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.

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.

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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.

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 program. The state’s program uses a system of snowplow routes that must factor in the location and attributes of trucks, facilities, materials, and roadways. Although functionally effective, the program had never been evaluated for efficiency. Researchers at the Kentucky Transportation Center used ArcGIS to assess the performance of KYTC’s current snowplow routing procedures and identify strategies for optimizing them. The research established optimized routings for four counties located in two of the state’s highway districts. Esri’s Network Analyst and the vehicle routing problem toolset were used for this process. Early models were county-based, meaning that trucks were assigned to routes within counties based on truck type and route priority. These early models achieved some optimization but it was limited and routes were overly complex. In subsequent models, researchers devised more optimal results by modeling routes at the multi-county or district level. These successful models eliminate nine snowplow trucks across four counties, resulting in savings of US$225,000 per year. In addition to cost savings, optimizing the routing system can improve efficiency, increase safety, and reduce the amount of time needed to treat roadways. This report documents the challenges, successes, and lessons learned from this research. Specific examples are provided to demonstrate the advantages of route optimization. Subsequent research will expand upon the four successful counties and attempt to optimize snow and ice removal throughout the state.