Comparative analysis of remote sensing and ground-based surveys in determining merchantable volume of a boreal forest stand

Abstract

Accurate volume estimations are pivotal for effective forest resource management, influencing stakeholders throughout the forestry industry. Traditionally, estimations relied on stem diameter measurements and geometric assumptions. However, advancements in remote sensing have revolutionized volume calculations, offering new possibilities for precision and efficiency. This thesis delves into volume estimations within the Romeo Mallette Forest of Northeastern Ontario’s Boreal Forest, employing a multifaceted approach that includes ground surveys, Ontario Forest Resource Inventory (FRI) data, and Remotely Piloted Aircraft System (RPAS)-based remote sensing. The objectives encompass evaluating the accuracy of FRI data, assessing ground surveys' precision, investigating RPAS. Additionally, the study aims to leverage FPInnovations' Single Tree Metrics and Stand assessment (STEMS), a pre-harvest inventory tool that utilizes consumer-grade RGB imagery from an RPAS, and to scrutinize the variance between estimated volumes and actual mill volumes. The study meticulously evaluates the efficacy of the STEMS algorithm against ground surveys and FRI merchantable volume estimates, utilizing the final Bill of Lading (BOL) as the control measurement. Remarkably, the initial RPAS flight path, harnessing STEMS technology, emerged as the most precise in estimating merchantable volume, yielding 129 m3

/ha compared to the final BOL measurement of 122 m3

/ha. In contrast, ground

surveys anticipated 134 m3

/ha, while the FRI data was the only underestimation at 106 m3 /ha. This singular study underscores the potential of STEMS in accurately estimating merchantable volumes in forestry, signaling a significant advancement in volume estimation methodologies.