## 3 Considering the ALS Workflow and Its Impact on the Efficacy of Data Products
### Planning and Data Collection
#### 3.1.2 Maximizing Canopy Penetration  
Of all the capabilities of ALS systems, the ability to detect and record ground returns from underneath thick vegetation canopies is probably the most important for archaeological prospection. It has to be emphasized that ALS cannot see through vegetation in the way X-rays see through flesh, but rather the LASER energy must propagate through gaps in the vegetation, hit the ground and return to the sensor. In a previous work [38] researchers studied the effect of forest vegetation type on the probability of LiDAR reaching the forest floor to detect archeological features. However, they did not investigate the effect that different system configurations and flying parameters might have on that probability. NCALM experience and experimentation with archaeological projects in the thick jungles of Mesoamerica (Mexico, Belize and Honduras) indicates that customizing flight plans and sensor configurations are fundamental to achieving maximal canopy penetration. In the jungle sometimes less is more, using a lower PRF may produce a lower shot density but the resulting higher energy per pulse may actually produce more ground returns. Special attention is required in selecting flying heights,scan angles, PRF and beam divergence (See Table 2). While Mesoamerica might be assumed to be a monolithically uniform ecosystem, the biophysical characteristics of its forests (canopy height, thickness, density, gap fraction, leaf area index, _etc._) vary widely across the region. This wide variation is illustrated in Figure 13 which presents histograms of the number of ALS returns obtained from the forest canopies at different heights above the ground. Because of this wide variation we are confident that even if the specific results presented below are not directly applicable to other forest environments (conifer, alpine, Mediterranean, _etc._) the methodology can still be utilized. In general, to achieve optimal canopy penetration several conditions need to be met: (a) the entire surface area needs to be illuminated (ideally more than once from different angles) so that laser pulses are placed in canopy gaps; (b) laser pulses need to have enough energy to make the round trip through the canopy (LiDAR equation); and (c) for discrete LiDAR systems the slant range through the lowest understory vegetation needs to be greater than the width of the laser pulse so that the system range resolution and detector dead time are not detrimental factors for the detection of ground returns [39]. From experience we have learned that most of the ground returns come from shots fired close to nadir and that there is significant drop-off for scan angles greater than \(\pm\)20\({}^{\circ}\). For this reason we conclude that ALS systems equipped with Palmer scanners, which distribute the LASER shots at a scanning angle of 15 to 20\({}^{\circ}\) off nadir, are probably not well suited for mapping of landscapes covered by heavy vegetation. Taking into consideration the scan angle limitation we performed several canopy penetration experiments during archaeological prospection projects, and the results are summarized in Table 2. While these results are sensor specific and different sensors will produce different results based on their own engineering specifications, this type of analysis should be performed for each project to ensure optimized canopy penetration producing maximum ground returns. In Table 2 the sites are sorted based on the thickness of the canopy cover from thinnest at the top to densest (bottom). For these tests the same flight line was flown using different PRFs and beam  
Figure 13: Canopy histograms that represent the detection of canopy returns at different elevation above the ground level of a 250 m \(\times\) 250 m sample of different Mesoamerican forests. (**a**) La Mosquitia, Honduras; (**b**) Caracol, Central Belize; (**c**) Yaxnohcah, Campeche, Mexico; (**d**) Cansahcab, Campeche, Mexico. divergences.