Geospatial Assessment in Support of Urban & Community Forestry Programs
A study initiated to examine the strengths and limitations of existing methods for identifying forest opportunities in urban areas.
Geospatial information is an important component of urban and community forestry assessment in the Northern Area. The syn-thesis of geographic data can help inform the decision making process at a range of scales, from prioritizing communities within a state to targeting individual properties for tree plantings. For accurate and meaningful information to be gained from these assessments it is crucial that any geospatial assessment employ datasets and tools that are appropriate to the scale of analysis.
An accurate representation of the tree canopy is arguably the most important source dataset of any urban and community forestry geospatial assessment. This study showed that estimates of tree canopy in urban areas obtained from readily avail-able moderate resolution national datasets have substantial accuracy issues, typically underestimating tree canopy by large percentages. As such, these datasets should only be used to examine the relative differences in land cover between urban areas, and should not be used in those cases where accurate estimates are required (e.g. tree canopy goal setting). High-resolution land cover datasets yield highly accurate estimates of tree canopy, but such datasets are not readily available for most urban areas. Although such datasets are not commonplace, generating high resolution land cover datasets is now a feasible option due to recent technological advances.
We conclude that pixel-based overlay methods, such as those used in the Spatial Analysis Project (SAP) are not appropriate for urban and community forestry assessment. A summary method, similar to what has been implemented in the Urban Tree Canopy assessment (UTC) analysis and National Urban Forest Assessment (as mandated by the Renewable Resource Planning Act), using scale appropriate data, can provide decision makers with information needed to help target resources in support of urban and community forestry initiatives. To assist with is process we generated four tools: the Urban and Community Forestry Index (UCF-i), the Maryland Method (MD-Method), the Urban Tree Canopy assessment (UTC) and the Priority Planting Index (PPI). These tools are incorporated into the Urban Forestry Toolbox, and can be executed using GIS software. UCF-i and MD-Method are designed to work at the regional scale. Both tools make use of readily available land cover and census datasets to help target communities in the Northern Area or within a state. Once those communities have been identified and high resolution land cover data becomes available, UTC and PPI assist in identifying and prioritizing areas within community. [Executive Summary]
A.R. Troy, J.M. Grove, J.P.M. O’Neil-Dunne
Canopy, GIS/Mapping, Modeling (spatial)
NLCD, NLCD, FOS, FOS