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 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 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 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).Item Reclassification of Sustainable Neighborhoods: An Opportunity Indicator Analysis in Baltimore Metropolitan Area(2013) Knaap, Elijah; Knaap, Gerrit; Liu, ChaoThe “Sustainable neighborhoods” has become widely proposed objective of urban planners, scholars, and local government agencies. However, after decades of discussion, there is still no consensus on the definition of sustainable neighborhoods (Sawicki and Flynn, 1996; Dluhy and Swartz 2006; Song and Knaap,2007; Galster 2010). To gain new information on this issue, this paper develops a quantitative method for classifying neighborhood types. It starts by measuring a set of more than 100 neighborhood sustainable indicators. The initial set of indicators includes education, housing, neighborhood quality and social capital, neighborhood environment and health, employment and transportation. Data are gathered from various sources, including the National Center for Smart Growth (NCSG) data inventory, U.S. Census, Bureau of Economic Analysis (BEA), Environmental Protection Agency (EPA), many government agencies and private vendors. GIS mapping is used to visualize and identify variations in neighborhood attributes at the most detailed level (e.g census tracts). Factor analysis is then used to reduce the number of indicators to a small set of dimensions that capture essential differences in neighborhood types in terms of social, economic, and environmental dimensions. These factors loadings are used as inputs to a cluster analysis to identify unique neighborhood types. Finally, different types of neighborhoods are visualized using a GIS tool for further evaluation. The proposed quantitative analysis will help illustrate variations in neighborhood types and their spatial patterns in the Baltimore metropolitan region. This framework offers new insights on what is a sustainable neighborhood.Item Transit-Induced Gentrification: Who Will Stay, and Who Will Go?(2014) Dawkins, Casey; Moeckel, RolfTransit-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.Item Barriers to Development Inside Maryland's Priority Funding Areas: Perspectives of Planners, Developers, and Advocates(2012) Dawkins, Casey; Knaap, Gerrit; Sartori, JasonPassed in 1997, Maryland’s Smart Growth and Neighborhood Conservation Initiative took a novel approach to growth management, utilizing the power of the purse to encourage sustainable development. The initiative seeks to discourage suburban sprawl through a targeted spending approach, while also allowing local governments to retain their land use decision-making authority. It required local governments to designate Priority Funding Areas (PFAs) where state infrastructure funding would be focused. Through this tool, the State aimed to promote development and revitalization within Maryland’s urbanized areas, while limiting the urbanization of Maryland’s rural areas and green spaces. Data from the Maryland Department of Planning, however, suggests that PFAs are having limited impacts. The percent of single-family acres developed outside of PFAs has risen steadily over time. Development densities have declined in PFAs, with the average parcel size inside PFAs increasing from 0.25 acres in 1990 to 0.28 acres in 2004. Despite their disappointing performance, PFAs are anticipated to play key roles in future policies regarding development on septic systems and in PlanMaryland, the state development plan. Given their growing prominence but questionable efficacy, PFAs warrant further examination. That is the purpose of this study, conducted by the Housing Strategies Group of the National Center for Smart Growth Research and Education at the University of Maryland, and funded by the Maryland State Builders Association and NAIOP Maryland chapters. The study relies upon responses to a telephone survey of forty-seven representatives from three key stakeholder groups—planners, policy advocates and consultants, and developers. HSG made every effort to obtain the perspectives of a variety of sources but it is important to note that the survey respondents could not be said to be randomly selected and the sample size is too small for rigorous statistical analysis. While not presenting new empirical analysis of the influence of PFAs on development patterns across the State, the study does produce new information on how critical stakeholders view the efficacy of PFAs and the barriers to development inside PFAs. Survey respondents identified a number of ways to improve development conditions in PFAs, ranging from limiting the length of APFO restrictions to reducing impact fees and lowering level of service requirements for certain types of infrastructure inside PFAs. Other recommendations included expediting the state agency review processes and lessening stormwater management and other environmental protection requirements for projects inside PFAs.