Light Detection and Ranging (LiDAR) is a remote sensing method used to examine the Earth's surface by generating a precise three-dimensional representation of its characteristics. The sensing method uses light in a form of a pulsed laser to measure the distance of surfaces on the earth. These pulsing light and other data recorded by the airborne system are what generate the three-dimensional representation.
Once captured, points are stored as data in a three-dimensional point cloud representing buildings, vegetation, and the ground surface, among other features. Since airborne LiDAR is able to sample large-scale areas at a high resolution, typically collecting four points of information within a square meter, high precision datasets can be produced. Its final products, such as a digital elevation model, detailed elevation contours, and the classification of ground returns are frequently applied in the field of forestry and hydrology. The detailed image of the Earth’s surface created by LiDAR can be used to describe the characteristics of tree canopy such as height, density, and degree of closure.
It is possible to reach a robust system of green infrastructure — a key goal particularly in the face of the risk of mass extinctions — by incorporating trees into development projects and restoring forests. The key to accomplishing that goal lies in the right questions, and LiDAR could help HARC scientists to address questions such as how differing tea canopy structures impact stormwater retention or how the remaining forest canopy can best be leveraged.
The answers to these questions can be used to plan tree plantings for forest restorations or green infrastructure projects, and to help guide conservation efforts by identifying areas of forest canopy ideal to mitigate area-wide floods.