## 3 Mapping of Land Cover and Physiological or Structural Variables
### Physiological Variables
#### 3.2.2 Canopy Height  
Canopy height or tree height is a critical parameter for quantification and modelling AGB as the biomass increases with increasing size of the tree [109; 110]. Continuous measurement of the two world's tallest tree species _Sequoia sempervirens_ and _Eucalyptus regnans_ showed that the AGB significantly correlates with age and height of the tree [111]. However, the dense structure of tropical forests impedes conventional ground-based measurements (telescoping height measuring pole, tangent methods, laser range finder, etc.) of canopy structure and the accuracy of the measurements is significantly influenced by the method being used and/or expertise of the surveyors [112]. The rapid development of remote-sensing-based technologies can overcome these difficulties by providing accurate and repeatable estimates of the canopy models in dense tropical forests. For instance, ALS can provide a three-dimensional model of the multi-layered forest structure as the laser can penetrate the upper canopy layers. A study in the tropical forest of Africa achieved an accuracy of 0.64 while estimating AGB from the canopy height metrics derived from airborne LiDAR [113]. However, the mapping accuracy was improved to 0.70 when the LiDAR-derived canopy height metrics were combined with hyperspectral data to estimate the AGB. The scarcity of the LiDAR data due to the cost and logistic arrangement is one of the major limitations for contagious mapping of AGB estimates. However, efforts have been made to integrate LiDAR derived canopy height with high-resolution optical images ('Planet Dove'satellite imagery at a 4 m spatial resolution) for country-level estimates of AGB in Peru. The study achieved the correlation of 0.70 with an RMSE (root-mean-square error) of 25.38 MgC per ha [114]. Similarly, another study derived AGB estimates by calculating mean tree canopy height using airborne LiDAR observation at a 1 ha spatial resolution and then extrapolated the results by integrating it with spatially contiguous environmental variables [34]. The accuracy of AGB estimates from ALS data is influenced by the spatial resolution (inversely proportional to the square root of plot area) and 10% error could be expected while producing LiDAR-based AGB maps at a 1 ha spatial resolution [115]. Furthermore, airborne LiDAR data have been demonstrated to increase the accuracy by \(\sim\)40% of AGB estimates from freely available medium-resolution remote sensing images [116]. Spaceborne LiDAR altimetry observation from GLAS onboard ICESat-1 [32; 105], Advanced Topographic Altimeter System (ATLAS) onboard ICESat-2 [117; 118; 119] and the GEDI onboard International Space Station (ISS) [108] are extensively being used for developing forest canopy and height parameters which are essential for AGB estimation models [23]. Recently, a forest canopy height map of 2019 at a 30 m spatial resolution is released by the UMD GLAD [120; 121]. The global forest canopy height map is derived from combined analysis of LiDAR observation acquired by the GEDI and time series of the Landsat. However, this forest canopy height map can underestimate forest canopy heights above 30 m and direct use of this product may require further investigation.