Aboveground Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil

Marcus D’Oliveira,Eben Broadbent,Ricardo Mello,Evandro Figueiredo,Danilo Almeida,Luis Oliveira,Marcelo Oliveira-Da-Costa,Felipe Avino,Lúcio Jorge,Manuel Ferreira,Angelica Zambrano,Ben Wilkinson,Carlos Silva,Pedro Brancalion,Gabriel Prata,Leomar Junior,Daniel Papa,Rafael Albuquerque

doi:10.3390/rs12111754

Abstract

Tropical forests are often located in difficult-to-access areas, which make high-quality forest structure information difficult and expensive to obtain by traditional field-based approaches. LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-efficient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal differences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 ± 1.8 vs. 381.2 ± 58 pts/m2). Differences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 ± 0.09 vs. 0.42 ± 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation models and estimated AGB. Our results validate the ability for UAV-borne LiDAR sensors to accurately quantify AGB in dense high-leaf-area tropical forests in the Amazon. We also highlight new possibilities using the dense point clouds of UAV-borne systems for analyses of detailed crown structure and leaf area density distribution of the forest interior.

Highlights

Tropical forests are often located in remote and difficult-to-access areas
Light Detection And Ranging (LiDAR) has multiple applications in the planning and monitoring of activities related to forest management through the assessment of digital elevation and surface models with sub-meter accuracy [7,8,9,10,11], enabling surveying of areas difficult to access at relatively low cost
The GatorEye produced about 35 times greater density point clouds than the aircraft system, averaging 381.2 ± 58.2 returns m−2 versus 11.0 ± 1.8 returns m−2, respectively (Table 4, Figure 2A,B)

Summary

Introduction

Tropical forests are often located in remote and difficult-to-access areas. field data collection costs are high, which forces compromises in the measurements collected or the number of locations sampled. Airborne Light Detection And Ranging (LiDAR) data have been widely used to produce structural parameter estimates of both temperate and tropical forests and to monitor native and commercial forests [1,2,3,4,5]. This technology provides a quick and complete assessment of forest structure, which allows the calculation of metrics such as canopy height, wood volume, biomass, and carbon stocks [4,6]. Challenges in obtaining data are considerable for regions that are furthest away from population centers where the companies providing these services are usually located (e.g., [7]), which limits the use of LiDAR surveys—notably those that require repeated flights over the same area or that do not have large budgets for data acquisition

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