Airborne and terrestrial laser scanning

By J. Genderen. International Journal of Digital Earth, 2011

865 citations recorded by the source corpus.

Subfields: Environmental Engineering, Geology

View Paper: https://www.semanticscholar.org/paper/bb9941c92505a5cbb5a6edb3783cf8f4931898f7

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In Environmental Engineering

In Geology

Citations in the corpus

An improved simple morphological filter for the terrain classification of airborne LIDAR data (2013, background): “extraction of terrain from the point cloud alone (Meng et al., 2010; Shan and Toth, 2008; Vosselman and Maas, 2010).”
Comparison and Combination of Mobile and Terrestrial Laser Scanning for Natural Forest Inventories (2018, neutral): “Laser scanning (LS) systems have been used to survey forest structures for almost two decades now [1,2].”
Analyzing High Resolution Topography for Advancing the Understanding of Mass and Energy Transfer Through Landscapes: A Review (2015, background): “We refer the reader795 to Shan and Toth (2009), Vosselmann and Maas (2010), and Renslow (2012) for further reading on georeferencing.”
Automated dimensional quality assessment of precast concrete panels using terrestrial laser scanning (2014, background): “Recently, TLS has garnered much attention from the construction industry because it can easily scan a large structure and measure distances to different parts of the structurewithmillimeter-level accuracy [43,28].”
Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning (2011, background): “Optical range sensors [29-31] like pulsed (Time-of-Flight), phase-shift and triangulation-based (light sheet or pattern projection) instruments have received much attention in recent years, also from non-experts, for 3D surveying and modeling purposes.”
Review of optical-based remote sensing for plant trait mapping (2013, methodology): “Laser scanning 426 has emerged to be the most accurate RS technology for the measurement of plant and canopy 427 height (Danson et al., 2009; Lefsky, 2002; van Leeuwen and Nieuwenhuis, 2010).”
State of the art in high density image matching (2014, background): “Range or active sensors (Vosselman and Mass, 2010), such as laser scanners or structured light systems, are a common source of dense point clouds due to their ease of use, speed and ability to capture millions of points in a very short time.”