Estimation of tropical forest tree diameter at breast height from airborne LiDAR metrics

Issue Date

2015

Abstract

LiDAR is limited to getting the height of forest canopies. This paper describes methods and results to estimate the average diameter at breast height (DBH) by regressing parameters that were derived from airborne LIDAR. Specifically it aims to estimate the DBH of trees at the study area using derivative metrics from airborne LiDAR data. The study site is at Molawin-Dampalit, a two-hectare plot managed by Makiling Center for Mountain Ecosystems, Los Baños, Laguna. The plot was divided to 20m, 10m and 5m subplots or grids. The field DBH data and coordinates were also obtained. Linear and log-linear regression models were developed depending on these grid sizes to estimate the average DBH per grid. After applying data transformation to improve each model, all three grid sizes showed promising results in estimating DBH. Linear regression analysis showed an r2 of 0.72, 0.83, 0.70 for 20 × 20m, 10 × 10m, 5 × 5m grids, respectively. For the loglinear, 10 × 10m grid showed the highest r2 of 0.67 followed by 20 × 20m (r2=0.56) and 5 × 5m grid (r2=0.05). The method poses a compliment alternative to forest inventory plots as a means of assessing forest conditions.

Source or Periodical Title

ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings

Page

1-11

Document Type

Conference Paper

Physical Description

maps, illustrations, tables, graphs

Language

English

Subject

Biomass, GIS, Regression analysis, Remote sensing, Tree metrics

Digital Copy

yes

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