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
More filters
Journal ArticleDOI
Digital Deforestation: Comparing Automated Approaches to the Production of Digital Terrain Models (DTMs) in Agisoft Metashape
TL;DR: In this paper , the suitability of automated point cloud classification tools provided by the popular image-based modeling (IBM) software package Agisoft Metashape for the generation of digital terrain models (DTMs) at moderately-vegetated archaeological sites was tested.
Object-oriented residential building land-use mapping using lidar and aerial photographs
TL;DR: In this article, the authors presented an approach to detect and separate residential land uses on a building scale directly from remotely sensed imagery to enhance urban land-use analysis, where they applied a multi-directional ground filter to generate a bare ground surface from lidar data, then utilizes a morphology-based building detection algorithm to identify buildings from both lidar and aerial photographs, and finally separates residential buildings using a supervised C4.5 decision tree analysis based on seven selected building land use indicators.
Book ChapterDOI
Chapter 5 – Errors and Accuracy
TL;DR: In this article, the root mean square error of a function of measured variables is used to estimate the accuracy of digital terrain models of local morphometric attributes, which can be used to detect and analyze errors in DTM-based geological studies.
Proceedings ArticleDOI
Feature extraction with LIDAR data and aerial images
TL;DR: A hierarchy method for feature extraction with LIDAR data and aerial images is discussed and it was possible to detect more object information and get a better result of feature extraction than using automatic filters alone.
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.