Evaluation of digital terrain models generated in forest conditions from airborne laser scanning data acquired in two seasons

2011 ◽  
Vol 26 (4) ◽  
pp. 374-384 ◽  
Author(s):  
Krzysztof Stereńczak ◽  
Jacek Kozak
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Digital Terrain Models ◽  
Digital Terrain ◽  
Terrain Models ◽  
Airborne Laser ◽  
Forest Conditions

scholarly journals Airborne laser scanning and usefulness for hydrological models

2005 ◽  
Vol 5 ◽  
pp. 57-63 ◽  
Author(s):  
M. Hollaus ◽  
W. Wagner ◽  
K. Kraus
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Airborne Laser Scanning ◽  
Scanner Data ◽  
Digital Terrain Models ◽  
Mountainous Regions ◽  
Digital Terrain ◽  
Terrain Models ◽  
Airborne Laser ◽  
Land Cover Maps

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.

Interpreting cultural remains in airborne laser scanning generated digital terrain models: effects of size and shape on detection success rates

2013 ◽  
Vol 40 (12) ◽  
pp. 4688-4700 ◽  
Author(s):  
Ole Risbøl ◽  
Ole Martin Bollandsås ◽  
Anneli Nesbakken ◽  
Hans Ole Ørka ◽  
Erik Næsset ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Success Rates ◽  
Digital Terrain Models ◽  
Size And Shape ◽  
Digital Terrain ◽  
Terrain Models ◽  
Airborne Laser

scholarly journals Accuracy Assessment of Point Clouds from LiDAR and Dense Image Matching Acquired Using the UAV Platform for DTM Creation

2018 ◽  
Vol 7 (9) ◽  
pp. 342 ◽  
Author(s):  
Adam Salach ◽  
Krzysztof Bakuła ◽  
Magdalena Pilarska ◽  
Wojciech Ostrowski ◽  
Konrad Górski ◽  
...  
Keyword(s):  
Land Cover ◽  
Laser Scanning ◽  
Point Clouds ◽  
Data Sources ◽  
Digital Terrain Models ◽  
Vegetation Height ◽  
Digital Terrain ◽  
Terrain Models ◽  
Airborne Laser ◽  
Vertical Accuracy

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.

Large-scale prediction of aboveground biomass in heterogeneous mountain forests by means of airborne laser scanning

2016 ◽  
Vol 46 (9) ◽  
pp. 1138-1144 ◽  
Author(s):  
M. Maltamo ◽  
O.M. Bollandsås ◽  
T. Gobakken ◽  
E. Næsset
Keyword(s):  
Aboveground Biomass ◽  
Laser Scanning ◽  
Large Scale ◽  
Airborne Laser Scanning ◽  
Mountain Forests ◽  
Airborne Laser ◽  
Model Predictions ◽  
Growing Conditions ◽  
Southern Norway ◽  
Forest Conditions

This study considered airborne laser scanning (ALS) based aboveground biomass (AGB) prediction in mountain forests. The study area consisted of a long transect from southern Norway to northern parts of the country with wide ranges of elevation along a long latitudinal gradient (58°N–69°N). This transect was covered by ALS data and field data from 238 plots. AGB was modeled using different types of predictor variables, namely ALS metrics, variables related to growing conditions (elevation, latitude, and climatic variables), and tree species information. Modelling of AGB in the long transect covering diverse mountainous forest conditions was challenging: the RMSE values were rather large (37%–70%). The effects of growing conditions on model predictions were minor. However, species information was essential to improve accuracy. The analysis revealed that when doing inventories of spruce-dominated areas, all plots should be pooled together when the models are developed, whereas if pine or deciduous species dominate the area in question, separate dominant species-wise models should be constructed.

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