National Center for Smart Growth

Permanent URI for this communityhttp://hdl.handle.net/1903/21472

The National Center for Smart Growth (NCSG) works to advance the notion that research, collaboration, engagement and thoughtful policy development hold the key to a smarter and more sustainable approach to urban and regional development. NCSG is based at the University of Maryland, College Park, housed under the School of Architecture, Planning, and Preservation, with support from the College of Agriculture & Natural Resources, the A. James Clark School of Engineering, the School of Public Policy, and the Office of the Provost.

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Author: search.filters.author.Moeckel, RolfSubject: search.filters.subject.Transportation

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Now showing 1 - 4 of 4
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    Gradual Rasterization: Redefining the Spatial Resolution in Transport Modeling
    (2014) Moeckel, Rolf; Donnelly, Rick
    Finding the appropriate spatial resolution in modeling is a serious challenge at the beginning of every modeling project. The paper presents a methodology to adjust the spatial geography to the resolution of a network. Based on the quadtree algorithm, raster cells are generated that are dynamic in size. Smaller raster cells are used in urban areas and larger raster cells are used in low-density, rural areas. Trip tables of a travel demand model for the State of Georgia are disaggregated to this new zone system of raster cells, and assignment results validate significantly better than when using the original zone system.
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    A Mega-region Framework for Analyzing a High Energy Price Future
    (2012) Ducca, Fred; Mishra, Sabyasachee; Moeckel, Rolf; Weidner, Tara
    Mega-regions are a new geography that may well form the “nation's operative regions when competing in the future global economy. A challenge is to determine how to foster greater efficiencies in these mega-regions by creating a stronger infrastructure and technology backbone in the Nation's surface transportation system,” according to the March 2010 FHWA Strategic Plan. To meet this challenge these regions will need analysis tools to evaluate scenarios and their regional impacts, analysis tools covering areas larger than covered by the typical Metropolitan Planning Organization (MPO) or State Department of Transportation (DOT) models. This paper describes what makes mega-regions different and identifies analytic issues mega-regions may need to address, identifies the Chesapeake Mega-region and provides a framework for analyzing issues within the Chesapeake mega-region. Finally, the framework is tested through a proof of concept scenario which assumes a sudden price rise in gasoline prices and the likely effects on travel. A brief summary of further work and additional scenarios planned is provided.
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    Integrating Models for Complex Planning Policy Analysis: Challenges and a Solution in Coupling Dissimilar Models
    (2015) Moeckel, Rolf; Shahumyan, Harutyun
    It is an expensive and time consuming task to develop a new model. Besides, a single model often cannot provide answers required for integrated decision making. Therefore, coupling existing models is often used for model integration. The paper provides an overview of possible model integration approaches, briefly explains the models of a particular application and focuses on the integration methods applied in this research. While the initial attempt was to integrate all models as tightly as possible, the authors developed a much more agile integration approach. Python wrappers were developed to loosely couple land-use, transportation and emission models developed in different environments. ArcGIS Model Builder was used to provide a graphical user interface and to present the models’ workflow. The suggested approach is efficient when the models are developed in different programming languages, their source codes are not available or the licensing restrictions make other coupling approaches infeasible.
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    Transit-Induced Gentrification: Who Will Stay, and Who Will Go?
    (2014) Dawkins, Casey; Moeckel, Rolf
    Transit-Oriented Development (TOD) has been promoted by planners and policy advocates as a solution to a variety of urban problems, including automobile traffic congestion, air pollution, and urban poverty. This paper addresses the question: How do TOD-based affordable housing policies influence the intra-urban location of low income households over time? This paper examined historical descriptive evidence along with land use forecasts generated by the Simple Integrated Land-Use Orchestrator (SILO) land use model to examine the impact of housing policies on patterns of sorting by income within the Washington, D.C. metropolitan area. The historical evidence suggests that in most decades when Metro stations were opened, census tracts near transit stations saw higher increases in median household income than other census tracts. We also find evidence that income growth around stations constructed in the 1970s and 1980s persisted over time, while income growth around stations constructed during the 1990s was largest in the following decade. Consistent with other studies (Kahn 2007), we interpret these findings as evidence that some degree of transit-induced gentrification has been occurring in the Washington, D.C. region.