Showing papers by "Norbert Pfeifer published in 2009"
TL;DR: A comparison of the evaluation techniques shows that they highlight different properties of the building detection results, and a comprehensive evaluation strategy involving quality metrics derived by different methods is proposed.
Abstract: In this paper, different methods for the evaluation of building detection algorithms are compared. Whereas pixel-based evaluation gives estimates of the area that is correctly classified, the results are distorted by errors at the building outlines. These distortions are potentially in an order of 30%. Object-based evaluation techniques are less affected by such errors. However, the performance metrics thus delivered are sometimes considered to be less objective, because the definition of a ldquocorrect detectionrdquo is not unique. Based on a critical review of existing performance metrics, selected methods for the evaluation of building detection results are presented. These methods are used to evaluate the results of two different building detection algorithms in two test sites. A comparison of the evaluation techniques shows that they highlight different properties of the building detection results. As a consequence, a comprehensive evaluation strategy involving quality metrics derived by different methods is proposed.
311 citations
TL;DR: In this article, an automatic method for water surface classification and delineation by combining the geometrical and signal intensity information provided by airborne laser scanning (ALS) is presented. But this method is not suitable for water-land boundary segmentation.
Abstract: In recent years airborne laser scanning (ALS) evolved into a state-of-the-art technology for topographic data acquisition. We present a novel, automatic method for water surface classification and delineation by combining the geometrical and signal intensity information provided by ALS. The reflection characteristics of water surfaces in the near-infrared wavelength (1064 nm) of the ALS system along with the surface roughness information provide the basis for the differentiation between water and land areas. Water areas are characterized by a high number of laser shot dropouts and predominant low backscatter energy. In a preprocessing step, the recorded intensities are corrected for spherical loss and atmospheric attenuation, and the locations of laser shot dropouts are modeled. A seeded region growing segmentation, applied to the point cloud and the modeled dropouts, is used to detect potential water regions. Object-based classification of the resulting segments determines the final separation of water and non-water points. The water-land-boundary is defined by the central contour line of the transition zone between water and land points. We demonstrate that the proposed workflow succeeds for a regulated river (Inn, Austria) with smooth water surface as well as for a pro-glacial braided river (Hintereisfernerbach, Austria). A multi-temporal analysis over five years of the pro-glacial river channel emphasizes the applicability of the developed method for different ALS systems and acquisition settings (e.g. point density). The validation, based on real time kinematic (RTK) global positioning system (GPS) field survey and a terrestrial orthophoto, indicate point cloud classification accuracy above 97% with 0·45 m planimetric accuracy (root mean square error) of the water–land boundary. This article shows the capability of ALS data for water surface mapping with a high degree of automation and accuracy. This provides valuable datasets for a number of applications in geomorphology, hydrology and hydraulics, such as monitoring of braided rivers, flood modeling and mapping. Copyright © 2009 John Wiley & Sons, Ltd.
173 citations
TL;DR: The presented method uses the full 3D information for both feature extraction and solar potential analysis, which offers a number of new applications in fields where natural processes are influenced by the incoming solar radiation.
Abstract: A relative height threshold is defined to separate potential roof points from the point cloud, followed by a segmentation of these points into homogeneous areas fulfilling the defined constraints of roof planes. The normal vector of each laser point is an excellent feature to decompose the point cloud into segments describing planar patches. An objectbased error assessment is performed to determine the accuracy of the presented classification. It results in 94.4% completeness and 88.4% correctness. Once all roof planes are detected in the 3D point cloud, solar potential analysis is performed for each point. Shadowing effects of nearby objects are taken into account by calculating the horizon of each point within the point cloud. Effects of cloud cover are also considered by using data from a nearby meteorological station. As a result the annual sum of the direct and diffuse radiation for each roof plane is derived. The presented method uses the full 3D information for both feature extraction and solar potential analysis, which offers a number of new applications in fields where natural processes are influenced by the incoming solar radiation (e.g., evapotranspiration, distribution of permafrost). The presented method detected fully automatically a subset of 809 out of 1,071 roof planes where the arithmetic mean of the annual incoming solar radiation is more than 700 kWh/m2.
137 citations
TL;DR: In this paper, a DTM thinning approach based on adaptive TIN refinement was proposed to compress the point data while preserving the most relevant topographic features (height tolerance ±20 cm).
Abstract: . Airborne LiDAR (Light Detection And Ranging) combines cost efficiency, high degree of automation, high point density of typically 1–10 points per m2 and height accuracy of better than ±15 cm. For all these reasons LiDAR is particularly suitable for deriving precise Digital Terrain Models (DTM) as geometric basis for hydrodynamic-numerical (HN) simulations. The application of LiDAR for river flow modelling requires a series of preprocessing steps. Terrain points have to be filtered and merged with river bed data, e.g. from echo sounding. Then, a smooth Digital Terrain Model of the Watercourse (DTM-W) needs to be derived, preferably considering the random measurement error during surface interpolation. In a subsequent step, a hydraulic computation mesh has to be constructed. Hydraulic simulation software is often restricted to a limited number of nodes and elements, thus, data reduction and data conditioning of the high resolution LiDAR DTM-W becomes necessary. We will present a DTM thinning approach based on adaptive TIN refinement which allows a very effective compression of the point data (more than 95% in flood plains and up to 90% in steep areas) while preserving the most relevant topographic features (height tolerance ±20 cm). Traditional hydraulic mesh generators focus primarily on physical aspects of the computation grid like aspect ratio, expansion ratio and angle criterion. They often neglect the detailed shape of the topography as provided by LiDAR data. In contrast, our approach considers both the high geometric resolution of the LiDAR data and additional mesh quality parameters. It will be shown that the modelling results (flood extents, flow velocities, etc.) can vary remarkably by the availability of surface details. Thus, the inclusion of such geometric details in the hydraulic computation meshes is gaining importance in river flow modelling.
80 citations
01 Jan 2009
TL;DR: The objectives of the new OPALS program system are to provide a complete processing chain for large ALS projects and to shorten development cycles significantly, to help new research outcomes get available more rapidly for the scientific community.
Abstract: Since the mid-1990s, the Institute of Photogrammetry and Remote Sensing (I.P.F.) is engaged in Airborne Laser Scanning (ALS) in research and development. Scientific contributions have been made in a wide field of related topics like full waveform signal analysis, georeferencing and filtering of ALS point clouds, automatic breakline modelling, DTM generation, quality control, etc. Apart from that, converting research ideas into software solutions is an enduring tradition at the I.P.F. for which the DTM program SCOP++ is an example. Partial solutions of ALS-related issues have been implemented in SCOP++, but a complete processing chain is missing, as the development cycles for this highly interactive program are long. Thus, the objectives of the new OPALS program system are to provide a complete processing chain for large ALS projects and to shorten development cycles significantly. OPALS is designed as a collection of small well-defined modules which can be accessed in three different ways: (i) from DOS/Unix shells as executables, (ii) from Python shells as full-featured, platform-independent Python modules or (iii) from custom C++ programs by dynamic linkage (DLL) for fastest module calls. Sophisticated custom processing chains can be established by freely combining the OPALS modules using shell or Python scripts. To reduce development times, a lightweight framework is introduced. It allows non-expert programmers to implement their own modules, concentrating on the implementation of their latest research outcomes, whereas the framework deals with general issues like validation of user inputs, error handling, logging, etc. In this way, new research outcomes get available more rapidly for the scientific community. OPALS does not only target researchers, but also ALS service providers dealing with large ALS projects. Efficient data handling is a precondition for this purpose. Thus, the OPALS data manager (ODM) is one of the core units, allowing administration of data volumes in the order of 10 9 points. The ODM acts as spatial cache and provides high-performance spatial queries. Currently, a quality control package (opalsQC) is in progress and first results (point density maps, strip difference maps, 3D-strip shifts) are presented in the paper.
62 citations
TL;DR: A new methodology for high precision monitoring of deformations with a long term perspective using terrestrial laser scanning technology integrated with two complementary surveying techniques, i.e., high quality static GNSS positioning and precise tacheometry is presented.
Abstract: The paper presents a new methodology for high precision monitoring of deformations with a long term perspective using terrestrial laser scanning technology. In order to solve the problem of a stable reference system and to assure the high quality of possible position changes of point clouds, scanning is integrated with two complementary surveying techniques, i.e., high quality static GNSS positioning and precise tacheometry. The case study object where the proposed methodology was tested is a high pressure underground pipeline situated in an area which is geologically unstable.
60 citations
TL;DR: Results show that state-of-the-art ICESat waveform processing is able to analyze waveforms at the individual shot level, particularly outside urban areas.
Abstract: Since 2003, the full-waveform laser altimetry system onboard NASA's Ice, Cloud and land Elevation Satellite (ICESat) has acquired a worldwide elevation database. ICESat data are widely applied for change detection of ice sheet mass balance, forest structure estimation, and digital terrain model generation of remote areas. ICESat's measurements will be continued by a follow-up mission. To fully assess the application possibilities of the full-waveform products of these missions, this research analyzes the vertical accuracy of ICESat products over complex terrain with respect to land cover type. For remote areas, validation of individual laser shots is often beyond reach. For a country with extensive geo-infrastructure such as The Netherlands, excellent countrywide validation is possible. Therefore, the ICESat full-waveform product GLA01 and the land elevation product GLA14 are compared to data from the Dutch airborne laser altimetry archive Actual Height model of the Netherlands (AHN). For a total population of 3172 waveforms, differences between ICESat- and AHN-derived terrain heights are determined. The average differences are below 25 cm over bare land and urban areas. Over forests, differences are even smaller but with slightly larger standard deviations of about 60 cm. Moreover, a waveform-based feature height comparison resulted in feature height differences of 1.89 m over forest, 1.48 m over urban areas, and 29 cm over low vegetation. These results, in combination with the presented processing chain and individual waveform examples, show that state-of-the-art ICESat waveform processing is able to analyze waveforms at the individual shot level, particularly outside urban areas.
59 citations
01 Jan 2009
TL;DR: In this paper, the authors analyzed the potential of full-wave-form airborne laser scanning for tree species classification of a mixed-woodland environment, based on segmented tree crowns and the mean backscatter cross section of all echoes above the 50 th height percentile.
Abstract: Airborne laser scanning is an evolving operational measurement technique for deriving forest parameters. The objective of the current study was to analyze the potential of full-waveform airborne laser scanning for tree species classification of a mixed woodland. The quantities used were the echo width, backscatter cross section, as well as the distribution of the echoes in vertical direction. Based on segmented tree crowns the mean backscatter cross section of all echoes above the 50 th height percentile was computed. Additionally, the canopy density, describing the ratio of the number of all echoes above the 50 th height percentile and the total number of echoes, was used for a knowledge-based classification of coniferous and deciduous trees. The achieved overall accuracy was 83%. Furthermore, the standard deviation of the echo widths per crown segment was applied for a separation of spruce and larch. An overall accuracy of the classified tree species red beech, larch and spruce of 75% was obtained. The presented results show that combining geometric information and backscattering properties of full-waveform airborne laser scanning data has a high potential for tree species classification.
53 citations
01 Jan 2009
TL;DR: In this article, a model for strip adjustment without GNSS/IMU-trajectory data using five parameters per strip: one 3D shift, one roll angle, and one affine yaw parameter was presented.
Abstract: Airborne laser scanning (ALS) requires GNSS (Global Navigation Satellite System; e.g. GPS) and an IMU (Inertial Measurement Unit) for determining the dynamically changing orientation of the scanning system. Because of small but existing instabilities of the involved parts - especially the mounting calibration - a strip adjustment is necessary in most cases. In order to realize this adjustment in a rigorous way the GNSS/IMU-trajectory data is required. In some projects this data is not available to the user (any more). Derived from the rigorous model, this article presents a model for strip adjustment without GNSS/IMU-trajectory data using five parameters per strip: one 3D shift, one roll angle, and one affine yaw parameter. In an example with real data consiting of 61 strips this model was successfully applied leading to an obvious improvement of the relative accuracy from (59.3/23.4/4.5) [cm] to (7.1/7.2/2.2) (defined as RMS values in (X/Y/Z) of the differences of corresponding points derived by least squares matching in the overlapping strips). This example also clearly demonstrates the importance of the affine yaw parameter.
30 citations
TL;DR: In this article, the impacts of anthropogenic influences on karst geomorphology through various geomorphologically based environmental indicators are analyzed, visualizing, interpreting and discussing the impacts.
Abstract: The objective of this contribution is analyzing, visualizing, interpreting and discussing the impacts of anthropogenic influences on karst geomorphology through various geomorphologically based environmental indicators. The primary data sources are digital terrain models (DTMs) as continuous surface data, supported by aerial photographs, satellite images, topographic maps and databases of natural and anthropogenic features. The sources are supplemented by written information about surface changes and in situ inspections. Spatial analyses as quantitative methods in combination with enhanced visualizations as qualitative methods performed in a geographical information system (GIS) on different data sets are introduced as an important methodology. This enables explaining many anthropogenic influences on the terrain surface (landform), which were not perceived before by classical surveying techniques and verifications.
18 citations
01 Jan 2009
TL;DR: In this paper, the authors present the project "Determination of surface properties from laser scanning data" which addresses these demands by incorporating certain aspects of remote sensing in natural hazard management.
Abstract: Within the thematic area of Databases and Modelling a certain focus is placed on the effective acquisition and management of geo-data and the derivation of standardized products from this data, e.g. as input parameters in process simulation models. In most cases, in-situ data collection (e.g. run-off measurements) is state-of-the-art. As there is a growing demand for area-wide data collection, the utilization of remote sensing technology will gain ground in the future. Within alpS the project ‘Determination of surface properties from laser scanning data’ addresses these demands by incorporating certain aspects of remote sensing in natural hazard management. Remote sensing is the contactless collection of information about an object or process. This is done with electromagnetic waves and imaging methods. Remote sensing can be carried out from the earth’s surface or from airborne and spaceborne platforms. For earth observation issues passive sensors are widely applied, which record the reflected radiation of natural energy sources (with the sun as the most important one). For many applications the method of choice is still aerial photography. Active sensors are more flexible as they have their own energy source. Laser scanning is such an active method.
TL;DR: This article concentrates on the integrated self-calibration of both the interior orientation and the distance measurement system of a time-of-flght range camera (photonic mixer device) based on the same data set that is captured without auxiliary devices serving as high-order reference, but with the camera being guided by hand.
Abstract: This article concentrates on the integrated self-calibration of both the interior orientation and the distance
measurement system of a time-of-flght range camera (photonic mixer device). Unlike other approaches that
investigate individual distortion factors separately, in the presented approach all calculations are based on the
same data set that is captured without auxiliary devices serving as high-order reference, but with the camera being
guided by hand. Flat, circular targets stuck on a planar whiteboard and with known positions are automatically
tracked throughout the amplitude layer of long image sequences. These image observations are introduced into
a bundle block adjustment, which on the one hand results in the determination of the interior orientation.
Capitalizing the known planarity of the imaged board, the reconstructed exterior orientations furthermore allow
for the derivation of reference values of the actual distance observations. Eased by the automatic reconstruction
of the cameras trajectory and attitude, comprehensive statistics are generated, which are accumulated into a
5-dimensional matrix in order to be manageable. The marginal distributions of this matrix are inspected for the
purpose of system identification, whereupon its elements are introduced into another least-squares adjustment,
finally leading to clear range correction models and parameters.
01 Aug 2009
TL;DR: In den last 15 years, Airborne Laserscanning (ALS) has been revolutioniert in the world of computer vision as mentioned in this paper, and the Gelandeaufnahme durch bislang unerreichte Datendichte von mehreren Punkten/m2 have been besser als 15 cm revolutionized.
Abstract: In den letzten 15 Jahren hat Airborne Laserscanning (ALS) die Gelandeaufnahme durch bislang unerreichte Datendichte von mehreren Punkten/m2 sowie Hohengenauigkeit von besser als 15 cm revolutioniert. Als prazise geometrische Datengrundlage fur Gefahrenzonenplanung, Ausweisung von Uberschwemmungsflachen, aber auch fur wasserbiologische Fragestellungen sind topographische Daten aus Laserscanning heute nicht mehr wegzudenken. Der vorliegende Artikel gibt einen Uberblick uber das Einsatzspektrum von ALS-Daten in der wasserwirtschaftlichen Praxis. Im ersten Teil wird der Aufbau eines genauen Wasserlauf-Gelandemodells beschrieben. Die Prozesskette beginnt bei der Qualitatskontrolle und umfasst weiters die Ableitung hydraulisch relevanter Gelandekanten, die Trennung der ALS-Punktwolke in Wasser-, Boden- und Nicht-Bodenpunkte sowie die Interpolation qualitativ hochwertiger digitaler Gelandemodelle (DGM). Neben dem DGM sind weiters Gebaude- und Vegetationslayer fur Folgeanwendungen von Interesse. Im zweiten Teil wird die Aufbereitung dichter ALS-basierter Topographiedaten fur die anschliesende hydrologische bzw. hydraulische Modellierung behandelt. Eine qualitativ hochwertige Ausdunnung der DGM-Daten, bei der typischerweise Reduktionsraten bis zu 99 % erreicht werden, ist dabei fur die erfolgreiche Anwendung in nachfolgenden Simulationen von groser Bedeutung. Abschliesend wird eine geometrische Herangehensweise zur Generierung von Rechengittern beschrieben.
TL;DR: A number of approaches are reviewed within this framework and discussed, which differ in the object space features used for calibration, the calibration models themselves, and possibly required environmental conditions.
Abstract: Range cameras and terrestrial laser scanners provide 3D geometric information by directly measuring the range from the sensor to the object. Calibration of the ranging component has not been studied systematically yet, and this paper provides a first overview. The proposed approaches differ in the object space features used for calibration, the calibration models themselves, and possibly required environmental conditions. A number of approaches are reviewed within this framework and discussed. For terrestrial laser scanners, improvement in accuracy by a factor up to two is typical, whereas range camera calibration still lacks a proper model, and large systematic errors typically remain.
01 Jan 2009
TL;DR: Hofle et al. as discussed by the authors presented a fully automatic procedure for glacier surface classification, working directly on the LiDAR point cloud (Fig.2) and laser shot dropouts are modeled.
Abstract: REFERENCES: [1] Hofle, B., Vetter, M., Pfeifer, N., Mandlburger, G., Stotter, J. (2009): Water surface mapping from airborne laser scanning using signal intensity and elevation data. Earth Surface Processes and Landforms. submitted. [2] Hofle, B., Pfeifer, N. (2007): Correction of laser scanning intensity data: data and model-driven approaches. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 62 (6), 415-433. [3] Hofle, B., Geist, T., Rutzinger, M., Pfeifer, N. (2007): Glacier surface segmentation using airborne laser scanning point cloud and intensity data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 36 (Part 3/W52), pp. 195-200. We present a fully automatic procedure for glacier surface classification, working directly on the LiDAR point cloud (Fig.2). Firstly, signal amplitudes are corrected [2] (Fig.3) and laser shot dropouts are modeled (Fig.4), i.e. where no laser point could be measured [1]. A point cloud based segmentation delineates connected, homogeneous areas (i.e. low variation in amplitude within a segment and no abrupt change in elevation). Based on the segment feature statistics (e.g. mean amplitude) the surface objects are classified into snow, firn, ice or surface irregularities (e.g. crevasses). Methods
01 Apr 2009
TL;DR: Hofle et al. as mentioned in this paper presented a fully automatic procedure for glacier surface classification, working directly on the LiDAR point cloud (Fig.2) and laser shot dropouts are modeled.
Abstract: REFERENCES: [1] Hofle, B., Vetter, M., Pfeifer, N., Mandlburger, G., Stotter, J. (2009): Water surface mapping from airborne laser scanning using signal intensity and elevation data. Earth Surface Processes and Landforms. submitted. [2] Hofle, B., Pfeifer, N. (2007): Correction of laser scanning intensity data: data and model-driven approaches. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 62 (6), 415-433. [3] Hofle, B., Geist, T., Rutzinger, M., Pfeifer, N. (2007): Glacier surface segmentation using airborne laser scanning point cloud and intensity data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 36 (Part 3/W52), pp. 195-200. We present a fully automatic procedure for glacier surface classification, working directly on the LiDAR point cloud (Fig.2). Firstly, signal amplitudes are corrected [2] (Fig.3) and laser shot dropouts are modeled (Fig.4), i.e. where no laser point could be measured [1]. A point cloud based segmentation delineates connected, homogeneous areas (i.e. low variation in amplitude within a segment and no abrupt change in elevation). Based on the segment feature statistics (e.g. mean amplitude) the surface objects are classified into snow, firn, ice or surface irregularities (e.g. crevasses). Methods
01 Apr 2009
TL;DR: In this article, the authors present the results of the Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing (DopplerLab) at the University of Vienna.
Abstract: (1) Christian Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Austria (bh@ipftuwienacat), (2) International Institute for Geo-Information Science and Earth Observation, The Netherlands (rutzinger@itcnl), (3) Department of Geography and Regional Research, University of Vienna, Austria (rainerbell@univieacat)
01 Jan 2009
TL;DR: In this article, the authors present the results of the Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing (CLDSRS) at Vienna University of Technology, Austria.
Abstract: (1) Christian Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Austria (bh@ipf.tuwien.ac.at), (2) International Institute for Geo-Information Science and Earth Observation, The Netherlands (rutzinger@itc.nl), (3) Department of Geography and Regional Research, University of Vienna, Austria (rainer.bell@univie.ac.at)
01 Apr 2009
TL;DR: Vetter et al. as mentioned in this paper presented the results of the Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing at the University of Innsbruck in Austria.
Abstract: (1) Institute of Geography, University of Innsbruck, Innsbruck, Austria (michael.vetter@uibk.ac.at), (2) Christian Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Vienna, Austria , (3) International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands
01 Apr 2009
TL;DR: In this paper, the authors describe the importance of high-resolution Digital Terrain Models (DTMs) representing the bare Earth as a fundamental input for various applications in geomorphology, and the essential advances in the technologies are improvements in ranging through the introduction of full waveform (FWF) laser scanning and rigorous models of strip adjustment.
Abstract: High-resolution Digital Terrain Models (DTMs) representing the bare Earth are a fundamental input for various applications in geomorphology. Airborne laser scanning (ALS) is established as a standard tool for deriving DTMs over large areas with unprecedented accuracy. Due to advances in sensor technology and in processing algorithms in the recent years the obtainable accuracy is still increasing. Accuracy is understood as the deviation from the elevation at one specified point to its true value. These advances may lead to a more efficient data acquisition, if reduced accuracy is targeted, but also allow data acquisition schemes with more detail becoming visible, i.e. small features of the relief. For the latter a high internal precision, i.e. repeatability, is necessary. The essential advances in the technologies are improvements in ranging through the introduction of full-waveform (FWF) laser scanning and rigorous models of strip adjustment.
01 Apr 2009
TL;DR: Vetter et al. as mentioned in this paper proposed a method for the analysis of spatial data from laser scanning and remote sensing in Innsbruck, Austria, where they used the Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing.
Abstract: (1) Institute of Geography, University of Innsbruck, Innsbruck, Austria (michael.vetter@uibk.ac.at), (2) Christian Doppler Laboratory for Spatial Data from Laser Scanning and Remote Sensing, Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Vienna, Austria , (3) International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands, (4) Austrian Research Promotion Agency (FFG), Vienna, Austria