Troy, A. and Grove, J. M. and O’Neil-Dunne, J. (2012) The relationship between tree canopy and crime rates across an urban–rural gradient in the greater Baltimore region. Landscape and Urban Planning. 9 pp..
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Abstract
The extent to which urban tree cover influences crime is in debate in the literature. This research took advantage of geocoded crime point data and high resolution tree canopy data to address this question in Baltimore City and County, MD, an area that includes a significant urban–rural gradient. Using ordinary least squares and spatially adjusted regression and controlling for numerous potential confounders, we found that there is a strong inverse relationship between tree canopy and our index of robbery, burglary, theft and shooting. The more conservative spatially adjusted model indicated that a 10% increase in tree canopy was associated with a roughly 12% decrease in crime. When we broke down tree cover by public and private ownership for the spatial model, we found that the inverse relationship continued in both contexts, but the magnitude was 40% greater for public than for private lands. We also used geographically weighted regression to identify spatial non-stationarity in this relationship, which we found for trees in general and trees on private land, but not for trees on public land. Geographic plots of pseudo-t statistics indicated that while there was a negative relationship between crime and trees in the vast majority of block groups of the study area, there were a few patches where the opposite relationship was true, particularly in a part of Baltimore City where there is an extensive interface between industrial and residential properties. It is possible that in this area a significant proportion of trees is growing in abandoned lands between these two land uses.
| Item Type: | Article |
|---|---|
| Additional Information: | This research was made possible by the generous support of the U.S. Forest Service’s Northern Research Station and Northeastern Area State & Private Forestry Program (USDA03-CA-11244225- 531), the National Science Foundation Long-Term Ecological Research program (NSF DEB-0423476) and the National Science Foundation Human and Social Dynamics Program (award #0624159), which in turn supported the Baltimore Ecosystem Study. Thanks also go out to R. Holli Howard for her expert GIS help and to Colin Drane of Spotcrime for his help with interpreting crime data. |
| Uncontrolled Keywords: | Urban tree canopy,Crime,Urban vegetation,Public safety, Geographically weighted regression |
| Author Affiliation: | University of Vermont, Rubenstein School of Environment and Natural Resources and Spatial Analysis Lab, Aiken Center, 81 Carrigan Drive, Burlington, VT 05405, United States |
| Subjects: | Social Sciences |
| Divisions: | UNSPECIFIED |
| Depositing User: | Mr Siva Shankar |
| Date Deposited: | 04 May 2012 07:24 |
| Last Modified: | 04 May 2012 07:24 |
| Official URL: | http://dx.doi.org/10.1016/j.landurbplan.2012.03.01... |
| URI: | http://eprints.icrisat.ac.in/id/eprint/5095 |
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