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))
This section based on Milutin Milenković (TUWien) NEWFOR summer school presentation
Discrete Echo LiDAR: This echo registration technique is more commonly used during the national-wide ALS campaign. In this case, the waveform is processed onboard and each peak saved as each return (along with intensity). This measurement technique produces mostly 4 number of returns.
Full Wave Form (FWF) LiDAR: Recording the entire return signal using a sampling interval of ~1ns. This measurement technique allows analyzing the waveform directly and during a Gaussian decomposition process adding extra attributes regarding each echo: (Intensity), Range, Echo width. This measurement technique is producing up to 15 echoes (!) very useful attribute for vegetation structure analysis.
Echo: "Temporally connected part of the whole backscattered laser power that was detected by the receiver and that can be allocated to a certain reflecting surface element." OPALS Glossary
Intensity: Return strength of the laser pulse that generated the point. Intensity is depending on view angle, distance to the sensor, angle of the target to incoming/outgoing beam. This is why radiometric calibration is required before the usage of intensity attribute.
Pulse Repetition Rate or Pulse Repetition Frequency: number of emitted pulses per second (typical values in ALS: 10 – 400 kHz)
Footprint: "Illuminated area(s) of the divergence of the laser beam." OPALS Glossary. Small-footprint and large footprint laser scanning exist.
Beam divergence: "(Whole) Angle of the widening of the laser beam. Due to the typically varying energy distribution within the laser beam, the angle is limited to the region where the energy decrease from the maximum follows the ratio of 1/e^2."OPALS Glossary
Point density: Number of points per area (mostly m2). This is a general information about the LiDAR data quality. Average point density is depending on flight height (altitude) (h [m]), flying speed (v [m/s]), effective pulse frequency [Hz], Scan opening angle [deg]. One way to calculate: average point density= points per second/area per second=PRF/swathwidthv=PRF/2hvtan(alpha/2).
Scanning mechanism: this parameter causing different sampling pattern. Most used ones: rotating mirror, oscillating mirror, Fiber scanner, Nutating mirror.
Multi-Sensor System: Airborne Laser Scanning uses 3 different component during the measurement: laser scanner, GNSS receiver (measures position of the platform), INS (Inertial Navigation System measures a rotation of the platform).
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.
Feature: Feature is a specific representation of data. The 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 variables etc.