Analysis of Canopy Gaps of Coastal Broadleaf Forest Plantations in Northeast Taiwan Using UAV Lidar and the Weibull Distribution

Jonathan Wang,Shu-Lin Deng,Cho-Ying Huang,Chih-Hsin Chung

doi:10.3390/rs14030667

Jonathan Wang, Shu-Lin Deng + Show 2 more

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https://doi.org/10.3390/rs14030667

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Abstract

Canopy gaps are pivotal for monitoring forest ecosystem dynamics. Conventional field methods are time-consuming and labor intensive, making them impractical for regional mapping and systematic monitoring. Gaps may be delineated using airborne lidar or aerial photographs acquired from a manned aircraft. However, high cost in data acquisition and low flexibility in flight logistics significantly reduce the accessibility of the approaches. To address these issues, this study utilized miniature light detection and ranging (lidar) onboard an unmanned aircraft vehicle (UAVlidar) to map forest canopy gaps of young and mature broadleaf forest plantations along the coast of northeastern Taiwan. This study also used UAV photographs (UAVphoto) for the same task for comparison purposes. The canopy height models were derived from UAVlidar and UAVphoto with the availability of a digital terrain model from UAVlidar. Canopy gap distributions of the forests were modeled with the power-law zeta and Weibull distributions. The performance of UAVlidar was found to be superior to UAVphoto in delineating the gap distribution through ground observation, mainly due to lidar’s ability to detect small canopy gaps. There were apparent differences of the power-law zeta distributions for the young and mature forest stands with the exponents λ of 1.36 (1.45) and 1.71 (1.61) for UAVlidar and UAVphoto, respectively, suggesting that larger canopy gaps were present within the younger stands. The canopy layer of mature forest stands was homogeneous, and the size distributions of both sensors and methods were insensitive to the spatial extent of the monitored area. Contrarily, the young forests were heterogeneous, but only UAVlidar with the Weibull distribution responded to the change of spatial extent. This study demonstrates that using the Weibull distribution to analyze canopy gap from high-spatial resolution UAVlidar may provide detailed information of regional forest canopy of coastal broadleaf forests.

Highlights

IntroductionCanopy gaps (or “gaps”, used interchangeably hereafter), caused by large branch losses, individual tree death or several treefalls due to natural processes or disturbance, play a pivotal role in regulating forest ecosystems [1,2,3,4,5,6,7]
The forests are dominated by Casuarina equisetifolia, Cerbera manghas, Terminalia catappa, Trema orientalis, Pongamia pinnata, Melaleuca leucadendra, Hibiscus tiliaceus and Pandanus odoratissimus
This study assessed the feasibility of UAVlidar and UAVphoto to map canopy gaps of young and mature broadleaf plantation forests in a coastal region of northeastern Taiwan, and tested the feasibility of using different mathematical functions to characterize canopy gaps of forest stands

Summary

Introduction

Canopy gaps (or “gaps”, used interchangeably hereafter), caused by large branch losses, individual tree death or several treefalls due to natural processes or disturbance, play a pivotal role in regulating forest ecosystems [1,2,3,4,5,6,7]. The metrics commonly utilized to quantify canopy gaps are the gap depth and size. Gap depth is defined as openings in the forest canopy extending down to an average height ≤ 2 m aboveground [15]. High variation in canopy gap size may be attributed to biotic and abiotic factors such as the number of trees that have fallen, died or been removed. The range of gap sizes of hardwood and broadleaf stands typically vary

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