Terrestrial LiDaR (Light Detection and Ranging) scanners are able to acquire three-dimensional data of individual trees and the surrounding forest environment in a rapid and accurate way. This means that the technology has a tremendous potential to revolutionize the forestry industry at different levels, from operational forest management to worldwide political decisions.
In this article, we describe some of the applications of ground-based mobile mapping systems and how they compare to traditional methods in forest management.
Usually, forest inventories are based on field samples that typically consist of a small forest area. The data is collected through tree-by-tree measurements that are aggregated into plot-level means and totals. Therefore, the accuracy of the inventory depends on the quality of the sample.
Traditionally, the tree-by-tree measurements are performed using simple tools (e.g., clinometers and calipers) to get some basic attributes of each tree, such as height and Diameter at Breast Height (DBH). These methods are time-consuming and the usage of the resulting data to obtain other important attributes, like stem volume and biomass, relies on the accuracy of allometric models.
Ground-based 3D scanners, like our BMS3D backpack, can replace these methods by improving the work efficiency with a millimetric level of accuracy. With individual tree detection, scanners can, not only replace manually measured attributes, but also provide more attributes, including quality, stem curve, and timber assortments at different levels of detail.
Allometric model development is an important subject in forestry research. These models are conventionally constructed by using destructive sampling methods for each individual tree, which is an expensive and labor-intensive task.
In contrast, by using specialized software, mobile 3D scanners allow for individual tree detection, providing a highly accurate, non-destructive, and automated measurement method to develop allometric models.
Tree growth monitoring is the comparison of some tree attributes, such as height, DBH, and stem volume over time. Analyzing this growth provides information about the health of the forest, but also on how environmental factors are influencing tree growth. Monitoring the height:diameter ratio, for example, is a good way to determine the appropriate moments for thinning the forest but also to assess the stand stability, particularly for conifer trees.
The efficiency of mobile laser scanners makes it easy to perform consecutive scans for the same plot area over time. Therefore, time series analyses can be performed to evaluate tree growth in height, DBH, and/or volume.
Furthermore, tree growth models can be used to assess timber harvesting potential and allow for data-driven decisions for forest management.
Canopy, terrain, and elevation models
Mobile 3D scanners can capture a whole three-dimensional representation of the forest. This means that all of its components can be analyzed individually by using point cloud segmentation and classification.
The point cloud data can be used to generate a Digital Terrain Model (DTM) that includes all the trees and vegetation above ground. By using filtering algorithms, such as the Cloud Simulation Filter, one can isolate all the points belonging to the ground, which allows for the generation of a Digital Elevation Model (DEM). By subtracting the Digital Elevation Model from the Digital Terrain Model, a Canopy Height Model can be generated, representing the height of the trees as a continuous surface.
Canopy Height Models can be useful for a variety of applications. Some examples of these applications are:
- fire risk analysis
- forest inventory analysis
- solar energy assessment based on tree shade
- identification of dominant trees
Digital Terrain Models can also be very useful for forest management. For example, they can be used to determine slopes, which most of the time can be correlated to soil conditions, vegetation, and land use capability. Knowing the topography of the forested area can also be useful for planning logging activities, determining access roads and the type of harvesting equipment needed.
Many of the same benefits of using terrestrial mobile scanners for forest inventories are also shared with forest ecology studies. In both research areas, basic tree attributes, such as DBH and tree height, are collected and 3D scanners facilitate the measuring of these attributes.
However, in ecology studies, individual tree data is not always sufficient. Information about the three-dimensional arrangement of the forest canopy is needed. This is especially important for ecological studies because the canopy structure can have a direct influence on light interception, CO2 fluxes, and even the presence of specific organisms and wildlife.
How can such a complex structure be described? For this, researchers use different measurements, such as leaf area index (LAI) and gap fraction. Leaf area index indicates the ratio between leaf area and ground area in the forest, and gap fraction is the probability of a ray of light going through the canopy without being intercepted by foliage from the forest canopy.
Conventional methods of measuring these attributes involve time-consuming and labor-intensive tasks, which could even make it impossible to collect sufficient samples to accurately characterize large forests. So, how can laser scanners make these tasks more efficient? By providing a three-dimensional point cloud, the forest canopy can be analyzed in a completely digital and automated way, saving hours of work and generating accurate results.
Terrestrial mobile mapping systems, such as our BMS3D backpack, are innovating the forestry industry by providing an efficient way of capturing three-dimensional data of the forest environment. This data can be used to determine individual tree and forest canopy attributes much faster than conventional methods, and with the same or better accuracy. This technology is here to stay and is innovating rapidly. Will you be able able to keep pace?