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Abstract

Richmond has a large quantity of trees which currently cannot be efficiently monitored for individual tree health. This lack of monitoring results in high mortality rates. It is to the benefit of the city financially that these trees are saved instead of having to be replaced. The solution includes the delivery of an Unmanned Aerial System (UAS) with modified camera technology for image processing and log identification utilizing Normalized Difference Vegetation Index (NDVI) values as numerical indicators of health. A low-cost, Federal Aviation Administration (FAA) compliant system was required for solution implementation and budget appropriations. It was decided aerial imagery provided a fast, efficient method of data collection for arborist deployment to key zones. Successful implementation of the system includes aerial imaging of tree canopies and relevant flagging of unhealthy trees for further inspection. Automated waypoint navigation was not able to be implemented in the current iteration due to software complications. Appropriate FAA exemptions and pilot licenses still need to be acquired for the legal deployment of the system. The UAS will provide fast data collection to enable preventative action by the arborists to save trees and improve overall quality of life in the city.

Publication Date

2016

Keywords

Electrical and computer engineering, NDVI, NIR, reflectance, UAS

Disciplines

Electrical and Computer Engineering | Engineering

Faculty Advisor/Mentor

Carl Elks

Faculty Advisor/Mentor

John Syndor

VCU Capstone Design Expo Posters

Rights

© The Author(s)

Date of Submission

August 2016

Tree Canopy Analysis: Improving Forest and Tree Health through Aerial Spectral Measurement

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