Urban tree canopy tool suite: Green infrastructure tools for planners

This week my colleague Dexter Locke and I had the opportunity to present at the DE / MD APA 2014 Regional Planning Conference. We presented on the suite of urban tree canopy tools available to planners.

While many tree canopy goal efforts have focused disproportionately on tree planting, strategies for all variables in the equation below are needed to realize a tree canopy goal. There are tools to support each component.

conceptual framework for UTC

Conceptual model of tree canopy goal framework

The basis for all tools in the suite is a high resolution, 7-class land cover data set derived from remote sensing imagery and LiDAR data.

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7 class landcover

Imagery + LiDAR data fusion and resulting hi-res 7-class landcover

Fusing these two datasets provides the highest level of accuracy, more than either does on its own.

By mashing up the landcover data with GIS layers of various geographies, we can quantify existing and potential tree canopy cover at a variety of scales from the parcel to the neighborhood to the city to the region. This is an Urban Tree Canopy (UTC) assessment.

existing and possible UTC at various scales

UTC Assessment showing existing and potential UTC at the parcel and landscape (3-county) scales

With UTC Prioritization, we determine desired outcomes (why do you want more tree canopy – heat island reduction? environmental equity? stormwater management?), identify GIS data to serve as proxies for those outcomes, and provide a weighted, spatially explicit map to help you target efforts and use limited resources most efficiently.

NYC Prioritization

UTC Prioritization process of converting units of various layers to a common scale and weighting and ranking to maximize efficient use of resources to realize desired outcomes

UTC Market Segments uses market segmentation data to identify what markets are participating in UTC goal efforts and to assess market penetration and access. Results are displayed as an odds ratio where 1:1 is proportional participation/access based on that market segment, a greater odds ratio is better than proportional participation/access, and a lower odds ration is lower than proportional participation/access.

UTC Market Segments DC

UTC Market Segments assessment of market participation in tree and rain barrel programs in context of existing and potential UTC

UTC Change Detection is based on the methods we use for UTC assessment. However, in this instance we combine four datasets (imagery + LiDAR from one point in time and imagery+ LiDAR from another point in time) and map the specific locations of gain and loss over the time period between the two images (this produces more accurate results than creating a land cover image for one point in time, creating a land cover image for another point in time, and calling the difference between the two results the change over time).

UTC Change DC

UTC Change Detection mapping canopy gains and losses over a given period

The UTC tool suite is developed and deployed by Dr. Morgan Grove, US Forest Service Northern Research Station; Jarlath O’Neil-Dunne, University of Vermont Spatial Analysis Lab; Dexter Locke, Clark University; and me, Director of the Consulting Group at SavATree.

For more information, please see our Prezi on the UTC tool suite.