National Center for Smart Growth Research Works
Permanent URI for this collectionhttp://hdl.handle.net/1903/21473
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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Item Smart Growth in Maryland: Looking Forward and Looking Back(2007) Frece, John; Knaap, GerritSpring of 2007 will mark the 10th anniversary of the passage of Maryland’s Smart Growth and Neighborhood Conservation Initiative; an effort designed to discourage sprawl development, foster more compact communities, protect the best remaining farms and open space in the state, and save taxpayers from the growing cost of providing services and infrastructure to serve far-flung development. Almost before its various provisions took effect in 1997 and 1998, the Maryland initiative generated interest and acclaim across the country. It received numerous awards and became the principal legacy of the program’s primary architect, former Governor Parris N. Glen- dening. Governors in other states, such as New Jersey, Colorado and Massachusetts, instituted their own “smart growth” proposals, often modeled after portions of the Maryland program. Even the popularity and wide usage of the now omnipresent phrase “smart growth” can be attributed in large part to the Maryland program. But, what has been the effect of Maryland’s Smart Growth pro- gram? Looking at it some ten years later, has it worked? Did it accomplish what it was designed to do? What have been the strengths and weaknesses of the Maryland approach, and how can lessons from the Maryland experience be used to offer a new set of policymakers in Maryland, as well as elsewhere in the nation, practical suggestions on how to make smart growth smarter?Item A Case for Increased State Role in Transit Planning: Analyzing Land Use and Transit Ridership Connections Using Scenarios(2011) Chakraborty, Arnab; Mishra, SabyasacheeLand use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.Item Hotspots for Growth: Land Use Change and Priority Funding Area Policy in a Transitional County in the U.S.(2010) Hanlon, Bernadette; Howland, Marie; McGuire, MichaelThis paper uses a logit model to estimate whether and to what extent Maryland’s Priority Funding Area (PFA) program steers urban growth to locations inside targeted growth area boundaries of an ex-urban county in the outer suburbs of the Washington, D.C. region. The results of our model indicate that the size of an agricultural parcel, its distance from urban parcels, its proximity to highways, the quality of the land for agriculture, and the location in or outside of PFAs influence the probability an agricultural parcel will remain in agriculture or be converted to urban use. We find that some of the areas experiencing the greatest market pressure for development are located outside PFAs and, although Maryland’s incentive-based strategy reduces the likelihood a parcel outside a PFA will transition to urban use, this policy is not one hundred percent effective.Item The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis(2014) Liu, Chao; Ding, Chuan; Lin, Yaoyu; Wang, YaowuThe empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process.Item A Multiobjective Optimization Approach to Smart Growth in Land Development(2010) Faria, Jose; Gabriel, Steven; Moglen, GlennIn this paper we describe a multiobjective optimization model of "Smart Growth" applied to land development in Montgomery County, Maryland. The term "Smart Growth" is generally meant to describe those land development strategies which do not result in urban sprawl, however the term is somewhat open to interpretation. The multiobjective aspects arise when considering the conflicting interests of the various stakeholders involved: the government planner, the environmentalist, the conservationist, and the land developer. We present a formulation, which employs linear and convex quadratic objective functions for the stakeholders that are subject to polyhedral and binary constraints. As such, the resulting optimization problems are convex, quadratic mixed integer programs which are known to be NP-complete (Mansini and Speranza, 1999). We report numerical results with this model and present these results using a geographic information system (GIS).Item The Contagion Effect of Neighboring Foreclosures on Own Foreclosures(2010) Lawley, Chad; Towe, CharlesIn this paper, we examine a highly localized contagion effect of foreclosures and find strong evidence that social interactions influence the decision to foreclose. We utilize a hazard model and a unique spatially explicit dataset documenting parcel level residential foreclosures in Maryland for the years 2006 through 2009. We combine these data with tax and assessment data, loan data, Census, and unemployment data. These data allow us to control for important factors influencing the likelihood of foreclosure within a given community, including the prevalence of subprime loans and the distribution of socioeconomic characteristics. Additionally, we use the tax data to construct variables describing individual homes, surrounding homes, and community. These variables include structural characteristics of houses, their price history, and length of ownership.Item Information Technology in the 1990s: More Footloose or More Location-bound?(2002) Sohn, JungyulThis paper examines if information technology has worked towards dispersion or concentration of economic activities in two steps of analysis. The first analysis using locational Gini coefficient and Moran’s I focuses on distribution of the urban area as a whole and finds that dispersion was prominent over the years. The second analysis using Gi* statistic as the dependent variable in the regression model, however, shows that the technology has induced more concentration rather than dispersion at an intrametropolitan scale, reflecting that there is a discrepancy in the results of the two analyses depending on the spatial scale of the analysis.Item A functional integrated land use-transportation model for analyzing transportation impacts in the Maryland-Washington, DC Region(2011) Mishra, Sabyasachee; Ye, Xin; Ducca, Fred; Knaap, GerritThe Maryland-Washington, DC region has been experiencing significant land-use changes and changes in local and regional travel patterns due to increasing growth and sprawl. The region’s highway and transit networks regularly experience severe congestion levels. Before proceeding with plans to build new transportation infrastructure to address this expanding demand for travel, a critical question is how future land use will affect the regional transportation system. This article investigates how an integrated land-use and transportation model can address this question. A base year and two horizon-year land use-transport scenarios are analyzed. The horizon-year scenarios are: (1) business as usual (BAU) and (2) high gasoline prices (HGP). The scenarios developed through the land-use model are derived from a three-stage top-down approach: (a) at the state level, (b) at the county level, and (c) at the statewide modeling zone (SMZ) level that reflects economic impacts on the region. The transportation model, the Maryland Statewide Transport Model (MSTM), is an integrated land use-transportation model, capable of reflecting development and travel patterns in the region. The model includes all of Maryland, Washington, DC, and Delaware, and portions of southern Pennsylvania, northern Virginia, New Jersey, and West Virginia. The neighboring states are included to reflect the entering, exiting, and through trips in the region. The MSTM is a four-step travel-demand model with input provided by the alternative land-use scenarios, designed to produce link-level assignment results for four daily time periods, nineteen trip purposes, and eleven modes of travel. This article presents preliminary results of the land use-transportation model. The long-distance passenger and commodity-travel models are at the development stage and are not included in the results. The analyses of the land use-transport scenarios reveal insights to the region’s travel patterns in terms of the congestion level and the shift of travel as per land-use changes. The model is a useful tool for analyzing future land-use and transportation impacts in the region.Item What Are the Effects of Contamination Risks on Commercial and Industrial Properties? Evidence from Baltimore, Maryland(2005) Alberini, Anna; Longo, AlbertoUsing the hedonic pricing approach, we investigate how the information released on public registries of contaminated and potentially contaminated sites affects nearby commercial and industrial properties in Baltimore, Maryland. We find that commercial and industrial properties are virtually unaffected by proximity to a site with a history of contamination. Knowing that the site is no longer considered contaminated does not have a rebound effect on property prices either. We also find that urban economic development policies, such as Empowerment Zones and Enterprise Zones, have little effect on property values. In sum, brownfield properties in Baltimore are not particularly attractive investments for developers, and there is little potential for self-sustaining cleanup based on appropriate fiscal incentives, such as Tax Increment Financing. It is doubtful that “one size fits all” measures to encourage the cleanup of contaminated sites can be successful in this context.Item Indicators of Smart Growth in Maryland(2011) Knaap, Gerrit; Moore, Terry; Sartori, JasonMaryland is often referred to as the birthplace of smart growth, a movement in land use planning that contributed to what is now referred to as sustainability planning, sustainable development, and sustainable communities. Maryland adopted a Smart Growth Program in 1997 with the primary purposes being to use incentives to (1) direct growth into areas already developed and having public facilities, and (2) reduce the conversion of farm, forest, and resource land to urban uses. The National Center for Smart Growth Research and Education at the University of Maryland was established in 2000 in large part because of Maryland’s leadership in the field of smart growth. Its mission is to provide research and leadership training on smart growth and related land use issues in Maryland and in metropolitan regions around the nation. Thus, a key focus of the Center’s research is Maryland’s Smart Growth Program: where is it effective, and how can it be improved? This report provides some indicators (also called performance measures) that suggest answers to those questions. The term “suggest” is important: (1) there are many limitations of any assessment based on indicators, no matter how well developed, and (2) the indicator assessment reported here is only in its preliminary stages. Understanding the limitations of indicators is critical to interpreting their significance. Thus, Section 2 and Appendix B of this report discuss in some detail data, methods, and limitations. Researchers and policymakers acknowledge those limitations, but that acknowledgement does not slack their desire for indicators that say something concrete about whether desired outcomes are being achieved, and at what cost in direct expenditures and spillover effects; and about directions for policy that would increase the desired outcomes, reduce the costs, or both. Sections 3 and 4 address those issues. Section 3 reports indicators for six categories of issues. Population and employment growth drive development. That development is the immediate concern of the two thrusts of the Maryland Smart Growth Program: it puts pressure on the natural areas that the Program wants to protect, and it can occur in development patterns that not only eliminate and vitiate those natural areas, but also are inefficient from the perspective of providing transportation and other infrastructure and, ultimately housing (and other buildings). Some of the key findings: (1) Population, (2) Employment, (3) Transportation, (4) Development patterns, (5) Housing, and (6) Natural areas. If the indicators here are leaning in any direction, it is that Maryland has not made substantial progress toward improving its performance in many of the areas pertaining to smart growth. There are, however, reasons to qualify a direct conclusion like that one: (1) Without the kind of research design that goes well beyond the reporting of indicators into statistical controls for multiple explanatory variables, there is no solid way to rebut the hypothesis that what the Maryland Smart Growth Program did was to prevent many indicators from getting much worse than they are. (2) Things take time. Many changes in technology, social attitudes, prices, and the built environment occur slowly. (3) If it is too early to expect to see much by way of results (e.g., changes to trends) then perhaps indicators of outcomes should be supplemented by indicators of inputs: of efforts made to stimulate future change (i.e., the number and strength of policies to change the patterns and effects of growth).