ESTIMATING DIAMETER AND HEIGHT DISTRIBUTIONS FROM AIRBORNE LIDAR VIA COPULAS

Authors

  • Ting-Ru Yang Faculty of Forestry and Environmental Management University of New Brunswick
  • John A Kershaw Faculty of Forestry, University of New Brunswick

Keywords:

stand structure, height-diameter relationships, bivariate distributions, copulas, moment-based parameter recovery

Abstract

Estimates of quantitative variables in forest stands often are required. Light Detection and Ranging (LiDAR) can create three-dimensional point clouds of forest structures and ground surface
elevation maps. These features are useful for quantifying forest stand parameters such as volume and canopy height at broad scales. This study explores the potential of applying copulas and LiDAR metrics to obtain diameter and height estimates. Predicted values were compared with field measurements. Diameter and height distributions were obtained using moment–based parameter recovery and prediction of moments using nonlinear least squares from LiDAR attributes. We then used copula methods to link the diameter and height distributions. Using the diameter and height distributions, other attributes such as volume or carbon content can be estimated and summed to obtain area-based estimates.

Author Biography

  • John A Kershaw, Faculty of Forestry, University of New Brunswick

    Professor of Forest Biometrics

    Faculty of Forestry and Envir. Mgmt

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Published

2022-04-30

Issue

Vol. 14 No. 1: MCFNS April 30, 2022

Section

GIS and Remote Sensing

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How to Cite

ESTIMATING DIAMETER AND HEIGHT DISTRIBUTIONS FROM AIRBORNE LIDAR VIA COPULAS. (2022). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 14(1), 1-14(14). https://mcfns.com/index.php/Journal/article/view/14.1

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