Modeling the Forest Structure and Basal Area of the Medway Community Forest Coop through UAV-derived Remote Sensing Imagery
2021
Jarrar, Heba | Caspersen, John | Rodger, Mary Jane
In 2019, an Unmanned Aerial Vehicle (UAV) was flown over four different regions of the Medway Community Forest Coop, comprising 4908 ha of the total area. The purpose of this imagery was to obtain accurate forest metrics to aid in forest management. This capstone project aimed to model basal area and forest structure from the UAV-derived canopy height model and ground data. The purpose of this study was to aid in the remediation of the forest due to the intensive clearcutting that occurred in the region prior to the community forest being established in 2015. Four models were developed that predicted the following variables: basal area and three forest structural indices (the Gini Coefficient, the Berger-Parker Index, the McIntosh Evenness Index). There was a general positive relationship seen in all models where higher structural diversity and larger basal areas correlated with higher canopy heights. The basal area model was found to have an R2 of 0.55. The forest structural diversity indices models were found to have lesser accuracies with values of the following: Gini Coefficient (R2 = 0.28), McIntosh Evenness Index (R2 = 0.21) and Berger-Parker Index (R2 = 0.32). The models developed will help with assessing and identifying harvest areas and appropriate prescription treatments. Identifying areas with low basal area and canopy heights (i.e. young stands) will also help with planning for how stands will grow overtime, and whether pre-treatment prescriptions to promote the growth of the stands is necessary. Lastly, this project will open up the opportunity for more remote sensing imagery to be analyzed and collected in the area for future studies.
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Эту запись предоставил University of Toronto