The Potential of Low-Cost 3D Imaging Technologies for Forestry Applications: Setting a Research Agenda for Low-Cost Remote Sensing Inventory Tasks

James Mcglade,Karin Reinke,Luke Wallace,Simon Jones

doi:10.3390/f13020204

Abstract

Limitations with benchmark light detection and ranging (LiDAR) technologies in forestry have prompted the exploration of handheld or wearable low-cost 3D sensors (<2000 USD). These sensors are now being integrated into consumer devices, such as the Apple iPad Pro 2020. This study was aimed at determining future research recommendations to promote the adoption of terrestrial low-cost technologies within forest measurement tasks. We reviewed the current literature surrounding the application of low-cost 3D remote sensing (RS) technologies. We also surveyed forestry professionals to determine what inventory metrics were considered important and/or difficult to capture using conventional methods. The current research focus regarding inventory metrics captured by low-cost sensors aligns with the metrics identified as important by survey respondents. Based on the literature review and survey, a suite of research directions are proposed to democratise the access to and development of low-cost 3D for forestry: (1) the development of methods for integrating standalone colour and depth (RGB-D) sensors into handheld or wearable devices; (2) the development of a sensor-agnostic method for determining the optimal capture procedures with low-cost RS technologies in forestry settings; (3) the development of simultaneous localisation and mapping (SLAM) algorithms designed for forestry environments; and (4) the exploration of plot-scale forestry captures that utilise low-cost devices at both terrestrial and airborne scales.

Highlights

Accepted: 25 January 2022Information is a key factor for the effective planning and management of any natural resource
These tables present the type of low-cost technology and sensor used to capture forest inventory, the method used to capture information with the sensor, the inventory measurements explored within the study and the number of stems recorded
The recent advancements in RGB-D sensors and simultaneous localisation and mapping (SLAM) algorithms has allowed for the exploration of alternative low-cost methods with benefits associated with timely data capture and processing, as well as low requirements for experienced technicians

Summary

Introduction

Accepted: 25 January 2022Information is a key factor for the effective planning and management of any natural resource. The following sections outline the predominant low-cost sensor approaches for 3D terrestrial forest inventory acquisition This includes the operating principles for each technology, in which errors may propagate within measurements derived from these approaches and their limitations in capturing 3D biophysical information in structurally complex forestry environments. The most common terrestrial CRP approach for estimating biophysical stem characteristics from point-cloud information is SfM [8] This is an iterative process that uses a series of overlapping images, captured from different viewing angles and orientations relative to the object of interest, to find matching features and simultaneously estimate camera location and scene geometry. These feature regions are used to simultaneously determine the relative 3D positions of cameras and features within an arbitrary coordinate system using a bundle adjustment

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