«Urban Problems and sPatial methods VolUme 17, nUmber 1 • 2015 U.S. Department of Housing and Urban Development | Office of Policy Development and ...»
A Journal of Policy
Development and Research
Urban Problems and sPatial methods
VolUme 17, nUmber 1 • 2015
U.S. Department of Housing and Urban Development | Office of Policy Development and Research
Managing Editor: Mark D. Shroder
Associate Editor: Michelle P. Matuga
The Reinvestment Fund
Richard K. Green
University of Southern California
Case Western Reserve University
Matthew E. Kahn
University of California, Los Angeles C. Theodore Koebel Virginia Tech Jens Ludwig University of Chicago Mary Pattillo Northwestern University Carolina Reid University of California Patrick Sharkey New York University Cityscape A Journal of Policy Development and Research Urban Problems and sPatial methods VolUme 17, nUmber 1 • 2015 U.S. Department of Housing and Urban Development Office of Policy Development and Research The goal of Cityscape is to bring high-quality original research on housing and community development issues to scholars, government officials, and practitioners. Cityscape is open to all relevant disciplines, including architecture, consumer research, demography, economics, engineering, ethnography, finance, geography, law, planning, political science, public policy, regional science, sociology, statistics, and urban studies.
Cityscape is published three times a year by the Office of Policy Development and Research (PD&R) of the U.S. Department of Housing and Urban Development (HUD). Subscriptions are available at no charge and single copies at a nominal fee. The journal is also available on line at http://www.
PD&R welcomes submissions to the Refereed Papers section of the journal. Our referee process is double blind and timely, and our referees are highly qualified. The managing editor will also respond to authors who submit outlines of proposed papers regarding the suitability of those proposals for inclusion in Cityscape. Send manuscripts or outlines to firstname.lastname@example.org.
Opinions expressed in the articles are those of the authors and do not necessarily reflect the views and policies of HUD or the U.S. government.
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Other services of HUD USER, PD&R’s Research and Information Service, include listservs, special interest and bimonthly publications (best practices, significant studies from other sources), access to public use databases, and a hotline (1–800–245–2691) for help with accessing the information you need.
Contents Symposium Urban Problems and Spatial Methods
Guest Editors: Ron Wilson and Robert Renner Guest Editors’ Introduction Advancing Thought on the Use of Spatial Techniques and Methods for Urban Analysis....... 3 Risk Terrain Modeling for Spatial Risk Assessment
by Joel M. Caplan, Leslie W. Kennedy, Jeremy D. Barnum, and Eric L. Piza Linking Public Health, Social Capital, and Environmental Stress to Crime Using a Spatially Dependent Model
by Greg Rybarczyk, Alex Maguffee, and Daniel Kruger Exploring the Spatial Diffusion of Homicides in Mexican Municipalities Through Exploratory Spatial Data Analysis
by Miguel Flores and Amado Villarreal A Spatial Difference-in-Differences Approach To Studying the Effect of Greening Vacant Land on Property Values
by Megan Heckert Does the House or Neighborhood Matter More? Predicting Abandoned Housing Using Multilevel Models
by Victoria C. Morckel 3-D Residential Land Use and Downtown Parking: An Analysis of Demand Index.............. 71 by William J. Gribb Rethinking Food Deserts Using Mixed-Methods GIS
by Jerry Shannon Spatializing Segregation Measures: An Approach To Better Depict Social Relationships..... 97 by Masayoshi Oka and David W.S. Wong Increasing the Accuracy of Urban Population Analysis With Dasymetric Mapping............ 115 by Jeremy Mennis An Integrated Framework To Support Global and Local Pattern Assessment for Residential Movements
by Yin Liu and Alan T. Murray Spatial Experiences: Using Google Earth To Locate Meanings Pertinent to Sense of Place
by Nicholas Wise Small Stories in Big Data: Gaining Insights From Large Spatial Point Pattern Datasets..... 151 by Ate Poorthuis and Matthew Zook iii Cityscape Contents Refereed Papers
Sustaining Homeownership After Delinquency: The Effectiveness of Loan Modifications by Race and Ethnicity
by J. Michael Collins, Carolina K. Reid, and Carly Urban Departments
Data Shop Data Sources for U.S. Housing Research, Part 2: Private Sources, Administrative Records, and Future Directions
by Daniel H. Weinberg Connecting Address and Property Data To Evaluate Housing-Related Policy
by Alyssa J. Sylvaria, Jessica Cigna, and Rebecca Lee Industrial Revolution Glass-Modified Asphalt Shingles for Mitigation of Urban Heat Island Effect
by Marwa Hassan, Micah Kiletico, and Somayeh Asadi Foreign Exchange Measuring U.S. Sustainable Development
by Eugenie L. Birch iv Volume 17, Number 1 Symposium Urban Problems and Spatial Methods Guest Editors: Ron Wilson and Robert Renner
Advancing Thought on the Use of Spatial Techniques and Methods for Urban Analysis Ron Wilson University of Maryland, Baltimore County Robert Renner U.S. Department of Housing and Urban Development The views expressed in this introduction are those of the guest editors and do not represent the official positions or policies of the Office of Policy Development and Research, the U.S. Department of Housing and Urban Development, or the U.S. government.
Over the past 20 years, spatial analysis has exploded across a range of uses. Primarily promoted by the rising capacity of Geographic Information Systems (GISs), spatial analysis is now its own scientific field of inquiry, with many journals, conferences, and academic degrees (see Goodchild, 2010, for a recent two-decade review of accomplishments). Analysts have developed spatial analysis tools across many scientific disciplines to measure local variations of social and environmental phenomena. More often than not, the interaction between these phenomena vary across space, suggesting that a spatial approach may be required to fully understand and respond to society’s most pressing problems. Spatial tools provide us with a quantitative foundation for understanding these complex interactions and implementing place-based solutions. The symposium in this issue of Cityscape is designed to show how spatial techniques and methods can be creatively applied to a wide range of urban issues.
The Spatial Analysis and Methods (SpAM) department of Cityscape was created to demonstrate the use of spatial approaches for urban applications so that readers can replicate the methods in their own research. With SpAM, we also hope to combat the notion that spatial analysis is just mapmaking with GIS.
The remarkable growth in use of spatial methods may be expressed quantitatively. Exhibit 1 shows the percentage of journal articles published across several social science disciplines that use some form of spatial analysis. Other surveys demonstrate a similar multidisciplinary growth, such as
Exhibit 1 Trends in Use of Spatial Analysis Across the Social Sciences Notes: Compiled from authors’ tabulation from sociological abstracts, applied social sciences index and abstracts, and social service abstracts. Authors conducted a search using the following keywords: spatial, mapping, geographic information systems, GIS, hot spots, and crime mapping. The last two keywords are included to more accurately portray realistic levels in criminology and criminal justice, because those keywords represent spatial analysis that would not have been otherwise detected.
Fearon (2003), who presents a similar trend with spatial analysis growing from 1.3 percent in 1990 to 3.7 percent in 2001.1 All charted disciplines show a marked upward trend in the use of spatial approaches in understanding the interaction between people and place.
This symposium covers a wide range of practical articles that are representative of the published papers represented in exhibit 1. The problems analyzed include crime, vacant land, residential mobility, urban population distribution, neighborhoods and housing, food deserts, segregation, and place meaning. The U.S. Department of Housing and Urban Development (HUD), like many local governments, is increasingly employing spatial analysis in its work, with the Office of Policy Development and Research (PD&R) playing the key role.
Many of HUD’s programs are inherently place based. Program data are regularly geocoded and integrated with other spatially enabled sociodemographic and economic data for analytic purposes.
PD&R manages the Enterprise GIS (eGIS) program, which supports and coordinates these activities across the entire agency. An important aspect of PD&R’s role in eGIS is the adoption, practice, and promotion of geospatial analytical techniques like the ones presented in this symposium.
The percentage of publications per year is higher in the Fearon paper than in exhibit 1 because Fearon’s literature analysis includes a broader scope of disciplines than the authors’ analysis in exhibit 1.
4 Urban Problems and Spatial Methods Advancing Thought on the Use of Spatial Techniques and Methods for Urban Analysis For example, the dasymetric approach that Jeremy Mennis addresses in his article has been implemented with block-level data to support the grant application process for a number of HUD’s signature grant programs, including the Neighborhood Stabilization Program, Choice Neighborhoods, Rural Innovation Fund, and, most recently, Promise Zones. In another example, Masayoshi Oka and David W.S. Wong demonstrate in their article that “spatializing” common segregation measures improves the representation of social relationships between the races and ethnicities. PD&R staff use program data for monitoring and evaluating expected outcomes. Other examples of HUD spatial analysis appear in earlier SpAM articles, such as evaluating Housing Choice Voucher holder density changes for deconcentration (Wilson, 2012) and the spatial mismatch between the homeless and available resource locations (Mast, 2014). Many PD&R in-house and outside-funded research projects are increasingly using spatial techniques and methods as part of their evaluation strategies.
We hope this symposium spurs more readers to use spatial analysis beyond the typical visualization of data in maps. Many state and local governments are posting geocoded data on line, generating new opportunities for analytic experimentation. New technologies, from social media to sound sensors and smart-phone applications, are capturing geographic data, offering rich, new sources of nongovernmental data.
Spatial analysis is breaking new ground in finding fresh approaches to urban problems. We expect that many more groundbreaking examples will appear in future issues of Cityscape.
Guest Editors Ron Wilson is a lecturer in the Geographic Information Systems Professional Studies program at the University of Maryland, Baltimore County.
Robert Renner is a social science analyst in the Office of Policy Development and Research and the head of GIS activities at the U.S. Department of Housing and Urban Development.
References Fearon, David S. 2003. The Scope and Growth of Spatial Analysis in the Social Sciences.
Unpublished paper. University of California, Santa Barbara, Center for the Spatially Integrated Social Sciences. http://www.csiss.org/aboutus/reports/Report_on_Spatial_Analysis_literature.pdf.
Goodchild, Michael F. 2010. “Twenty Years of Progress: GIScience in 2010,” Journal of Spatial Information Science 1: 3–20.
Mast, Brent D. 2014. “Measuring Spatial Mismatch Between Homelessness and Homeless Resources With a Theil Index and Statistical Inference,” Cityscape 16 (1): 339–350.
Wilson, Ron. 2012. “Using Dual Kernel Density Estimation To Examine Changes in Voucher Density Over Time,” Cityscape 14 (3): 339–350.
Eric L. Piza John Jay College of Criminal Justice Abstract Spatial factors can influence the seriousness and longevity of crime problems. Risk terrain modeling (RTM) identifies the spatial risks that come from features of a landscape and models how they colocate to create unique behavior settings for crime. The RTM process begins by testing a variety of factors thought to be geographically related to crime incidents. Valid factors are selected and then weighted to produce a final model that basically paints a picture of places where crime is statistically most likely to occur.
This article addresses crime as the outcome event, but RTM can be applied to a variety of other topics, including injury prevention, public health, traffic accidents, and urban development. RTM is not difficult to use for those who have a basic skillset in statistics and Geographic Information Systems, or GISs. To make RTM more accessible to a broad audience of practitioners, however, Rutgers University developed the Risk Terrain Modeling Diagnostics (RTMDx) Utility, an app that automates RTM. This article explains the technical steps of RTM and the statistical procedures that the RTMDx Utility uses to diagnose underlying spatial factors of crime at existing high-crime places and to identify the most likely places where crime will emerge in the future, even if it has not occurred there already. A demonstrative case study focuses on the process, methods, and actionable results of RTM when applied to property crime in Chicago, Illinois, using readily accessible resources and open public data.