Last Updated on 2nd December 2022

Research and development of digital technologies for the forestry sector are transforming the industry and the way humans impact forests around the globe. With approximately 20.93Mha annual tree loss in 2018 worldwide, due to deforestation and forest degradation, it’s important that companies adopt sustainable ways of working. LiDAR in forestry is one example of modern technology that is helping to transform the industry.

Other industries such as mining, construction and real estate often rely on LiDAR too, due to its versatility and ability to capture useful and accurate data. As the technology develops, specialists are finding new ways to capture and use the data for a number of LiDAR forestry applications – here, we will explore how it’s being used, and the changes it has already made to the sector.

TLS is a useful tool for capturing forestry data. It’s commonly used for capturing highly accurate data beneath the tree canopy. With TLS, it’s possible to create high-resolution point clouds to measure parameters such as tree height and other structural information.

Due to the nature of the technology, it can be challenging to use TLS effectively on uneven terrain and it’s difficult to gather data from above the tree canopy. Additionally, it can be time consuming to scan large areas using TLS, as multiple scans need to be captured and overlapped to accurately showcase the whole environment.

Using a laser scanner that’s handheld or mounted to a pole or vehicle, is one of the easiest ways to capture data. Handheld mapping systems can map large areas in a short amount of time, and across tough terrains. The data accuracy is high enough for many forestry applications, and the ease of use of the data capture makes it repeatable.

The versatility of handheld mapping solutions, combined with other mapping methods like UAV, gives users accurate data quickly and efficiently. This data is starting to be used across the sector in applications to help with deforestation, forest planning and wildfire prevention.

The SFI SmartForest programme, from the Centres for Research-based Innovation scheme of the Research Council of Norway, aims to position Norway’s forestry sector at the forefront of digitisation by 2028. Its goal is to facilitate a free flow of information and real-time communication, which can help to increase productivity and reduce the environmental impact of the sector.

The programme’s team knew it wanted to use LiDAR to inform its research. As well as needing versatility, the team required highly-precise measurements to ensure they were monitoring the forest accurately.

Although TLS offered high levels of accuracy, it was too time consuming for their needs. They also considered a UAV-based solution, but it was less effective at penetrating thick vegetation so couldn’t capture the full data range required.

SFI SmartForest chose GeoSLAM’s ZEB Horizon, a mobile mapping system, to scan the dense and rough terrain. It enabled the team to quickly capture large volumes of data from the ground and from the air, collecting highly-accurate datasets and creating point cloud models to extract features including wood quality and biomass.

Following a successful initial period, the research programme will continue to use the mobile scanner to create accurate point clouds which serve as the basis for deep learning research opportunities.

Tom Potter, a doctoral researcher at the University of Leicester, UK, set out to develop a technique to estimate biomass and carbon more efficiently using state-of-the-art, mobile LiDAR sensors across multiple, complex forest environments.

The Eden Project in Cornwall, UK, houses the world’s largest rainforest and species from the Mediterranean, North America and Chilean terrains, as well as a ‘rainforest’ biome of more than 1,000 trees and plants. Tom chooses to gather data here to take advantage of the diverse datasets he could capture.

However, his time to scan was limited, as the area is open to the public and is a popular tourist destination. A fixed-point scanner would have struggled to capture the forest’s full mass, with each tree prone to obstructing each other and creating shadows.

The portable SLAM scanner was chosen because of its ability to collect data quickly. After collecting over 43,000 measurement points per second the whole environment was scanned by walking in a simple circular loop.

Forest landscapes are typically rural spaces, with uneven and challenging terrain. They’re densely populated, which can make it hard to capture measurements for individual trees without obstructing objects or creating problematic shadows.

Mobile mapping LiDAR scanners, such as the ZEB Horizon, overcome these challenges. It captures data up to 100m from the scanner and can be used as a handheld scanner or mounted to a pole, backpack, drone or vehicle, offering multiple ways to capture hard-to-reach areas with high levels of accuracy.

The time savings offered by mobile LiDAR are transforming the forestry sector. Now, taking measurements and surveying an area can take a couple of hours, rather than days on site-meaning it’s possible to make important decisions much quicker.

Additionally, with deep learning models and algorithms constantly improving, the data provided from LiDAR systems will only become more and more useful over time.