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
Unsupervised Building Instance Segmentation of Airborne LiDAR Point Clouds for Parallel Reconstruction Analysis
TL;DR: Zhang et al. as mentioned in this paper proposed a novel unsupervised building instance segmentation (UBIS) method of airborne Light Detection and Ranging (LiDAR) point clouds for parallel reconstruction analysis, which combines a clustering algorithm and a novel model consistency evaluation method.
Journal ArticleDOI
Original paper: A post-processing step error correction algorithm for overlapping LiDAR strips from agricultural landscapes
Jeffrey L. Willers,Mingzhou Jin,Burak Eksioglu,Andy Zusmanis,Charles G. O'Hara,Johnie N. Jenkins +5 more
TL;DR: In this article, a post-processing, quadratic optimization model was formulated to reduce step artifacts in the processing of light detection and ranging (LiDAR) data, which is an abrupt change in estimates of elevation between adjacent strips and must be reduced before building a digital surface model of elevation.
Automated Building Information Extraction and Evaluation from High-resolution Remotely Sensed Data
TL;DR: This paper aims to provide a chronology of the events that led to and culminated in the publication of this book in the form of a single, coherent chapter.
Journal ArticleDOI
DEM Retrieval From Airborne LiDAR Point Clouds in Mountain Areas via Deep Neural Networks
Yimin Luo,Hongchao Ma,Liguo Zhou +2 more
TL;DR: A new DEM retrieval method from airborne LiDAR point clouds in mountain areas based on deep neural networks (DNNs) is proposed, which becomes much easier by inputting their DSM into this model for prediction.
Proceedings ArticleDOI
Dynamic triangle — Based method for 3D building rooftop reconstruction from LiDAR data
TL;DR: The experimental results illustrate that the proposed framework can derive the reliable and accurate 3D building rooftops.
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.