Sampling strategies using panoramic photographs

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Good forest management requires good management tools and good forest inventory data. Efficient design of forest inventories requires decisions regarding the number and spatial arrangement of sampling units as well as the type of sampling unit utilized. For most forest inventories in Canada, Bitterlich's angle count sampling (ACS) is used. ACS coupled with efficient subsampling of trees for detailed stem measurements is generally cost-effective and less prone to measurement bias and error than other commonly employed sampling units. In this proposal, ACS is applied to 360-degree panoramic photographs. Image analysis algorithms are proposed that will automate the detection and measurement of trees and field sampling techniques to correct for count biases due to hidden trees are proposed.