Glossary
LiDAR: Light Detection And Ranging
"LiDAR is an active remote sensing technique in the sense that the sensor emits its own light. This contrasts with traditional passive remote sensing techniques, such as satellite imagery and aerial photography, which rely on reflected radiation from the surface originating from the sun. LiDAR instruments emit short-duration laser pulses that illuminate a target and measure its location in three dimensions (x, y, and z). Given that the time the pulse is emitted and received back to the sensor is known, as well as the exact position of the sensor in space (including the roll, pitch, and yaw when on board an aircraft), the distance to the object can be calculated and the vertical distribution of the surface measured. LiDAR sensors emit near-infrared (NIR) light, typically between 900 and 1100 nm. In this wavelength range, vegetation foliage is partly transmissive, allowing the NIR light to pass through the canopy to the ground. With each interaction of the light with the canopy elements, such as foliage, some of the light is returned to the sensor, allowing for a digitisation of the vertical distribution of the canopy tissues." Source: Davies and Asner, 2014
ALS: Airborne Laser Scanning - platform: airplane, helicopter etc.
TLS: Terrestrial Laser Scanning - platform: tripod + reflectors for georeferencing
MLS: Mobile Laser Scanning - platform: mobile vehicle (car)
ULS: UAV-borne Laser Scanning - platform: UAV (unmanned aerial vehicle (drone))
footprint beam divergence scan angle flight altitude pulse repetition frequency
echo FWF discrete echo single echo first last registered
point density radiometric calibration
DSM: Digital Surface Model - This model includes objects on it (vegetation, buildings, etc.).
DTM: Digital Terrain Model - This model is interpolated based on ground points.
nDSM: Normalized Digital Surface Model - This model is a normalized surface model (nDSM=DSM-DTM). This value represents the absolute object's height above ground.
CHM: Canopy Height Model - Represents the absolute height of canopy above ground like nDSM, however, this term is more commonly used in forestry applications.
Figure: Illustration of DSM and DTM Source
Feature: Feature is a specific representation of data. Feature can be additional attributes assigned to the original x,y,z dataset, after calculation based on a given neighborhood (for example: eigenvalues) or a raster layer consisted statistical derivatives from the point cloud. Different articles named it differently: LiDAR metrics or LiDAR derivatives.