## 3 Considering the ALS Workflow and Its Impact on the Efficacy of Data Products
### Data Processing
#### 3.2.5 Surface Model Generation  
From the classified point cloud tiles surface models can be generated. The simplest surface model type that can be generated is the Triangulated Irregular Network or TIN. A TIN is generated by creating a network of triangular planar facets that join the three closest points in such a way that the area of all triangulated facets is minimized. The TIN is as dense as the point cloud that is used to generate it and it is also an irregularly spaced dataset. Some people prefer to work with TINs because they are composed of the actual observed data points rather than interpolated values. However, for ease of manipulation, visualization and analysis regularly spaced dataset or elevation rasters can be created. As illustrated with Figure 20 these elevation rasters are created by interpolating the elevation values from the irregularly spaced point clouds to a single elevation value for each raster element, with the raster element equally spaced in the X,Y horizontal plane. Such surface models are considered to be only 2.5-dimensional as they only represent one elevation value per raster element, and contain less information than the original point cloud. Whereas a point cloud might have tens of elevations points per square meter a surface model might only represent one or four elevations per square meter. Elevation rasters may represent different surfaces. For example, if a raster is created wholly from classified ground points the elevation raster represents the bare-Earth surface and the model is called a digital elevation model or DEM (DTM in the European usage [18]). If the elevation raster is made from the first returns it represents the first intercepted surface and it is usually called a Digital Surface Model or DSM. Other rasters might be created from the point cloud, they might represent spatial information such as the variance or standard deviation of the elevation (elevation roughness) of all returns in each raster element; or just a count of the number of returns obtained in each raster element. A modern approach, but not yet common, is creating a 3-dimensional array of 3D elements called voxels (volume elements) [55]. These voxel arrays can store several elevation values for each cell in the X,Y plane, an advantage over the single value stored by traditional elevation rasters. There are many 3D interpolation algorithms that can be used to generate surface models, whether they are considered DSMs or DEMs. Among the most common are: triangulation with linear interpolation (TLI), inverse distance weighting (IDW), kriging, minimum curvature, modified Shepard's method, moving average, natural neighbor, nearest neighbor and, polynomial regression. Each one of these methods will produce slightly different models and slightly different representations of reality based on the available information [56,57]. Thus it is important to know the differences between the methods and the results they produce, and when a given method might be better than another to answer a particular research question. Table 3 summarizes some of the characteristics of the main interpolation methods in terms of whether the method is an exact or smooth interpolator, the weighting mechanism that is used to ponder the available observations and the ability to extrapolate the surface model beyond the extent of the existing data [58]. To illustrate the difference Figure 21 present DEMs of a section of the Honduran Mosquitia produced from the same ground points but using different interpolation methods. The simplest method is the triangulation with linear interpolation, which basically extends the concept of a triangulated