Lidar-based Hotspot Area / Tree Canopy Coverage Gap Analysis
Lidar-based Hotspot Area / Tree Canopy Coverage Gap Analysis
Cincinnati Area Geographic Information System (CAGIS)
Cincinnati Area GIS (CAGIS)
The Challenge
Cincinnati Area Geographic Information System (CAGIS), a division of the City of Cincinnati’s Department Enterprise Technology Solutions Department (ETS), wanted to complete an updated Urban Tree Canopy Gap Analysis for the City and surrounding Hamilton County, and improve land cover mapping. Key questions were whether and where tree canopy was being gained or lost, and the location and extent of impervious surfaces.
The Outcome
The AppGeo Team collected Quality Level 1 (QL1) leaf-on LiDAR data for the City of Cincinnati and Hamilton County. The project created seven land cover data classifications – impervious surfaces, tree canopy, grass/shrub, bare soil, water, buildings, roads/railroads, and other paved areas (such as driveways and courtyards) – that allowed CAGIS to measure and confirm change and support its planning processes.
Land Cover Data Classifications
What we noticed was that AppGeo, more than anything, they were dedicated to the quality of data that they were putting forward. They gave us the options we needed, and told us what the cost-benefit analysis of that is. So, as an individual that’s not well-versed in GIS or lidar, they did a great job putting in their proposal exactly what they were going to deliver. I have to say as of this point that every deliverable has been on point, on time, and of the best quality that we could have imagined.
– Crystal Courtney, Division Manager – Natural Resources, City of Cincinnati
The Details
Protecting and enhancing the urban tree canopy is an important factor in addressing climate change, heat stress, surface water management, green infrastructure, and environmental justice.
This project for CAGIS established a detailed data set for tree canopy coverage for the City of Cincinnati and Hamilton County that supported change detection and planning. Using LiDAR data collection in combination with aerial imagery enabled higher resolution and more useful measurement of current conditions.
An important part of the effort was obtaining sufficient funding and bringing in stakeholders. Half the funding came from the Metropolitan Sewer District, which was interested in the benefits a detailed impervious service map would provide, as they are looking to create a taxing system for impervious services on private property. CAGIS was also able to get a grant from the U.S. Forest Service and the Ohio Department of Natural Resources to cover the rest of the cost of the Urban Tree Canopy (UTC) assessment. For more information on US funding sources for urban tree canopy assessments, contact AppGeo.
The AppGeo Team for this project included: AppGeo data scientists and geospatial analysts, data scientists from University of Vermont’s Spatial Analysis Lab (UVM SAL), Arborists from SavATree, and imagery data specialists from Quantum Spatial.
Jarlath O’Neil-Dunne’s team from the University of Vermont’s Spatial Analysis Lab collected the lidar data and conducted the UTC assessment, which was quantified using the percentage of coverage for each geographical unit (municipal neighborhood boundaries or census blocks or tracts). Change detection modeling used previous UTC studies performed in 2010 as a baseline. Using Lidar and in contrast to the 2010 data, one of the unique things that was added this time was tree counts, as well as detailed information on each tree, such as crown, crown radius, and diameter of tree can be measured.
“At a very, very precise scale, we’re mapping the gain, loss, and no change. It’s this precise accounting of the gain, loss, and no change that gives you the greatest insights into what is happening to your city. In the case of Cincinnati and Hamilton County, we’re seeing the benefits of tree planting that have happened over a decade ago.”
– Jarlath O’Neil-Dunne, Director, University of Vermont Spatial Analysis Lab
“We didn’t just take a picture of the top of the canopy, [with LiDAR] we actually got to take a picture of an entire canopy and going underneath into the understory; which really provided us really good, relevant information — not just the treetops but the actual trees themselves”
– Matt Dibona, GIS Analyst City of Cincinnati
Impervious surface mapping
Tree Canopy Gain (Green), Loss (Orange), and No Change (Purple)
Example of Tree Canopy and Tree Points Inventory
Key Results
The collected data and analysis yielded many key products for the City and County:
- The development of an impervious surface data layer, used by the MSD in the context of stormwater management.
- Precise measurement of tree canopy coverage, and the qualification of gains or losses in the canopy, leading to identification of areas of priority for planting.
- A map of existing tree canopy and possible vegetated tree canopy by neighborhood
- An erosion projection — particularly important for Cincinnati because of its hilly topography. Managing the tree canopy is important for controlling erosion.
- The PM 2.5 analysis; involving evaluating the loss and gain of tree model reforestation canopy growth to effectively demonstrate effects on air quality.
Learn More
We held an in-depth interview with the City of Cincinnati’s Matt Dibona (GIS Systems Analyst) and Crystal Courtney (Division Manager, Natural Resources) on a webinar held on September 21st, 2021. In this hour-long presentation, you can hear from Matt and Crystal with technical details on the project provided by Brian Coolidge, AppGeo’s tree canopy mapping expert, Jarlath O’Neil-Dunne, Director of University of Vermont’s Spatial Analysis Lab, and Mike Galvin, Consulting Arborist at SavATree.
