement will require a philosophical shift to a higher Arnstein ladder level, the identification and use of appropriate methodologies for involving large groups, and the integration of their valuations into effective decision support systems.

Subject to engineering constraints, bridges should present a pleasing visual aspect to their user communities. The research team extended its structured public involvement (SPI) protocol using casewise visual evaluation (CAVE) to the field of context-sensitive large-scale bridge design. The context-sensitive design process was used for Section 2 of the Louisville Southern Indiana Ohio River Bridges project. Key design parameters including bridge type, height, symmetry, complexity, and tunnel effect (superstructure shape) were identified by bridge designers. During a 3-month period, an SPI protocol was used to determine community preferences from Kentucky and Indiana participants. Group preferences were gathered rapidly, anonymously, and fairly from a focus group by using electronic polling technology to evaluate potential designs. A preference model was built by using CAVE, and a range of nonlinear preference variations relative to the design parameters was investigated. The favorable public evaluation results of the SPI process using CAVE are presented, and the reasons for its high performance are discussed. Emphasis is placed on the need for a close collaboration between bridge designers and public involvement specialists. The project demonstrates how an analytic approach to public involvement that integrates technology into the dialogic relationship between designers and the public allows for the achievement of inclusive, successful context-sensitive design even for large, complex infrastructure projects.

The conservation of stream biodiversity requires more explicit knowledge on the distribution of aquatic species within the context of their specific environmental settings and stresses. Although species distribution models (SDMs) have been widely used for organisms occupying contiguous spatial extents, the implementation of SDMs in relatively complex and segmented riverine networks is still at its early stage. In this study, we explicitly modelled the headwater stream habitat for the threatened blackside dace (Phoxinus cumberlandensis) endemic to the upper Cumberland River, Kentucky, USA. An occurrence record data set, along with variables describing stream properties and land use impacts, was used to predict the fish habitat suitability at the stream segment level. An approach combining geographic information systems and the maximum entropy species distribution modelling (MaxEnt) was adopted. Results demonstrated that natural conditions and land use disturbances, respectively, form the primary and secondary environmental constraints on the species' habitat. We generated regional‐scale management‐friendly maps showing subwatershed habitat suitability and locations of the clustered suitable habitats (hotspots) and thus set an example for spatially explicit management of threatened and endangered riverine species. This study demonstrates the usefulness of SDMs for stream network–based environments in the facilitation of biogeographic conservation efforts and studies. Copyright © 2012 John Wiley & Sons, Ltd.

Designing highways to influence driver operating speed effectively through environmental feedback is a key research field requiring special attention. Virtual reality video simulations were used to record the influence of environmental elements on driver judgments about the appropriate driving speed. This study evaluated the use of various means that could affect operating speeds and affect driver behavior without compromising safety. Data were analyzed through the fuzzy set nonlinear modeling system of Casewise Visual Evaluation methodology to identify design factors that most strongly influenced perceived operator discomfort. The findings indicated that vegetation type and density and barrier type have a significant effect on driver discomfort and thus have the potential to influence operating speeds. Roadway width has a similar effect where narrower roadways increase driver discomfort. The results indicate that roadside features and certain road design elements can be used to affect driver operating speeds.