Results

Results

Accurate, rapid, and low-cost inventory of forest stands enables reliable monitoring and decision-making in sustainable forest management. The end result of LiDAR technology is usually 3D point clouds, since for each point that receives the pulse, the distance at which the sensor is located (by means of the speed of light) and its coordinates can be calculated.

The point cloud can be generated since light pulses are able to penetrate semi-permeable surfaces, such as tree covers. That is, not only is the plant canopy continuously scanned, but the ground surface is also collected, whether or not it is covered by vegetation.

Accurate, rapid, and low-cost inventory of forest stands enables reliable monitoring and decision-making in sustainable forest management. The end result of LiDAR technology is usually 3D point clouds, since for each point that receives the pulse, the distance at which the sensor is located (by means of the speed of light) and its coordinates can be calculated.

The point cloud can be generated since light pulses are able to penetrate semi-permeable surfaces, such as tree covers. That is, not only is the plant canopy continuously scanned, but the ground surface is also collected, whether or not it is covered by vegetation.

Each point is classified into one of the possible categories (soil, low vegetation, medium vegetation, high vegetation, noise, etc.), depending on the intensity of the return, and the spatial configuration of the points.

With the points classified as vegetation, it is possible to predict the variables of the forest mass based on statistics and variables of the cloud using software based on complex algorithms that allow obtaining a precision product of the spatial characteristics of the scanned objects, and all the variables that define the state of the cloud.

 

Captura_hunde

Each point is classified into one of the possible categories (soil, low vegetation, medium vegetation, high vegetation, noise, etc.), depending on the intensity of the return, and the spatial configuration of the points.

With the points classified as vegetation, it is possible to predict the variables of the forest mass based on statistics and variables of the cloud using software based on complex algorithms that allow obtaining a precision product of the spatial characteristics of the scanned objects, and all the variables that define the state of the cloud.

Captura_hunde

Benefits of LiDAR Laser Technology

Lower the costs and reduce the times to set up of the Forest Status of the instruments of Sustainable Forest Management

Incorporate more precise and automated calculation tools in the evaluation of the Inventory

Correct limitations of airborne LiDAR, for more accurate and reliable information on dasometric and dendometric parameters

Provide higher quality LiDAR data to potential end users, who do not have tools to access this information

Need to develop new software and forest calculation algorithms, in friendly environments, for the automatic extraction of the main tree and mass variables.