Instead of dangerous operations, LiDAR makes forest resource surveys safer and more efficient

Application Background

Forest resource survey, as the main means to master the persent situation and development of forest resources, is of great significance to the management and protection of sustainable forest resources.

The traditional forest survey technology is relatively backward and extensive. Investigators need to go deep into the hinterland of the forest, with high labor intensity and unpredictable risks. The acquisition of forest parameters depends on field sampling and field measurement by field workers. The means used are only limited to relatively original measuring instruments such as handheld altimeter, DBH ruler and tape measure. It is not only time-consuming and laborious, but also can only obtain the information of small-scale forest area, and the investigation scope is not comprehensive.

The rapid development of remote sensing technology brings hope for the realization of efficient and large-area forest resources survey. However, due to the reality that optical remote sensing images can not "Penetrate" the forest canopy and obtain the forest vertical structure information, the available effective stand parameters are limited.

Application Direction

LiDAR technology is different from traditional optical remote sensing, which relies heavily on external light sources such as the sun. It has the ability of all-weather operation by actively emitting laser beams to detect targets. With the support of multiecho technology, the pulsed laser beam emitted by lidar can reach the tree trunk and even the ground through the forest gap to obtain its three-dimensional point cloud data, so as to completely obtain the forest vertical structure information, and finally extract the forest parameter information such as tree height, DBH and volume.

At present, the investigation and monitoring of large-area forest resources is mainly in the form of airborne LiDAR, supplemented by terrestrial and SLAM 3D laser scanners. LiDAR technology is mainly applied to the extraction of basic stand parameters such as plant number, tree height, DBH and canopy density, as well as the estimation of stand volume.

01 Number of stand

The number of trees is the quantity information of trees in a given area, which is an important index to describe the stand density. The tree number extraction algorithm is based on the canopy height model (CHM) produced by point cloud data for local maximum detection. After traversing the CHM to get the maximum value in the window, the crown vertex can be obtained, so as to get the plant number information.

02 Stand tree height

Stand height is not only a reflection of tree growth, but also an important parameter for estimating forest volume. LiDAR technology can obtain not only the forest canopy point cloud, but also the terrain point cloud under the forest canopy. Based on the CHM obtained by the two processes, the single tree height parameters can be extracted by using the crown vertices.

03 DBH of trees

DBH is one of the important parameters to evaluate the growth status of trees.

The manual measurement method is to use the DBH ruler to measure the diameter of the tree 1.3m away from the root of the tree as the DBH parameter. The method of extracting tree DBH information based on terrestrial or SLAM LiDAR point cloud data is Hough fitting circle method. This method is used to segment single tree point cloud. On this basis, the point cloud data at the height of 1.3m DBH is intercepted to generate the corresponding two-dimensional grid image. Then, the Hough transform fitting circle algorithm is used for circular fitting, and the obtained circular diameter can be regarded as tree DBH.

04 Stand canopy density

Canopy density is the macro reflection of forest growth and the key factor to determine the cutting intensity. Canopy density is the percentage of canopy projection and forest land area.

Traditional remote sensing methods need to use complex image processing algorithms to segment the forest canopy from Orthophoto Image (DOM), and then calculate the canopy density by counting the ratio of canopy to forest area. LiDAR based on multi-echo technology obtains canopy density by directly counting the ratio of vegetation points of the first echo to the total points of the first echo, which is simple and efficient.

Advantages of LiDAR 

LiDAR has obvious advantages in forest resources investigation and monitoring:

1. High operational efficiency to meet the needs of large-scale forest resources investigation

Taking Hi-Cloud airborne LiDAR PM-1500 as an example, it has four echoes and a scanning speed of up to 2 million points / s, which can effectively obtain comprehensive three-dimensional information such as branches, trunk and surface, so as to accurately extract stand parameters. In addition, thanks to the 1500 meter long ranging, it is not only fearless of the mountain terrain with high drop, but also has a large coverage area of single operation, and the efficiency of investigation operation has been greatly improved.

2. Less manual intervention,  personnel safety

The operation radius of PM-1500 airborne LiDAR can reach 30km, and the task can be executed automatically without manual intervention after route planning. Operators do not need to go deep into the forest area, so as to ensure the safety of personnel investigation and avoid accidents.

3. Rich results of forest resources survey 

In addition to the conventional parameters such as stand number, crown width and canopy density that can be obtained by conventional remote sensing means, LiDAR technology can also directly obtain the parameters of tree height and DBH and accurately estimate the stand volume, so as to provide more accurate and comprehensive parameter information for forest resources investigation.

4. The data is objective, accurate and traceable

Relying on field sampling survey manually, the selection of survey scope and objects is often random and subjective, and the survey activity can only be carried out once without traceability, which may lead to the difficulty of ensuring the objectivity and accuracy of the survey results.

Based on LiDAR technology, on the one hand, the forest point cloud data covering the whole range can be obtained, on the other hand, the automatic extraction of the overall stand parameters within the range can be realized based on the point cloud data processing algorithm.

In addition, through the fusion processing of airborne, terrestrial, SLAM and other multi-source LiDAR data, it can even meet the requirements of more detailed single tree stand parameter extraction. LiDAR technology has incomparable objectivity and effectiveness in extracting stand parameters.