Airborne LiDAR for DEM generation: some critical issues

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An improved simple morphological filter for the terrain classification of airborne LIDAR data (2013, background): “, Liu, 2008; Sithole and Vosselman, 2004). Meng et al. (2010) helpfully and systematically identify key dimensions (or attributes) on which algorithms typically differ, including whether they use the first, last, or full LIDAR return set, and whether the raw LIDAR data are used to interpolate a surf”
An illustrated introduction to general geomorphometry (2017, background): “(3) High- and super high-resolution DEMs have become widely available (Tarolli, 2014) owing to advances in LiDAR technology (Liu, 2008), real-time kinematic global navigation satellite system (GNSS) surveys (Awange, 2012: ch 8), areal surveys based on unmanned aerial vehicles (UAVs) (Colomina and Mo”
An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation (2016, background): “Nonetheless, their results suggested that slope-based algorithms were not guaranteed to function well in complex terrain, as the filtering accuracy decreased with increasingly steeper slopes [8].”
Modeling Soil Processes: Review, Key Challenges, and New Perspectives (2016, background): “However, the acquisition of DEMs, typically by Light Detection and Ranging (LIDAR, Liu, 2008), Synthetic Aperture Radar (SAR, e.g., Gruber et al., 2012), or stereoscopic optical imagery (Fujisada et al., 2005) is not straightforward because raw data can contain return signals from human-made…”