## 3 Considering the ALS Workflow and Its Impact on the Efficacy of Data Products
### Planning and Data Collection
#### 3.1.1 Flight Planning and System Configuration
For this experiment two beam divergence values were used: 0.8 milliradians (mrad) and 0.25 mrad; the shot densities for the datasets are 3.04 and 3.07 shots/m\({}^{2}\) respectively. DSMs with a raster resolution of 0.5 m were generated from the test data. Figure 11a,b shows shaded relief images produced from the DSM with the first returns overlaid on them. Figure 11c,d shows zoomed-in views of a small common section. The ALS returns and the return footprints are represented for both the 0.8 mrad and 0.25 mrad cases. The unique (non-overlapped) illuminated surface fraction is approximately 7% for the narrower 0.25 mrad beam divergence and 49% for the 0.8 mrad divergence. To further illustrate the importance of considering the percentage of the surface illumination and not just the shot density metric, Figure 12 shows the results of an experiment aimed at studying the probability of detecting small features using different laser beam divergences (footprint size). Figure 12: Relationship between laser beam footprint/surface illumination and target detection probability. **(a)** Reference high resolution (0.25 m DSM), red numbers indicate the number of columns that were identified and used for the test; **(b)** 0.5 m DSM from ALS data collected with 0.8 mrad divergence; **(c)** 0.5 m DSM from ALS data collected with 0.25 mrad divergence. The reference dataset is a 0.25 m DSM that was produced from a point cloud that had a shot density of 41.18 shots/m\({}^{2}\) collected with a beam divergence of 0.25 milliradians (mrad). The test datasets are two 0.5 m DSMs generated from single pass data collected using beam divergences of 0.8 mrad and 0.25 mrad, the shot densities (and percentage of surface illuminated) for the datasets are 3.04 (49%) and 3.07 (7%) shots/m\({}^{2}\) respectively. The test consisted of counting the narrow circular columns that are visible on each of the DSMs and comparing that number to the number derived from the higher resolution and shot density reference DSM. As can be seen in Figure 12, the DSM generated from the data collected with the 0.8 divergence has more visible column features than in the DSM generated from the data collected with the narrower 0.25 mrad beam divergence, despite the latter having a slightly higher shot density. A systematic count found that in the DSM from the 0.8 mrad dataset, 83 features can be identified while in the DSM from the 0.25 mrad dataset only 74 from a total of 117 can be identified on the reference DSM; yielding detection probabilities of 70.9% and 63.2% respectively. This example demonstrates that illuminating a larger portion of the surface increases the probability of detecting smaller features. Larger footprints also generally result in more uniform return intensity values. However, the benefit of using a larger footprint comes at the price of increasing the vertical and horizontal uncertainty (reduced accuracy) of the data. For a larger footprint area there is a higher uncertainty about where within the footprint the target that produced the return is located. Also, if there are several targets within the footprint or the terrain is sloped the resultant elevation of the return will be an averaged elevation (mixed signal) of all the targets within the footprint, which reduces the vertical accuracy of the return. This disadvantage is also evident in Figure 12.  
Another consideration for flight planning is to ensure that there will be no coverage gaps between flight strips. To achieve this it is necessary to laterally overlap adjacent flight swaths. This \"sidelap\" can, in principle, be as small as 10%. However, to achieve a more uniform distribution of laser shots a side overlap of 50% is recommended, meaning that the edge of each swath falls over the center of the adjacent swath. This 50% overlap also ensures that the target surface is illuminated from two different angles, which has proved to be beneficial in achieving optimal canopy penetration.