## 2 Advanced Instruments in Remote Sensing of EBC
### Lidar  
Light Detection and Ranging (LIDAR), also called Laser altimetry, is an active remote sensing technology that utilizes a laser to illuminate a target object and a photodiode to register the backscatter radiation [47, 48]. The current LIDAR remote sensing can be categorized into two general groups:  
\begin{table}
\begin{tabular}{l l l l l} \hline
**Designation** & **Type** & **Imager** & **Launch** & **Waveband** \\ \hline Alsat-1 & DMC & 32m MS & 2002 & \(\checkmark\) MS \\ UK-DMC & DMC & 32m MS & 2003 & NIR: 0.77–0.90 \(\upmu\)m \\ Nigeriaat-1 & DMC & 32m MS & 2003 & Red: 0.63–0.69 \(\upmu\)m \\ Beijing-1 & DMC+4 & 32m MS/4m Pan & 2005 & Green:0.52–0.60 \(\upmu\)m \\ Deimos-1 & DMC & 22m MS & 2008 & Pan \\ UK-DMC2 & DMC & 22m MS & 2008 & 0.50–0.80 \(\upmu\)m \\ \hline \end{tabular}
\end{table}
Table 2: Disaster Monitoring Constellation (DMC) on Orbit (adapted from DMC International Imaging Ltd.).  
non-scanning LIDARs, and scanning LIDARs. The non-scanning LIDARs record pulsed ranging that measures the travel time between the transmitted and received signal backscattered from the object surface, and the scanning LIDARs register continuous wave ranging that is produced in a transmitted sinusoidal signal and carried out by modulating the laser light intensity [49]. According to the characteristics of LIDAR technology, it has been proven to provide horizontal and vertical information at high spatial resolutions and vertical accuracies [47]. For example, [PERSON] stated that 5-30 cm range is the typical accuracies for LIDAR-derived vertical information [50]. Airborne LIDAR remote sensing systems such as LVIS (Laser Vegetation Imaging Sensor) have been used for bathymetry, forestry, and other applications [48, 51, 52]. For instance, [PERSON] _et al._ briefly discussed the airborne LIDAR remote sensing for biodiversity science and conservation [3]; [PERSON] _et al._ reviewed the application within forest structure (vertical information) [47], e.g., canopy and tree height, biomass, and volume; [PERSON] _et al._ claimed species distribution models have been improved through airborne LIDAR quantifying vegetation structure within a landscape [53]. LIDAR was underlined by [11] as one of the strong interests of the remote sensing community in ecology. Besides airborne LIDAR with the limitations of large data volumes, footprint size and high costs [54], spaceborne LIDAR has come through with the launch of the ICESat/GLAS (Ice, Cloud, and Land Elevation Satellite/Geoscience Laser Altimeter System), which is the first laser-ranging instrument for continuous global observations. The applications of the GLAS data in EBC, which are seldom reviewed, will be discussed below.  
LIDAR focused on the forest vertical structure, especially forest canopy height and aboveground biomass estimation. [PERSON] _et al._ estimated forest canopy height with an RMSE of 5 m (83% of variance explained) in varied forest types including evergreen needle leaf, deciduous broadleaf and mixed stands in temperate North America, and tropical evergreen broadleaf forests in Brazil [55]. Mangrove forests are considered as one of the most biodiverse and productive wetlands on Earth, and the mangrove height and aboveground biomass were measured and mapped based on SRTM (Shuttle Radar Topography Mission) elevation data, GLAS waveforms and field data [56]. [PERSON] _et al._ compared GLAS height and biomass estimates with reference data from the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service at a regional scale, and promising results were obtained [57]. [PERSON] _et al._ proposed the combination of Landsat time series and the GLAS to estimate the biomass accumulation of the Amazonian secondary forest, and the estimation agreed well with ground-based studies [58]. [PERSON] _et al._ tested simulated GLAS data under tough conditions, e.g., areas with dense forests, high relief, or heterogeneous vegetation cover, and demonstrated the capability of GLAS waveforms as supplemental model input to improve estimates of canopy height [54].