329
for the assessment of forest fuels and their vertical distribution, which are important
input variables in forest fire models used in fire management.
In summary, LiDAR RS is a powerful tool for monitoring vegetation structure
and plant diversity. It delivers detailed and accurate information about forest properties down to the scale of the individual tree and is therefore regarded as the gold
standard for determining vegetation structure. Nowadays, LiDAR is widely applied
in RS research as a reference to test the accuracy of other methods and is used in
practical forest management in the boreal zone of Scandinavia (Næsset 2007). The
development of new sensors will lead to multi- or hyperspectral LiDAR technology,
which will combine the advantages of today’s LiDAR and optical sensors. These
systems will be able to collect accurate 3-D information and calibrated spectral
information without facing the problems of varying illumination in the tree crowns.
Furthermore, the resolution of the data will increase, thereby enabling parameter
extraction at the branch level.
13.2.2.5 Radar
Several reviews have been conducted on radar alone or radar and optical sensors for
vegetation applications relevant to habitat and biodiversity. They typically include
classification of vegetation or land cover types, biophysical modeling of parameters
such as biomass or tree height, and ecosystem disturbance detection and mapping
(e.g., Balzter 2001; Treuhaft et al. 2004; Lu 2006, which includes summaries of four
previous reviews; Lutz et al. 2008; Bergen et al. 2009; Lowry et al. 2009; Koch
2010; Nagendra et al. 2013; Tiner et al. 2014; White et al. 2015; Timothy et al.
2016; Baltzer 2017).
Systems and Techniques
Active radar is the focus of this section because the resolution of passive sensors is
generally too coarse for all but large extent studies. In active radar, transmitted
pulses interact with scattering elements of the surface in terms of their dielectric
properties, size, and arrangement. In vegetation, moisture (increasing dielectric
constant) and more complex stem-branch-leaf arrangements result in increased
backscatter intensity. Much research has been conducted using physically based
models to characterize and understand backscatter effects in vegetated canopies
(e.g., Sun and Ranson 1995; Ningthoujam et al. 2016). Spatial and temporal variations in these properties associated with different vegetation types, age distribution,
health, and management provide information or indicators of potential habitat and
biodiversity. Radar data are available at different frequencies/wavelengths; X-, C-,
and L-bands (2.5–3.75 cm, 3.75–7.5 cm, and 15–30 cm wavelengths, respectively)
are the most common on satellite platforms. S-band (7.5–15 cm) has been deployed
on a couple of satellites, and new S- and P-band (30–100 cm) satellite sensors are
planned for the near future (e.g., NISAR L- and S-bands; NovaSAR S-band;
13 A Range of Earth Observation Techniques for Assessing Plant Diversity
for the assessment of forest fuels and their vertical distribution, which are important
input variables in forest fire models used in fire management.
In summary, LiDAR RS is a powerful tool for monitoring vegetation structure
and plant diversity. It delivers detailed and accurate information about forest properties down to the scale of the individual tree and is therefore regarded as the gold
standard for determining vegetation structure. Nowadays, LiDAR is widely applied
in RS research as a reference to test the accuracy of other methods and is used in
practical forest management in the boreal zone of Scandinavia (Næsset 2007). The
development of new sensors will lead to multi- or hyperspectral LiDAR technology,
which will combine the advantages of today’s LiDAR and optical sensors. These
systems will be able to collect accurate 3-D information and calibrated spectral
information without facing the problems of varying illumination in the tree crowns.
Furthermore, the resolution of the data will increase, thereby enabling parameter
extraction at the branch level.
13.2.2.5 Radar
Several reviews have been conducted on radar alone or radar and optical sensors for
vegetation applications relevant to habitat and biodiversity. They typically include
classification of vegetation or land cover types, biophysical modeling of parameters
such as biomass or tree height, and ecosystem disturbance detection and mapping
(e.g., Balzter 2001; Treuhaft et al. 2004; Lu 2006, which includes summaries of four
previous reviews; Lutz et al. 2008; Bergen et al. 2009; Lowry et al. 2009; Koch
2010; Nagendra et al. 2013; Tiner et al. 2014; White et al. 2015; Timothy et al.
2016; Baltzer 2017).
Systems and Techniques
Active radar is the focus of this section because the resolution of passive sensors is
generally too coarse for all but large extent studies. In active radar, transmitted
pulses interact with scattering elements of the surface in terms of their dielectric
properties, size, and arrangement. In vegetation, moisture (increasing dielectric
constant) and more complex stem-branch-leaf arrangements result in increased
backscatter intensity. Much research has been conducted using physically based
models to characterize and understand backscatter effects in vegetated canopies
(e.g., Sun and Ranson 1995; Ningthoujam et al. 2016). Spatial and temporal variations in these properties associated with different vegetation types, age distribution,
health, and management provide information or indicators of potential habitat and
biodiversity. Radar data are available at different frequencies/wavelengths; X-, C-,
and L-bands (2.5–3.75 cm, 3.75–7.5 cm, and 15–30 cm wavelengths, respectively)
are the most common on satellite platforms. S-band (7.5–15 cm) has been deployed
on a couple of satellites, and new S- and P-band (30–100 cm) satellite sensors are
planned for the near future (e.g., NISAR L- and S-bands; NovaSAR S-band;
13 A Range of Earth Observation Techniques for Assessing Plant Diversity