Assessment of landslide age, landslide persistence and human impact using airborne laser scanning digital terrain models

2012 ◽  
Vol 94 (1) ◽  
pp. 135-156 ◽  
Author(s):  
Rainer Bell ◽  
Helene Petschko ◽  
Matthias Röhrs ◽  
Andreas Dix
2005 ◽  
Vol 5 ◽  
pp. 57-63 ◽  
Author(s):  
M. Hollaus ◽  
W. Wagner ◽  
K. Kraus

Abstract. Digital terrain models form the basis for distributed hydrologic models as well as for two-dimensional hydraulic river flood models. The technique used for generating high accuracy digital terrain models has shifted from stereoscopic aerial-photography to airborne laser scanning during the last years. Since the disastrous floods 2002 in Austria, large airborne laser-scanning flight campaigns have been carried out for several river basins. Additionally to the topographic information, laser scanner data offer also the possibility to estimate object heights (vegetation, buildings). Detailed land cover maps can be derived in conjunction with the complementary information provided by high-resolution colour-infrared orthophotos. As already shown in several studies, the potential of airborne laser scanning to provide data for hydrologic/hydraulic applications is high. These studies were mostly constraint to small test sites. To overcome this spatial limitation, the current paper summarises the experiences to process airborne laser scanner data for large mountainous regions, thereby demonstrating the applicability of this technique in real-world hydrological applications.


2013 ◽  
Vol 40 (12) ◽  
pp. 4688-4700 ◽  
Author(s):  
Ole Risbøl ◽  
Ole Martin Bollandsås ◽  
Anneli Nesbakken ◽  
Hans Ole Ørka ◽  
Erik Næsset ◽  
...  

2018 ◽  
Vol 7 (9) ◽  
pp. 342 ◽  
Author(s):  
Adam Salach ◽  
Krzysztof Bakuła ◽  
Magdalena Pilarska ◽  
Wojciech Ostrowski ◽  
Konrad Górski ◽  
...  

In this paper, the results of an experiment about the vertical accuracy of generated digital terrain models were assessed. The created models were based on two techniques: LiDAR and photogrammetry. The data were acquired using an ultralight laser scanner, which was dedicated to Unmanned Aerial Vehicle (UAV) platforms that provide very dense point clouds (180 points per square meter), and an RGB digital camera that collects data at very high resolution (a ground sampling distance of 2 cm). The vertical error of the digital terrain models (DTMs) was evaluated based on the surveying data measured in the field and compared to airborne laser scanning collected with a manned plane. The data were acquired in summer during a corridor flight mission over levees and their surroundings, where various types of land cover were observed. The experiment results showed unequivocally, that the terrain models obtained using LiDAR technology were more accurate. An attempt to assess the accuracy and possibilities of penetration of the point cloud from the image-based approach, whilst referring to various types of land cover, was conducted based on Real Time Kinematic Global Navigation Satellite System (GNSS-RTK) measurements and was compared to archival airborne laser scanning data. The vertical accuracy of DTM was evaluated for uncovered and vegetation areas separately, providing information about the influence of the vegetation height on the results of the bare ground extraction and DTM generation. In uncovered and low vegetation areas (0–20 cm), the vertical accuracies of digital terrain models generated from different data sources were quite similar: for the UAV Laser Scanning (ULS) data, the RMSE was 0.11 m, and for the image-based data collected using the UAV platform, it was 0.14 m, whereas for medium vegetation (higher than 60 cm), the RMSE from these two data sources were 0.11 m and 0.36 m, respectively. A decrease in the accuracy of 0.10 m, for every 20 cm of vegetation height, was observed for photogrammetric data; and such a dependency was not noticed in the case of models created from the ULS data.


2020 ◽  
Vol 9 (4) ◽  
pp. 224
Author(s):  
Mihnea Cățeanu ◽  
Arcadie Ciubotaru

A digital model of the ground surface has many potential applications in forestry. Nowadays, Light Detection and Ranging (LiDAR) is one of the main sources for collecting morphological data. Point clouds obtained via laser scanning are used for modelling the ground surface by interpolation, a process which is affected by various errors. Using LiDAR data to collect ground surface data for forestry applications is a challenging scenario because the presence of forest vegetation will hinder the ability of laser pulses to reach the ground. The density of ground observations will be therefore reduced and not homogenous (as it is affected by the variations in canopy density). Furthermore, forest areas are generally present in mountainous areas, in which case the interpolation of the ground surface is more challenging. In this paper, we present a comparative analysis of interpolation accuracy for nine algorithms, which are used for generating Digital Terrain Models from Airborne Laser Scanning (ALS) data, in mountainous terrain covered by dense forest vegetation. For most of the algorithms we find a similar performance in terms of general accuracy, with RMSE values between 0.11 and 0.28 m (when model resolution is set to 0.5 m). Five of the algorithms (Natural Neighbour, Delauney Triangulation, Multilevel B-Spline, Thin-Plate Spline and Thin-Plate Spline by TIN) have vertical errors of less than 0.20 m for over 90 percent of validation points. Meanwhile, for most algorithms, major vertical errors (of over 1 m) are associated with less than 0.05 percent of validation points. Digital Terrain Model (DTM) resolution, ground slope and point cloud density influence the quality of the ground surface model, while for canopy density we find a less significant link with the quality of the interpolated DTMs.


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