325
not only on LST but also on surface emissivity and atmospheric conditions (Li and
Becker 1993). Therefore, besides cloud detection and radiometric calibration, corrections for emissivity and atmospheric effects have to be carried out. A large number of studies have addressed these issues in the past. It is beyond the scope of this
section to summarize these studies, but an excellent review is provided by Dash
et al. (2002).
13.2.2.4 Light Detection and Ranging (LiDAR)
LiDAR is an active RS technique in which short pulses of laser light emitted from a
scanning device are distributed across a wide area and their reflections from objects
are subsequently recorded by a sensor. The distance to the objects can be calculated
from the elapsed time and the speed of light. The absolute position of the reflection
can be reconstructed using the position recorded by the Global Positioning System
(GPS) and the orientation of the sensor determined by the inertial navigation system
(INS). The result is a set of 3-D points that represents the scanned surface from
which the pulses were reflected. More detailed descriptions of LiDAR technology
can be found in Popescu (2011) and Wehr and Lohr (1999).
The primary characteristic that makes LiDAR well suited for monitoring plant
biodiversity, vegetation structure, and landscape diversity is the penetration of light
beams below the forest canopy. When a LiDAR beam hits the top of the canopy, the
beam is reflected by leaves, needles, and branches, and the reflection is recorded by
the receiver. If the energy of the beam is still high when it hits the first reflective
surface, the beam will split and can penetrate farther through openings in the canopy
until it hits additional vegetation, which can again cause reflections. This process
continues until a massive reflector, such as a tree trunk or the ground, reflects the
beam or until the signal becomes too weak. These properties of LiDAR beams allow
a detailed reconstruction of 3-D vegetation structures below the forest canopy,
which cannot be provided by passive RS techniques (Koch et al. 2014). Hence,
LiDAR RS is a valuable technique for monitoring plant diversity and vegetation
structure, and it adds a further dimension to the properties of optical RS.
LiDAR systems can be classified as discrete-return systems or full-waveform
systems, based on the capabilities of data recording. At the onset of LiDAR development, sensors were only able to record either the first or the last reflection of the
LiDAR beam, which is generally the top of trees and the terrain, respectively. As
LiDAR evolved, discrete-return systems were developed, which were able to record
a fixed number of range measurements per LiDAR beam, usually up to four to five.
The returns were based on thresholds, which were integrated into the proprietary
detection method (Thiel and Wehr 2004).
With the more recently developed full-waveform systems, the entire pathway of
the LiDAR beam through the canopy can be detected and recorded (Wagner and
Ullrich 2004). The post-processing of this data can be applied to theoretically
extract an unlimited number of echoes. Moreover, with Gaussian decomposition—
13 A Range of Earth Observation Techniques for Assessing Plant Diversity
not only on LST but also on surface emissivity and atmospheric conditions (Li and
Becker 1993). Therefore, besides cloud detection and radiometric calibration, corrections for emissivity and atmospheric effects have to be carried out. A large number of studies have addressed these issues in the past. It is beyond the scope of this
section to summarize these studies, but an excellent review is provided by Dash
et al. (2002).
13.2.2.4 Light Detection and Ranging (LiDAR)
LiDAR is an active RS technique in which short pulses of laser light emitted from a
scanning device are distributed across a wide area and their reflections from objects
are subsequently recorded by a sensor. The distance to the objects can be calculated
from the elapsed time and the speed of light. The absolute position of the reflection
can be reconstructed using the position recorded by the Global Positioning System
(GPS) and the orientation of the sensor determined by the inertial navigation system
(INS). The result is a set of 3-D points that represents the scanned surface from
which the pulses were reflected. More detailed descriptions of LiDAR technology
can be found in Popescu (2011) and Wehr and Lohr (1999).
The primary characteristic that makes LiDAR well suited for monitoring plant
biodiversity, vegetation structure, and landscape diversity is the penetration of light
beams below the forest canopy. When a LiDAR beam hits the top of the canopy, the
beam is reflected by leaves, needles, and branches, and the reflection is recorded by
the receiver. If the energy of the beam is still high when it hits the first reflective
surface, the beam will split and can penetrate farther through openings in the canopy
until it hits additional vegetation, which can again cause reflections. This process
continues until a massive reflector, such as a tree trunk or the ground, reflects the
beam or until the signal becomes too weak. These properties of LiDAR beams allow
a detailed reconstruction of 3-D vegetation structures below the forest canopy,
which cannot be provided by passive RS techniques (Koch et al. 2014). Hence,
LiDAR RS is a valuable technique for monitoring plant diversity and vegetation
structure, and it adds a further dimension to the properties of optical RS.
LiDAR systems can be classified as discrete-return systems or full-waveform
systems, based on the capabilities of data recording. At the onset of LiDAR development, sensors were only able to record either the first or the last reflection of the
LiDAR beam, which is generally the top of trees and the terrain, respectively. As
LiDAR evolved, discrete-return systems were developed, which were able to record
a fixed number of range measurements per LiDAR beam, usually up to four to five.
The returns were based on thresholds, which were integrated into the proprietary
detection method (Thiel and Wehr 2004).
With the more recently developed full-waveform systems, the entire pathway of
the LiDAR beam through the canopy can be detected and recorded (Wagner and
Ullrich 2004). The post-processing of this data can be applied to theoretically
extract an unlimited number of echoes. Moreover, with Gaussian decomposition—
13 A Range of Earth Observation Techniques for Assessing Plant Diversity