The objective was to obtain a statistical model to estimate the operational performance of cutting trees with a chainsaw in the natural tropical forest north of Mato Grosso state. One-hundred-and-fifty-one operational cycles of selective logging for commercial purposes were registered. In each cycle, the effective time for cutting, the diameter of the trees, commercial height, the number of logs per tree, and the distance between trees was determined. A step-by-step regression analysis was performed to obtain the coefficients of the models and statistical parameters. The result of the analysis concluded that the most accurate model to estimate the operational performance is the one that transforms the diameter variable at breast height (DBH) squared and also includes the variables number of logs per tree and distance between logged trees.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.