Data and Methods Comparing Social Structure
and Vegetation Structure of Urban Neighborhoods
in Baltimore, Maryland
J. MORGAN GROVE
USDA Forest Service, Northeastern Research Station, Burlington,
Vermont, USA
MARY L. CADENASSO
Hixon Center for Urban Ecology, School of Forestry and Environmental
Studies, Yale University, New Haven, Connecticut, USA
WILLIAM R. BURCH, JR.
School of Forestry and Environmental Studies, Yale University,
New Haven, Connecticut, USA
STEWARD T. A. PICKETT AND KIRSTEN SCHWARZ
Institute of Ecosystem Studies, Millbrook, New York, USA
JARLATH O’NEIL-DUNNE
Spatial Analysis Lab, Rubenstein School of the Environment and Natural
Resources, University of Vermont, Burlington, Vermont, USA
MATTHEW WILSON
School of Business Administration and the Gund Institute for Ecological
Economics, University of Vermont, Burlington, Vermont, USA
Received 13 April 2004; accepted 6 July 2005.
We would like to thank the U.S. Forest Service’s Northeastern Research Station and the
National Science Foundation for their support of the Baltimore Ecosystem Study, Long-Term
Ecological Research project (NSF DEB-9714835). We would also like to thank the Maryland
Department of Natural Resources’ Forest Service, The City of Baltimore, Space Imaging,
LLC, and The Parks & People Foundation for their generous contribution of data and expert-
ise to this project. This paper has benefited from insights gained through interactions with
generous collaborators, students, and community partners from Baltimore since 1989. Two
anonymous reviewers, Ted Gragson, and Rick Krannich provided constructive comments
and suggestions that greatly improved the paper.
Address correspondence to J. Morgan Grove, PhD, USDA Forest Service, Northeastern
Research Station, 705 Spear Street, South Burlington, VT 05403, USA. E-mail: mgrove@
fs.fed.us
Society and Natural Resources, 19:117–136
Copyright # 2006 Taylor & Francis LLC
ISSN: 0894-1920 print/1521-0723 online
DOI: 10.1080/08941920500394501
117

AUSTIN TROY
Aiken Center, Rubenstein School of Environment and Natural Resources,
University of Vermont, Burlington, Vermont, USA
CHRISTOPHER BOONE
Department of Geography, Ohio University, Athens, Ohio, USA
Recent advances in remote sensing and the adoption of geographic information
systems (GIS) have greatly increased the availability of high-resolution spatial
and attribute data for examining the relationship between social and vegetation
structure in urban areas. There are several motivations for understanding this
relationship. First, the United States has experienced a significant increase in the
extent of urbanized land. Second, urban foresters increasingly recognize their need
for data about urban forestry types, owners and property regimes, and associated
social goods, benefits, and services. Third, previous research has focused primarily
on the distribution of vegetation cover or diversity. However, little is known about
(1) whether vegetation structure varies among urban neighborhoods and (2)
whether the motivations, pathways, and capacities for vegetation management vary
among households and communities. In this article, we describe novel data and meth-
ods from Baltimore, MD, and the Baltimore Ecosystem Study (BES) to address
these two questions.
Keywords Baltimore, landcover, LTER, remote-sensing, social structure, urban
ecology, vegetation
This article presents new kinds of data and methods for examining the relationship
between social and vegetation structure in urban areas. There are several motiva-
tions for employing these data and developing these methods. First, with a 34%
increase in the amount of urbanized land in the United States between 1982 and
1997 (NRCS 1999) and the amount of developed land projected to increase from
5.2% to 9.2% by 2025 (Alig and Kline 2004), understanding and forecasting the
social dynamics of urban vegetation in general will become increasingly important
to society and its metropolitan regions (Nowak et al. 2001; Dwyer et al. 2002;
Dwyer and McCaffrey 2004). Second, urban foresters increasingly recognize that
urban forestry requires knowledge and data about urban forestry types, owners
and property regimes, and associated social goods, benefits, and services (Lohr
et al. 2004; Grove et al. 2005; Grove et al. in press). Finally, previous research on
the relationship between social structure and vegetation has focused primarily on
the distribution of vegetation cover (Whitney and Adams 1980; Palmer 1984; Grove
1996; Jensen et al. 2005) or species diversity (Whitney and Adams 1980; Hope et al.
2003; Martin et al. 2004). While the extent of vegetation cover may be significant to
urban ecosystem processes, the structure of that vegetation cover in terms of large
and small trees, shrubs, and herbaceous layers may also be important. However,
little is known about (1) whether vegetation structure varies among urban neighbor-
hoods and (2) whether the motivations, pathways, and capacities for vegetation
management vary among households and communities. In this article, we describe
data and methods from Baltimore, MD, that may be used to address these two
questions.
118 J. M. Grove et al.