Forest plantations make up a large percentage of managed forest land globally. Assessing plantation productivity is vital from both commodity production and carbon management standpoints. Measuring the productivity of these areas is essential given their rapid growth and turnover. Transparent metrics to compare reported carbon storage with estimated values are required for internationally transferred mitigation outcomes under Article 6.2 of the Paris Agreement. Data from the Global Ecosystems Dynamics Investigation (GEDI) provide an excellent opportunity to measure plantation forests over large areas. We focused our efforts on Eucalyptus in southern Brazil and used data from an industrial partner to investigate plantation metrics (height, diameter, volume, stems per hectare, etc.) and to create a model of plantation diameter using Support Vector Regression (SVR). SVR enabled a robust model of tree diameter even given the heteroskedasticity and spatial auto correlation present in the GEDI data, which deleteriously impacted attempts at linear modeling. We could predict tree diameter in these plantations to within 1 cm using space-borne lidar, with broad implications for using space-borne lidars to monitor carbon accretion in secondary forest plantation. / Master of Science / Forest management practices have shifted in some cases to very crop-like forest plantings. These areas are functionally different from a 'natural' forest. Understanding the structure of these areas in a rapid and consistent manner is important to quantify the amount of carbon stored within these forests for international climate agreements such as the Paris Agreement. This effort focuses upon Eucalyptus forests in Southern Brazil. Using measurements from a lidar instrument (a lidar system fires a laser beam from space to the ground, recording the 'deflection' of the laser beam and the amount of time it takes to return to the sensor to measure features on the ground) we were able to measure the diameter of the trees to within a centimeter in these forests.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/110918 |
| Date | 23 June 2022 |
| Creators | Miller, Benjamin Daniel |
| Contributors | Forest Resources and Environmental Conservation, Wynne, Randolph H., Thomas, Valerie A., Schons Do Valle, Stella Zucchetti |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Coverage | Brazil |
| Rights | Creative Commons Attribution-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-sa/4.0/ |
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