OPALS – A framework for Airborne Laser Scanning data analysis

Pfeifer, Norbert; Mandlburger, Gottfried; Otepka, Johannes; Karel, Wilfried

doi:10.1016/j.compenvurbsys.2013.11.002

Cited by 210 publications

(176 citation statements)

References 43 publications

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“…Point clouds are then further processed using OPALS (version 2.1. 5;Pfeifer et al, 2014), Point Cloud Library (PCL) (Rusu and Cousins, 2011) and in CloudCompare (version 2.7.0). 10…”

Section: Pre-processingmentioning

confidence: 99%

Terrestrial laser scanning for quantifying small-scale vertical movements of the ground surface in Artic permafrost regions

Marx

Anders

Antonova

et al. 2017

Preprint

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Abstract. Three-dimensional data acquired by terrestrial laser scanning (TLS) provides an accurate representation of Earth's surface, which is commonly used to detect and quantify topographic changes on a small scale. However, in Arctic permafrost regions the tundra vegetation and the micro-topography have significant effects on the surface representation in the captured dataset. The resulting spatial sampling of the ground is never identical between two TLS surveys. Thus, monitoring of heave and subsidence in the context of permafrost processes are challenging. This study evaluates TLS for quantifying small-scale 15 vertical movements in an area located within the continuous permafrost zone, 50 km north-east of Inuvik, Northwest Territories, Canada. We propose a novel filter strategy, which accounts for spatial sampling effects and identifies TLS points suitable for multi-temporal deformation analyses. Further important prerequisites must be met, such as accurate co-registration of the TLS datasets. We found that if the ground surface is captured by more than one TLS scan position, plausible subsidence rates (up to mm-scale) can be derived; compared to e.g. standard raster-based DEM difference maps which contain change 20 rates strongly affected by sampling effects.

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“…Point clouds are then further processed using OPALS (version 2.1. 5;Pfeifer et al, 2014), Point Cloud Library (PCL) (Rusu and Cousins, 2011) and in CloudCompare (version 2.7.0). 10…”

Section: Pre-processingmentioning

confidence: 99%

Terrestrial laser scanning for quantifying small-scale vertical movements of the ground surface in Artic permafrost regions

Marx

Anders

Antonova

et al. 2017

Preprint

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“…2) for an automated reconstruction of the roof structure requires a registered point cloud as input data. The first step in the processing is to import the point cloud using the modulebased software OPALS (Pfeifer et al, 2014). The module opalsImport converts the point cloud into an efficient data format for a fast read and write access to point attribute information.…”

Section: Overviewmentioning

confidence: 99%

Automated Reconstruction of Historic Roof Structures From Point Clouds – Development and Examples

Pöchtrager

Styhler-Aydın

Döring-Williams

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The analysis of historic roof constructions is an important task for planning the adaptive reuse of buildings or for maintenance and restoration issues. Current approaches to modeling roof constructions consist of several consecutive operations that need to be done manually or using semi-automatic routines. To increase efficiency and allow the focus to be on analysis rather than on data processing, a set of methods was developed for the fully automated analysis of the roof constructions, including integration of architectural and structural modeling. Terrestrial laser scanning permits high-detail surveying of large-scale structures within a short time. Whereas 3-D laser scan data consist of millions of single points on the object surface, we need a geometric description of structural elements in order to obtain a structural model consisting of beam axis and connections. Preliminary results showed that the developed methods work well for beams in flawless condition with a quadratic cross section and no bending. Deformations or damages such as cracks and cuts on the wooden beams can lead to incomplete representations in the model. Overall, a high degree of automation was achieved.

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“…The resulting 3D point cloud is then median filtered using the nearest neighbours of each 3D point. The filtered point cloud is then interpolated in to a DSM using the moving planes interpolation in software OPALS (Pfeifer et al, 2014).…”

Section: Triangulation and Dsmmentioning

confidence: 99%

Satellite Stereo Based Digital Surface Model Generation Using Semi Global Matching in Object and Image Space

Ghuffar

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper presents methodology and evaluation of Digital Surface Models (DSM) generated from satellite stereo imagery using Semi Global Matching (SGM) applied in image space and georeferenced voxel space. SGM is a well known algorithm, used widely for DSM generation from airborne and satellite imagery. SGM is typically applied in the image space to compute disparity map corresponding to a stereo image pair. As a different approach, SGM can be applied directly to the georeferenced voxel space similar to the approach of volumetric multi-view reconstruction techniques. The matching in voxel space simplifies the DSM generation pipeline because the stereo rectification and triangulation steps are not required. For a comparison, the complete pipeline for generation of DSM from satellite pushbroom sensors is also presented. The results on the ISPRS satellite stereo benchmark using Worldview stereo imagery of 0.5m resolution shows that the SGM applied in image space produce slightly better results than its object space counterpart. Furthermore, a qualitative analysis of the results on Worldview-3 stereo and Pleiades tri-stereo images are presented.

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OPALS – A framework for Airborne Laser Scanning data analysis

Cited by 210 publications

References 43 publications

Terrestrial laser scanning for quantifying small-scale vertical movements of the ground surface in Artic permafrost regions

Terrestrial laser scanning for quantifying small-scale vertical movements of the ground surface in Artic permafrost regions

Automated Reconstruction of Historic Roof Structures From Point Clouds – Development and Examples

Satellite Stereo Based Digital Surface Model Generation Using Semi Global Matching in Object and Image Space

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