Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds
01 Aug 2004-Isprs Journal of Photogrammetry and Remote Sensing (Elsevier)-Vol. 59, Iss: 1, pp 85-101
TL;DR: 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.
Citations
More filters
TL;DR: In this article, the authors use a technique referred to as Gaussian decomposition for processing and calibrating data acquired with a novel small-footprint airborne laser scanner that digitises the complete waveform of the laser pulses scattered back from the Earth's surface.
Abstract: In this study we use a technique referred to as Gaussian decomposition for processing and calibrating data acquired with a novel small-footprint airborne laser scanner that digitises the complete waveform of the laser pulses scattered back from the Earth's surface. This paper presents the theoretical basis for modelling the waveform as a series of Gaussian pulses. In this way the range, amplitude, and width are provided for each pulse. Using external reference targets it is also possible to calibrate the data. The calibration equation takes into account the range, the amplitude, and pulse width and provides estimates of the backscatter cross-section of each target. The applicability of this technique is demonstrated based on RIEGL LMS-Q560 data acquired over the city of Vienna.
715 citations
TL;DR: This paper presents a new filtering method which only needs a few easy-to-set integer and Boolean parameters and may help the users without much experience to use LiDAR data and related technology in their own applications more easily.
Abstract: Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs) from airborne LiDAR (light detection and ranging) data. However, most filtering algorithms need to carefully set up a number of complicated parameters to achieve high accuracy. In this paper, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. Within the proposed approach, a LiDAR point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface. Finally, the ground points can be extracted from the LiDAR point cloud by comparing the original LiDAR points and the generated surface. Benchmark datasets provided by ISPRS (International Society for Photogrammetry and Remote Sensing) working Group III/3 are used to validate the proposed filtering method, and the experimental results yield an average total error of 4.58%, which is comparable with most of the state-of-the-art filtering algorithms. The proposed easy-to-use filtering method may help the users without much experience to use LiDAR data and related technology in their own applications more easily.
653 citations
Cites methods from "Experimental comparison of filter a..."
...This method was first tested by datasets that were provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) Working Group III/3 to quantitatively test the performance of different filters and identify directions for future research [30]....
[...]
TL;DR: In this article, the methods of small-footprint airborne laser scanning for extracting forest inventory data, mainly in the boreal forest zone, are reviewed and some recommendations for future research are given to foster the methodology development.
Abstract: Experiences from Nordic countries and Canada have shown that the retrieval of the stem volume and mean tree height of a tree or at stand level from laser scanner data performs as well as, or better than, photogrammetric methods, and better than other remote sensing methods. This paper reviews the methods of small-footprint airborne laser scanning for extracting forest inventory data, mainly in the boreal forest zone. The methods are divided into the following categories: extraction of terrain and canopy height model; feature extraction approaches (canopy height distribution and individual-tree-based techniques, techniques based on the synergetic use of aerial images and lidar, and other new approaches); tree species classification and forest growth using laser scanner; and the use of intensity and waveform data in forest information extraction. Despite this, the focus is on methods, some review of quality obtained, especially in the boreal forest area, is included. Several recommendations for future research are given to foster the methodology development.
573 citations
Cites methods from "Experimental comparison of filter a..."
...The comparison of the filtering techniques used for DTM extraction can be found in a report on the International Society for Photogrammetry and Remote Sensing (ISPRS) comparison of filters (Sithole and Vosselman 2004)....
[...]
...…in addition to errors caused by the laser system and errors caused by the applied methodology and algorithms (for an algorithm comparison see Sithole and Vosselman (2004)), the quality of a DTM derived from laser scanning is influenced by data characteristics (e.g. point density, first/last…...
[...]
TL;DR: This paper reviews the recent advances of airborne LiDAR systems and the use ofLiDAR data for DEM generation, with special focus on LiD AR data filters, interpolation methods, DEM resolution, and LiDar data reduction.
Abstract: Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of
LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for
DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage
and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity
characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented.
546 citations
Cites background from "Experimental comparison of filter a..."
...Slope-based filters work well in fairly flat terrain, but become more difficult as the slope of the terrain increases (Sithole and Vosselman, 2004), especially in a steep forested landscape....
[...]
...…for filtering LiDAR points is currently an active research topic (Silván-Cárdenas and Wang, 2006). extracting ground points from LiDAR point clouds (Sithole and Vosselman, 2004; Silván-Cárdenas and Wang, 2006; Kobler et al., 2007), among which interpolationbased (Kraus and Pfeifer, 1998),…...
[...]
...The primary aim of the study was to: (1) determine the comparative performance of existing filters; (2) determine the sensitivity of filtering algorithms under varying point densities; and (3) identify future research issues in the filtering of point clouds (Sithole and Vosselman, 2004)....
[...]
TL;DR: In this paper, two different methods for correcting the laser scanning intensity data for known influences resulting in a value proportional to the reflectance of the scanned surface are presented, data-driven and model-driven correction.
Abstract: Most airborne and terrestrial laser scanning systems additionally record the received signal intensity for each measurement. Multiple studies show the potential of this intensity value for a great variety of applications (e.g. strip adjustment, forestry, glaciology), but also state problems if using the original recorded values. Three main factors, a) spherical loss, b) topographic and c) atmospheric effects, influence the backscatter of the emitted laser power, which leads to a noticeably heterogeneous representation of the received power. This paper describes two different methods for correcting the laser scanning intensity data for these known influences resulting in a value proportional to the reflectance of the scanned surface. The first approach – data-driven correction – uses predefined homogeneous areas to empirically estimate the best parameters (least-squares adjustment) for a given global correction function accounting for all range-dependent influences. The second approach – model-driven correction – corrects each intensity independently based on the physical principle of radar systems. The evaluation of both methods, based on homogeneous reflecting areas acquired at different heights in different missions, indicates a clear reduction of intensity variation, to 1/3.5 of the original variation, and offsets between flight strips to 1/10. The presented correction methods establish a great potential for laser scanning intensity to be used for surface classification and multi-temporal analyses.
509 citations
References
More filters
01 Jan 2005
2,654 citations
"Experimental comparison of filter a..." refers background in this paper
...Further details can be found in Roggero (2001)....
[...]
Journal Article•
01 Jan 2000-ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
1,236 citations
"Experimental comparison of filter a..." refers background in this paper
...Further details can be found in Axelsson (1999, 2000)....
[...]
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.
Abstract: Large-scale terrain measurement in wooded areas was an unsolved problem up to now. Laser scanning solves this problem to a large extent. In this article, the characteristics of laser scanning will be compared to photogrammetry with reference to a big pilot project. Laser scanning supplies data with a skew distribution of errors because a portion of the supplied points is not on the terrain but on the treetops. Thus, the usual interpolation and filtering has to be adapted to this new data type. We will report on the implementation of this new method. The results are in accordance with the expectations. The geomorphologic quality of the contours, computed from a terrain model derived from laser scanning, needs to be improved. Solutions are still to be found.
1,196 citations
"Experimental comparison of filter a..." refers background in this paper
...Further details can be found in Kraus and Pfeifer (1998, 2001), Pfeifer et al. (1998, 1999a,b, 2001) and Briese and Pfeifer (2001)....
[...]
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.
Abstract: Airborne laser scanning systems are opening new possibilities for surveys and documentation of difficult areas and objects, such as dense city areas, forest areas and electrical power lines. Laser scanner systems available on the market are presently in a fairly mature state of art while the processing of airborne laser scanner data still is in an early phase of development. To come from irregular 3D point clouds to useful representations and formats for an end-user requires continued research and development of methods and algorithms for interpretation and modelling. 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. The classification algorithms are based on the Minimum Description Length criterion. The use of reflectance data and multiple echoes from the laser scanner is examined and found to be useful in many applications.
767 citations
"Experimental comparison of filter a..." refers background in this paper
...Further details can be found in Axelsson (1999, 2000)....
[...]
...Although this expectation has been stated previously (Ackermann, 1999; Axelsson, 1999), the data fusion for the purpose of filtering still needs to be developed....
[...]
01 Jan 2000
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.
Abstract: Laser altimetry is becoming the prime method for large scale acquisition of height data. Although laser altimetry is full integrated into processes for the production of digital elevation models in different countries, the derivation of DEM's from the raw laser altimetry measurements still causes problems. In particular the laser pulses reflected on the ground surface need to be distinguished from those reflecting on buildings and vegetation. In this paper a new method is proposed for filtering laser data. This method 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. In experiments it is shown that the latter filter causes smaller errors in the resulting digital elevation models. In general the performance of the filters deteriorates with a decreasing point density.
628 citations
"Experimental comparison of filter a..." refers background or methods in this paper
...Marco Roggero This filter is a variant on the morphological filter developed by Vosselman (Vosselman, 2000; Vosselman and Maas, 2001)....
[...]
...Like the Roggero filter, this filter is a variant on the morphological filter developed by Vosselman (Vosselman, 2000; Vosselman and Maas, 2001)....
[...]
...This filter is a variant on the morphological filter developed by Vosselman (Vosselman, 2000; Vosselman and Maas, 2001)....
[...]