Connecticut ranks among the top 13 states in the nation for amount of forested land area with 55% of the state. An additional 20+% enjoys the beauty of urban tree canopies. Within Connecticut’s 149 towns, through the diverse and trecovered regions of the state, including private lands, public open space and conservation areas, Eversource maintains nearly 17,000 miles of overhead electric distribution lines.
Remote sensing technology allows utilities and researchers to observe and collect data on the whole land area within their purview. Laser scans, from aircraft-mounted sensors, can create a 3-D image of the earth’s surface, giving us information including tree locations and canopy heights in addition to more traditional aerial imagery. Among other things, maps made with combinations of these technologies can help us see where forests pose the greatest risk to infrastructure should a storm hit.
UConn’s remote sensing research team is studying effective, large-scale, automated assessments of roadside forest characteristics as well as utility infrastructure. Areas of greater risk to public safety or reliable power can be prioritized in Eversource’s vegetation management efforts.
For the majority of eastern and northwestern Connecticut towns (86), we are using aerial light-detection-and-ranging (LiDAR) scanners to create a 3-D map of vegetation in proximity to utility infrastructure. We are looking specifically in great detail at Greenwich, Connecticut, as part of our 3-D imaging for modernization study where we capture 20-100 points of data in each square meter of land space. In addition, the 3-D image data becomes an input to our Outage Prediction Modeling reflecting local roadside vegetation conditions.
Eversource also works closely with communities and forest practitioners to develop sustainable and storm-resistant forest management practices that preserve the regions character and the myriad benefits of the forest, while mitigating the risk to infrastructure.
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The purpose of this mapping research is to help the public and utility companies most optimally manage their roadside trees and forests to increase storm resistance, thereby reducing weather-related power outages. It will also feed more information to the UConn Outage Prediction Model, helping to increase accuracy of predictions of outages during storm events. The specific goals for this project are:
As of Spring 2018
Jason Parent, Assistant Research Professor in the Department of Natural Resources and the Environment, University of Connecticut, leads the project task. |
John Volin, Professor and Department Head of Natural Resources & the Environment, University of Connecticut |
Tom Meyer, Professor in the Department of Natural Resources and the Environment, University of Connecticut |
Chandi Witharana, Visiting Assistant Professor, Department of Natural Resources and the Environment, University of Connecticut. |
For more information, please contact Jason Parent (jason.parent@uconn.edu) Members of the media, please contact Center Manager Malaquias Pena (mpena@uconn.edu) directly. |
Eversource Energy Center | Innovation Partnership Building: 159 Discovery Drive, Unit 5276, Storrs, CT 06269-5276 | E-Mail: eversourceenergycenter@uconn.edu