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Prioritizing preferable locations for increasing urban tree canopy in New York CityAuthor(s): Dexter Locke; J. Morgan Grove; Jacqueline W.T. Lu; Austin Troy; Jarlath P.M. O'Neil-Dunne; Brian Beck
Source: Cities and the Environment 3(1):18 p.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
PDF: Download Publication (4.2 MB)
DescriptionThis paper presents a set of Geographic Information System (GIS) methods for identifying and prioritizing tree planting sites in urban environments. It uses an analytical approach created by a University of Vermont service-learning class called "GIS Analysis of New York City's Ecology" that was designed to provide research support to the MillionTreesNYC tree planting campaign. These methods prioritize tree planting sites based on need (whether or not trees can help address specific issues in the community) and suitability (biophysical constraints and planting partners’ existing programmatic goals). Criteria for suitability and need were based on input from three New York City tree-planting organizations. Customized spatial analysis tools and maps were created to show where each organization may contribute to increasing urban tree canopy (UTC) while also achieving their own programmatic goals. These methods and associated custom tools can help decision-makers optimize urban forestry investments with respect to biophysical and socioeconomic outcomes in a clear and accountable manner. Additionally, the framework described here may be used in other cities, can track spatial characteristics of urban ecosystems over time, and may enable further tool development for collaborative decision-making in urban natural resource management.
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CitationLocke, Dexter; Grove, J. Morgan; Lu, Jacqueline W.T.; Troy, Austin; O’Neil-Dunne, Jarlath P.M.; Beck, Brian. 2010. Prioritizing preferable locations for increasing urban tree canopy in New York City. Cities and the Environment 3(1):18.
KeywordsUrban Forestry, UTC, urban tree canopy, possible, preferable, geographic information systems, GIS, trees, green space, vegetation
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