Future Suburban Development and the Environmental Implications of Lawns: A Case Study in New England, USA

  • Daniel Miller Runfola
  • Colin Polsky
  • Nick Giner
  • Robert Gilmore PontiusJr.
  • Craig Nicolson
Part of the Cities and Nature book series (CITIES)


Lawns cover more land than irrigated corn in the United States according to the most recent estimates (Milesi et al. 2009). The associated ecological ramifications – such as habitat fragmentation, water quality and availability – may be far-reaching. The way lawns are maintained, especially intensive fertilization and watering, also presents risks for water use and quality, nutrient cycling, urban climate regimes, and even human health. However, the lack of broad-extent, high-resolution land cover data has limited the ability of researchers to measure or project the extent of lawns. In this chapter, we first produce a high resolution (0.5 m) land-cover classification to quantify existing lawn extent for the year 2005 in the Plum Island Ecosystem (PIE), a collection of 26 suburban towns northeast of Boston, MA, USA. We then use this dataset in conjunction with the GEOMOD land-change model to project lawn extent under two scenarios of urban growth for the year 2030. We find that in 2005, 76 km2 of lawn – defined as grass on residential land – existed in the PIE study region. Under a Current Trends scenario, we project residential lawns may increase by 7.0 % to 81 km2, while under a Smart Growth scenario we project a 1.6 % increase to 77 km2. We estimate this could result in up to 61 million additional liters of annual water use under the Current Trends scenario, and 14 million under Smart Growth, putting additional stress on utilities that already face regular water shortages.


Land Cover Normalize Difference Vegetation Index Urban Growth Residential Land Residential Development 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The United States’ National Science Foundation (NSF) supported this work via the following programs: Long Term Ecological Research via grants OCE-0423565 and OCE-1026859 for Plum Island Ecosystems and OCE-0620959 for Georgia Coastal Ecosystems, Coupled Natural Human Systems via grant BCS-0709685, Research Experiences for Undergraduates Site via grant SES-0849985, Decision-Making Under Uncertainty via grant SES-0951366, Urban Long Term Research Areas via grant BCS-0948984, and a supplement grant entitled “Maps and Locals (MALS)” via grant DEB-0620579. The work has also benefited from the NICHD funded University of Colorado Population Center (grant R21 HD51146) for research, administrative, and computing support. Any opinions, findings, conclusions, or recommendation expressed in this paper are those of the authors and do not necessarily reflect those of the funders.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniel Miller Runfola
    • 1
  • Colin Polsky
    • 2
  • Nick Giner
    • 2
  • Robert Gilmore PontiusJr.
    • 2
  • Craig Nicolson
    • 3
  1. 1.National Center for Atmospheric ResearchUniversity of Colorado at BoulderBoulderUSA
  2. 2.Clark UniversityWorcesterUSA
  3. 3.University of Massachusetts AmherstAmherstUSA

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