While foresters don’t necessarily have to abandon their diameter tapes and vertex hypsometers, there is no denying that rapidly-evolving remote sensing technologies are revolutionising forest management practices.
Field-based inventory methods and sampling designs can estimate variables such as height, volume, basal area and number of trees fairly accurately, if enough sampling plots are included, but this approach is labour-intensive and costly.
An emerging, diverse collection of platforms, sensors, algorithms and efficient processing workflows offer opportunities across the forestry sector to gather more reliable and effective information. It is vital that the data collected can be easily accessed and applied to practice.
FWPA’s RD&E program has provided funding for a series of projects focused on the evaluation and application of remote sensing technology for the Australian forestry sector.
The most recent of these, “ Optimizing remotely acquired, high resolution remotely sensed data for plantation inventory”, edited by Drs Michael Watt and Christine Stone, is available on the FWPA website.
The aim of the project, led by industry partner Scion, was to optimise the extraction and processing of meaningful information from data which were acquired using LiDAR (Light Detection and Ranging) sensors mounted on light aircraft, such as helicopters, and UAVs.
Several remote LiDAR systems were evaluated in relation to their specifications and procedures for optimal data acquisition. This important project brought together internationally recognised expertise – in remote sensing, Airborne Laser Scanning (ALS) and UAV technologies – to harness the rapid technological advances in data capture and processing as a tool for forest management.
The team included researchers from the University of Tasmania’s TerraLuma group, the New Zealand forest research agency Scion, the University of Sydney’s Australian Centre for Field Robotics and the NSW Department of Primary Industries, as well as a collaborative engagement with industry through Interpine and Indufor Asia Pacific.
The project focused on using point cloud data to capture the shape and structure of the canopy surface, allowing greater access to sub-canopy information such as stem characteristics.
A point cloud is a set of data points in space. The data is collected by laser scanners beaming pulses of light waves to the external surfaces of objects (e.g. trees). The points where the beams make contact are used to create 3D images of the targeted objects.
The researchers compared a variety of 3D visualisation software packages for viewing dense point cloud datasets and looked at the potential of applying immersive virtual reality technology for the on-screen assessment of individual tree stems.
Hopefully there will be a broader operational adoption of dense point cloud data by plantation growers in Australia and New Zealand, for the assessment and monitoring of plantations at both the stand and tree-level scales.
As technologies advance, they provide increased direct benefits — e.g. more accurate and reliable data capture — as well as indirect benefits, such as increased safety and reduced operational time and costs through remote access to difficult or dangerous locations for on-ground inventory crews.
Source: R&D Works, November 2018
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