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The Urban Forest Effects (UFORE) Model
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The UFORE computer model was developed to help managers and researchers
quantify urban forest structure and its functions. UFORE is designed
to use standardized field data from randomly located plots, and local
hourly air pollution and meteorological data to quantify urban forest
structure and numerous urban forest effects for cities across the
world. The model calculates numerous attributes about the urban forest,
including:
 Species composition
Diameter distribution
Tree health
Species diversity
Exotic vs. native species distribution
The model also calculated various forest functions and values related to tree effects on:
Air pollution
Greenhouse gases and global warming
Pollen
Building energy use
The program, which was originally written in SAS, is currently being converted, in cooperation with
the Davey Resource Group, to a Windows® based code for operation on PCs. A Windows®
version of the model
will be released in 2006. Model operations will include
user's manual, field data collection manual, field data collection programs for PDAs, and UFORE program
for Windows®. New analytic modules are and will be developed in the future, including GIS-based mapping
and analysis capabilities.
For more information:
UFORE Summary Paper
UFORE Methods
UFORE
Random Plot Selection Tool
UFORE Field Data Collection
Manual
Tree/Shrub Species Codes (PDF format)(used in UFORE Manual and Urban FHM Manual)
Tree/Shrub Species Codes (EXCEL format)(used in UFORE Manual and Urban FHM Manual)
Urban Forest Health Monitoring (FHM)
Manual
City Reports:
Brooklyn
Houston
Funding Source: USDA Forest Service's State and Private Forestry, Cooperative Forestry's Urban and Community
Forestry Program; Forest Health Monitoring; and Northeastern Research Station; the National Urban and Community
Forestry Advisory Council; and the Texas Forest Service
Principal Investigators: David J. Nowak, Daniel E. Crane, Jack C. Stevens, Jeffrey T. Walton
(USFS, Northeastern Research Station), Jerry Bond, Greg Ina, Mike Binkley, and Lianghu Tian
(Davey Resource Group), and Ted Endreny and Jun Wang (SUNY College of Environmental Science and Forestry)
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