Journal ArticleDOI
Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds
G. Sithole,George Vosselman +1 more
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TLDR
In general, filters that estimate local surfaces are found to perform best and should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.Abstract:
Over the past years, several filters have been developed to extract bare-Earth points from point clouds. ISPRS Working Group III/3 conducted a test to determine the performance of these filters and the influence of point density thereon, and to identify directions for future research. Twelve selected datasets have been processed by eight participants. In this paper, the test results are presented. The paper describes the characteristics of the provided datasets and the used filter approaches. The filter performance is analysed both qualitatively and quantitatively. All filters perform well in smooth rural landscapes, but all produce errors in complex urban areas and rough terrain with vegetation. In general, filters that estimate local surfaces are found to perform best. The influence of point density could not well be determined in this experiment. Future research should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.read more
Citations
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Journal ArticleDOI
Aplicación de tecnología LIDAR en El Shincal de Quimivil, Londres, Catamarca
TL;DR: Moralejo, Reinaldo Andres as mentioned in this paper, presented the Consejo Nacional de Investigaciones Cientificas y Tecnicas (CNCI-TEC).
Journal ArticleDOI
Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling
TL;DR: In this article, the conditional random field (CRF) is used for point cloud contextual classification, which is based on probabilistic graphical models, an alternative representation of a conditional probability distribution over random variables.
Journal ArticleDOI
Digital elevation modeling through forests: the challenge of the Amazon
TL;DR: In this article , the authors address three research questions: To what extent can a terrain model be replaced by a more easily available canopy-level surface model for topography-based applications? How can the elevation be obtained at ground level through forest? Can a priori knowledge of general continental relief properties be used to compensate for the limits of measurement methods in the presence of forest?
Journal ArticleDOI
Assessment of automatic segmentation accuracy with various point cloud density
TL;DR: Effect on the performance, the accuracy of various segmentation methods and the geometric accuracy of the obtained models at density changes taking into account the processing time are evaluated.
Journal ArticleDOI
Comparison of the filtering models for airborne LiDAR data by three classifiers with exploration on model transfer
Hongchao Ma,Zhan Cai,Liang Zhang +2 more
TL;DR: Reliable results were achieved, especially in rural area (overall accuracy achieved 95.64%), indicating the feasibility of model transfer in the context of point cloud filtering for both easy automation and acceptable accuracy.
References
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Journal ArticleDOI
Determination of terrain models in wooded areas with airborne laser scanner data
K. Kraus,Norbert Pfeifer +1 more
TL;DR: In this article, the characteristics of laser scanning are compared to photogrammetry with reference to a big pilot project and the results are in accordance with the expectations, however, the geomorphologic quality of the contours, computed from a terrain model derived from laser scanning, needs to be improved.
Journal ArticleDOI
Processing of laser scanner data-algorithms and applications
TL;DR: This paper presents some methods and algorithms concerning filtering for determining the ground surface, DEM, classification of buildings for 3D City Models and the detection of electrical power lines.
Slope based filtering of laser altimetry data
TL;DR: In this article, a new method is proposed for filtering laser data, which is closely related to the erosion operator used for mathematical grey scale morphology, based on height differences in a representative training dataset, filter functions are derived that either preserve important terrain characteristics or minimise the number of classification errors.