| dc.description.abstract |
This project develops a unique methodology in identifying individual tax parcels in
North Carolina as possible locations for generating avoided conversion carbon offset
credits, as well as including co-benefits such as ecological conservation and corridor
viability. We used LiDAR canopy height data to estimate current and future carbon
storage on each parcel, which were discounted based on their respective probability
of conversion as determined by the randomForest statistical model. Conservation value
was added to the carbon value in order to accommodate the multi-objective interests
of our client, Duke Carbon Offset Initiative. The result of this project is a flexible
GIS model that uses the three major inputs (carbon, conversion risk, conservation)
to rank parcels for suitability based on the interests of the user. This unique method
will help DCOI obtain their 2024 carbon-neutral goals for Duke University, protect
key biodiversity areas, and set a framework for other academic institutions.
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