Photogrammetric control points from airborne laser scanner (original) (raw)
Related papers
Photogrammetric Record, 2008
The integration of photogrammetric images and lidar data is becoming a powerful procedure that can be applied in the optimisation of photogrammetric mapping techniques. The complementary nature of lidar and photogrammetric data optimises the performance of many procedures used to extract 3D spatial information from data. For example, photogrammetric imagery enables the accurate extraction of building borders and lidar provides accurate 3D points that give information on the physical surfaces of buildings. These properties demonstrate the usefulness of combining the two types of data to achieve a more robust and complete reconstruction of 3D objects. Photogrammetric procedures require the exterior orientation parameters (EOPs) of the images to extract mapping information. Despite the availability of GPS/INS systems, which greatly assist in direct georeferencing of the imagery, the majority of commercially available photogrammetric systems require control information in order to carry out photogrammetric mapping. Due to improvements in the accuracy of lidar systems in recent years, lidar data is considered a viable source of photogrammetric control. Point features are the principal source of control for photogrammetric triangulation, although linear features and planar patches have also been used. This paper presents a method of georeferencing photogrammetric images using lidar data. The method uses the centroids of rectangular building roofs as control points in the photogrammetric procedure. The centroid of a rectangular building roof derived using lidar data is equivalent to a single control point with 3D coordinates, and can therefore be used in traditional photogrammetric systems. Two photogrammetric experiments were carried out to verify the feasibility of the methodology. The results obtained from these experiments confirm the feasibility of applying the proposed methodology to the georeferencing of photogrammetric images using lidar data.L’intégration des données lidar avec les images photogrammétriques constitue une méthode puissante que l’on peut utiliser pour optimiser les techniques photogrammétriques en cartographie. La nature complémentaire des données photogrammétriques et lidar permet d’optimiser les performances de nombreux processus utilisés pour extraire de ces données des informations localisées et en 3D. Par exemple, l’imagerie photogrammétrique permet d’extraire avec précision les contours des bâtiments tandis que le lidar fournit avec précision des points en 3D qui nous renseignent sur la nature des surfaces de ces bâtiments. On conçoit donc l’utilité d’une combinaison de ces deux types de données pour obtenir une reconstruction plus robuste et plus complète d’objets en 3D. Les techniques photogrammétriques nécessitent de connaître les paramètres d’orientation externe des images pour en extraire les informations cartographiques. En dépit de l’existence des systèmes GPS et inertiels qui apportent une grande aide dans la géolocalisation des images, la plupart des systèmes photogrammétriques disponibles dans le commerce ont besoin d’un canevas de points d’appui pour effectuer une restitution cartographique. Etant donné les progrès réalisés ces dernières années dans la précision des systèmes lidar, on peut considérer que ces données lidar sont une source valable pour former ce canevas d’appui. Le canevas destinéà la triangulation photogrammétrique est essentiellement constitué de détails ponctuels, même si l’on utilise aussi des éléments linéaires ou surfaciques. On présente dans cet article une méthode pour géolocaliser les images photogrammétriques à partir de données lidar. Dans cette méthode on utilise les centroïdes des toits de bâtiments rectangulaires comme points d’appui photogrammétriques. Chaque centroïde issu des données lidar constitue l’un des points d’appui de ce canevas, déterminé par ses trois coordonnées et conséquent utilisable comme tel dans les systèmes photogrammétriques classiques. On a réalisé deux essais photogrammétriques pour s’assurer de la faisabilité de cette méthode. Les résultats obtenus ont confirmé qu’il était possible d’utiliser cette méthode pour géolocaliser les images photogrammétriques avec des données lidar.Die Integration photogrammetrischer Bilddaten und Laserscandaten, zweier komplementärer Datenquellen, bietet die Möglichkeit zur Optimierung der photogrammetrischen Erfassung räumlicher Information hinsichtlich Genauigkeit und Zuverlässigkeit. Die photogrammetrische Auswertung von Bilddaten erlaubt eine genaue Extraktion von Gebäudeumrisslinien, wohingegen Laserscandaten genaue 3D-Punkte auf den Gebäudeoberflächen bereitstellen. Die photogrammetrischen Verfahren benötigen die Parameter der Äußeren Orientierung (EOP) der Bilder, die in den meisten Fällen über die Messung von Passpunkten erfolgt, trotz der zunehmenden Verfügbarkeit von GPS/INS Systemen, die die direkte Georeferenzierung der Bilder unterstützen. Durch die Verbesserungen in der Genauigkeit der Laserscansysteme in den letzten Jahren können Laserscandaten als mögliche Grundlage für Passinformation für photogrammetrische Auswertungen eingesetzt werden. In der Photogrammetrie werden meist Punkte als Passinformation verwendet, obwohl auch schon lineare Merkmale oder ebene Flächen für die Bestimmung der äußeren Orientierung eingesetzt worden sind. Dieser Beitrag stellt eine Methode zur Georeferenzierung photogrammetrischer Bilder mit Hilfe von Laserscandaten vor. Die Methode stützt sich auf die Schwerpunkte rechteckiger Dachflächen von Gebäuden als Passpunkte in der photogrammetrischen Orientierung. An Hand von zwei photogrammetrischen Beispielen wird die Anwendbarkeit der Methode nachgewiesen.La integración de imágenes fotogramétricas y datos lidar se está convirtiendo en un procedimiento muy eficaz en la optimización de las técnicas de restitución fotogramétrica. El carácter complementario de los datos lidar y fotogramétricos permite optimizar muchos procedimientos de extracción de información espacial tridimensional de los datos. Por ejemplo, las imágenes fotogramétricas permiten la extracción exacta de contornos de edificios al tiempo que el lidar aporta datos tridimensionales exactos de las superficies físicas de los edificios. Estas propiedades ofrecen la ventaja de combinar los dos tipos de datos para conseguir una reconstrucción más robusta y completa de los objetos tridimensionales. Los procedimientos fotogramétricos requieren de parámetros de orientación externa de las imágenes para la restitución. Pese a la disponibilidad de sistemas integrados de navegación inercial y GPS para la georreferenciación directa de las imágenes, la mayoría de los sistemas fotogramétricos disponibles requieren de información de control para la restitución fotogramétrica. Con la mejora de la exactitud que los sistemas lidar han experimentada en los últimos años, sus datos se han convertido en una fuente asequible de control fotogramétrico. Los objetos puntuales son el principal tipo de información de control para la triangulación fotogramétrica, aunque también se han utilizado objetos lineales y teselas planas. Este artículo presenta un método de georreferenciación de imágenes fotogramétricas a partir de datos lidar utilizando los centroides de los tejados de edificios rectangulares como puntos de apoyo en el proceso fotogramétrico. El centroide de un tejado rectangular obtenido de los datos lidar es equivalente a un punto de apoyo con coordenadas tridimensionales y, por lo tanto, puede utilizarse en los sistemas fotogramétricos tradicionales. Se llevaron a cabo dos experimentos fotogramétricos para verificar la viabilidad de la metodología y los resultados confirman la aplicabilidad de esta metodología propuesta de georreferenciación de imágenes fotogramétricas mediante datos lidar.
In this study the planimetric accuracy of LIDAR data was verified with application of the intensity of laser beam reflection and point cloud modelling results. The presented research was the basis for improving the accuracy of the products from the processing of LIDAR data, what is particularly important in issues related to surveying measurements. In the experiment, the true-ortho from the large-format aerial images with known exterior orientation was used to check the planimetric accuracy of LIDAR data in two of the proposed approaches. The first analysis was carried out by comparing of the position of selected points identifiable on true-ortho from aerial images with corresponding points in the raster of reflection intensity. The second method to verify the planimetric accuracy used roof ridges from 3D building models automatically created from LIDAR data being intersections of surfaces from point cloud. Both analyses were carried out for 3 fragments of LIDAR strips. Detected systematic planimetric error in the size of few a centimetres enabled the implementation of appropriate correction for analyzed data locally. The presented problem and proposed solutions provide an opportunity to improve the accuracy of the LiDAR data. Such methods can allow for efficient use by specialists in other fields not directly related to the issues of orientation and accuracy of photogrammetric data during their acquisition and pre-processing * Corresponding author
Laser Scanning Airborne Systems -a New Step in Engineering Surveying
The new laser scanning airborne technologies can be successfully used in engineering surveying and geodesy. They are mounted on light airplanes or on helicopters, have a fly speed comprised between 70 to 100 km/h; a height fly comprised between 50 to 100 m and can collect three-dimensional points with a density of 20 to 30 per meter. The advantages of these systems are: reduction of field work time, easy and safe access to objects (railway, roads), permit to create 3D homogeneous spatial data base, ensure the topographic and geodetic support for specific information systems.
Generation Of 3D City Models From Airborne Laser Scanning Data
1997
Airborne laser scanners enable the geometric acquisitionof the terrain surface, including objects liketrees or buildings which rise from the terrain. Eventhough for a number of applications a so#called DigitalSurface Model #DSM# representing the surfacegeometry by an object independent distribution ofpoints is su#cient, the further quali#cation of theoriginal scanner data is necessary for more sophisticatedtasks like visualizations or high quality3Dsimulations.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
Abstract. The ever-growing and complex structure of cities has increased the need to include advanced information and communication technologies in management processes. In parallel with this, the concept of smart cities has emerged and the creation and use of three-dimensional (3D) city models have become one of the most important components for tracking cities online. Depending on technological advances; Photogrammetric methods come to the fore in surveying because it offers convenience in terms of cost and time. Among the photogrammetric methods, mobile laser scanning and UAV (Unmanned Aerial Vehicle) systems have become very popular. In this study; Necmettin Erbakan University, Faculty of Social Sciences and Humanities (SBIF), located in Köyceğiz Campus, was chosen as the study area and focused on integrating three-dimensional (3D) models produced by terrestrial and aerial photogrammetry under the theme of smart cities.
Reports on Geodesy and Geoinformatics, 2017
Airborne laser scanning data (ALS) are used mainly for creation of precise digital elevation models. However, it appears that the informative potential stored in ALS data can be also used for updating spatial databases, including the Database of Topographic Objects (BDOT10k). Typically, geometric representations of buildings in the BDOT10k are equal to their entities in the Land and Property Register (EGiB). In this study ALS is considered as supporting data source. The thresholding method of original ALS data with the use of the alpha shape algorithm, proposed in this paper, allows for extraction of points that represent horizontal cross section of building walls, leading to creation of vector, geometric models of buildings that can be then used for updating the BDOT10k. This method gives also the possibility of an easy verification of up-to-dateness of both the BDOT10k and the district EGiB databases within geometric information about buildings. For verification of the proposed methodology there have been used the classified ALS data acquired with a density of 4 points/m 2. The accuracy assessment of the identified building outlines has been carried out by their comparison to the corresponding EGiB objects. The RMSE values for 78 buildings are from a few to tens of centimeters and the average value is about 0,5 m. At the same time for several objects there have been revealed huge geometric discrepancies. Further analyses have shown that these discrepancies could be resulted from incorrect representations of buildings in the EGiB database.
2007
The paper deals with the registration and modelling of terrestrial laser point clouds. For both problems a non parametric regression is suitably exploited, whose unknowns are the function values and the partial derivatives of a second order Taylor’s expansion estimated for a certain number of surface points. These allow to directly estimate local curvatures, namely Gaussian, mean and principal values. Relating to the registration problem, tie points are automatically detected from point clusters having extreme Gaussian curvature values. The centroids of such clusters generate a vertexes configuration: the point to point correspondences are automatically defined by the analysis of the respective adjacency matrices. For these sets of pairs, the pre-alignment roto-translation parameters are computed by a SVD algorithm, while the final alignment is executed by an ICP method. The paper further proposes a method to directly detect the discontinuities (segmentation) and to successively est...
Polyhedral building model from airborne laser scanning data
Geomatics and Environmental Engineering, 2010
Lidar, also known as laser scanning, is a new, highly automated technique supplying data of high accuracy, reflecting scanned space surrounding us. The collected data are commonly called “points cloud” or 3D image. Among data collecting systems we can discriminate these located on board of airplanes, called airborne laser scanning, and these performing measurements from the ground, called terrestrial systems. Independent on the type of system, measured data are giving us three-dimensional information which can be understood as a product. Nevertheless, for many works such product is only a starting point for obtaining the final product, e.g. in the form of DTM, DSM or models of buildings, trees. Transition from raw data to final product is usually by means of automatic or semi-automatic data processing procedures.
Fusing airborne laser scanner data and aerial imagery for the automatic …
International Archives of …
Using airborne laser scanner data, buildings can be detected automatically, and their roof shapes can be reconstructed. The success rate of building detection and the level of detail of the resulting building models depend on the resolution of the laser scanner data, which is still lower ...