A Novel Tree Biomass Estimation Model Applying the Pipe Model Theory and Adaptable to UAV-Derived Canopy Height Models

Takashi Machimura,Ayana Fujimoto,Satoru Sugita,Hiroaki Takagi,Kiichiro Hayashi

doi:10.3390/f12020258

Takashi Machimura, Ayana Fujimoto + Show 3 more

Open Access

https://doi.org/10.3390/f12020258

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Journal: Forests	Publication Date: Feb 23, 2021
Citations: 8	License type: CC BY 4.0

Affiliation: Osaka University, Nagoya University

Abstract

Aiming to develop a new tree biomass estimation model that is adaptable to airborne observations of forest canopies by unmanned aerial vehicles (UAVs), we applied two theories of plant form; the pipe model theory (PMT) and the statical model of plant form as an extension of the PMT for tall trees. Based on these theories, tree biomass was formulated using an individual tree canopy height model derived from a UAV. The advantage of this model is that it does not depend on diameter at breast height which is difficult to observe using remote-sensing techniques. We also proposed a treetop detection method based on the fractal geometry of the crown and stand. Comparing surveys in plantations of Japanese cedar (Cryptomeria japonica D. Don) and Japanese cypress (Chamaecyparis obtusa Endl.) in Japan, the root mean square error (RMSE) of the estimated stem volume was 0.26 m3 and was smaller than or comparative to that of models using different methodologies. The significance of this model is that it contains only one empirical parameter to be adjusted which was found to be rather stable among different species and sites, suggesting the wide adaptability of the model. Finally, we demonstrated the potential applicability of the model to light detection and ranging (LiDAR) data which can provide vertical leaf density distribution.

Highlights

Forests are essential for the conservation of biodiversity and soil and water resources as well as for providing forest products [1]
To promote the implementation of sustainable management of all types of forest has been stated as a target in Goal 15 of the United Nations’ Sustainable Development Goals (UN SDGs) [3], and the multiple functions and benefits of forests are directly and indirectly linked to various goals such as water and sanitation, sustainable energy, and climate change action [4]
Innovations in miniaturizing light detection and ranging (LiDAR) devices boarded on unmanned aerial vehicles (UAVs) [10,11,12] have enabled more accurate observations of forest canopy structure than those using the structure from motion (SfM) technique [13]

Summary

Introduction

Forests are essential for the conservation of biodiversity and soil and water resources as well as for providing forest products [1]. They can make significant contributions to the economy, livelihoods, and environment [2]. In recent years, unmanned aerial vehicles (UAVs) have been increasingly used owing to their low material and operational costs, and high-intensity data collection [5]. They are suitable for monitoring relatively small areas of forest stands at high resolution and in short intervals. Innovations in miniaturizing light detection and ranging (LiDAR) devices boarded on UAVs [10,11,12] have enabled more accurate observations of forest canopy structure than those using the SfM technique [13]

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