Laser Scanning Data Processing Research Articles

ОСОБЕННОСТИ ПРЕДВАРИТЕЛЬНОЙ ОБРАБОТКИ ДАННЫХ МОБИЛЬНОГО ЛАЗЕРНОГО СКАНИРОВАНИЯ

The goal of preliminary mobile laser scanning (MLS) data processing is generating a unified point cloud in a required coordinate system. During this processing calibration of 2D scanners and digital cameras, point cloud adjustment, data filtering such as removal of noise and remirror points. Currently huge amount of software is developed for solving these tasks, but a degree of their auto-mation differs. Depending on software, type of scanned area preliminary MLS data processing technique can differ. The analysis of carried out scanning results with the task of revealing their pe-culiarities, determination of the preliminary data processing order and deciding about necessity to accept additional manual procedures.

Plane segmentation from point clouds

Recently, attempts have been made to automate data acquisition, which is also related to efforts to automate data processing. The paper deals with the automation of terrestrial laser scanning data processing. The approaches for point cloud segmentation are briefly described. An algorithm based on random sample consensus is proposed for automated plane identification and plane segmentation from point clouds. The proposed approach was tested by processing point clouds; the results of the testing are also described. Based on the proposed algorithm, a standalone application for automated plane segmentation from laser scanner data using Matlab® software was developed.

Multi-scan segmentation of terrestrial laser scanning data based on normal variation analysis

Point cloud segmentation groups points with similar attributes with respect to geometric, colormetric, radiometric, and/or other information to support Terrestrial Laser Scanning (TLS) data processing such as feature extraction, classification, modeling, analysis, and so forth. In this paper we propose a segmentation method consisting of two main steps. First, a novel feature extraction approach, NORmal VAriation ANAlysis (Norvana), eliminates some noise points and extracts edge points without requiring a general (and error prone) normal estimation at each point. Second, region growing groups the points on a smooth surface to obtain the segmentation result. For efficiency, both steps exploit the angular grid structure storing each TLS scan that is often neglected in many segmentation algorithms, which are primarily developed for unorganized point clouds. Additionally, unlike the existing methods exploiting the angular grid structure that can only be applied to a single scan, the proposed method is able to segment multiple registered scans simultaneously. The algorithm also takes advantage of parallel programming for efficiency. In the experiment, both qualitative and quantitative evaluations are performed through two datasets whilst the robustness and efficiency of the proposed method are analyzed and discussed.

Hybrid processing of laser scanning data

In this article the analysis of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the base of usage of laser scanning data for historic building information modeling is presented. The results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application for the historical building of St. Petersburg Polytechnic University shows reliability of the proposed approaches.

Extracting features from laser scanning point cloud

Analyses of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the basis of usage of laser scanning data for historic building information modelling are presented. Some results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application to historical building of St. Petersburg Polytechnic University shows the robustness of the approaches proposed.

Un approccio multidisciplinare per documentare e visualizzare un sito archeologico: la villa d’otium di Massaciuccoli (Massarosa, LU)

The research project VisualVersilia 3D aims at offering a new method to record andvisualize the territory and its heritage by matching the traditional reading of documents and the potential use of modern communication technologies. The purpose of the project is to define a methodology that can be applied to material culture, as well as to other types of contents and contexts, to enhance the characteristic features of the territory and its heritage. The innovation of the project consists in the development of a procedure for documenting current and past historical times and integrating their 3D visualizations with rendering, capable of returning an immersive virtual reality for a successful enhancement of the heritage. The research implements the methodology in the archaeological complex of Massaciuccoli (Massarosa, LU), one of the best preserved Roman site of the Versilia area (Tuscany, Italy). The activities briefly consist in: 1) analysis of all types of available sources; 2) metric three-dimensional survey by laser scanning technology addressed to the structures and buildings of the complex; 3) laser scanning data processing; 4) realization of virtual 3D rendering related to Roman and current condition for documentation and conservation purposes; 5) creation of virtual tour of the site in its current form, on the basis of spherical images then enhanced by texts, and 3D models of the Roman age.

Detection of structural faults in piers of masonry arch bridges through automated processing of laser scanning data

This paper introduces a new methodology for the automated processing of large point clouds for the diagnosis of structural pathologies in piers of masonry arch bridges. This method starts with the automatic segmentation of the global point cloud of the entire bridge in its different structural elements (piers, arches, spandrel walls, etc.). Later, piers were further segmented in order to be able to detect and quantify structural pathologies. Particularly, faults are based in geometric anomalies (tilts and skews) of the pier walls that might be indicators of stability problems of the entire bridge. The methodology was validated using several samples of representative masonry arch bridges. The obtained results demonstrate that this method can provide useful information about the structural health of the bridge requiring neither training in the technology nor advanced knowledge in the processing of laser scanning data.

Semiautomatic Registration of Terrestrial Laser Scanning Data Using Perspective Intensity Images

Point cloud registration is an important procedure for terrestrial laser scanning data processing. Artificial targets are usually used in practice to guarantee a robust registration. However, installing and locating targets are labor-intensive for large surveying and mapping project. A methodology for semiautomatic registration of terrestrial point clouds using perspective intensity images is presented in this letter. To register two point clouds, perspective intensity image series of the scanning area are first generated from the point clouds. Then, corner points are extracted from the generated perspective intensity images and are interactively selected as tie points. The 3-D coordinates of the selected tie points are directly obtained or estimated using least squares method. Registration parameters are solved using singular value decomposition. To improve robustness and accuracy of the registration, random sample consensus is used to remove outliers in the tie points. The robustness and effectiveness of the presented methodology is demonstrated by experimental results.

A Reverse Engineering method for 3d parametric modeling of geometries based on processing of laser scanning data and a sweep technique

A Reverse Engineering (RE) method for parametric modelling is presented in this paper. According to this method laser scanning data are processed by means of an algorithm and a parametric geometry is produced. The algorithm generates a spline used as a driving curve for a 2D profile, both approximated from the point cloud data, with the final geometry being produced through with a sweep based technique. The method was applied to digitize a commercial product, a bottle, and the geometry was reconstructed at high accuracy and surface quality. Finally the results of the proposed method were compared with auto surfacing from *.stl files and with surfaces generated by means of sweep commands without converting curves to splines.

Modeling hemispherical reflectance for natural surfaces based on terrestrial laser scanning backscattered intensity data.

Independent of instrumental properties and scanning geometry, target reflectance is significantly important for terrestrial laser scanning (TLS) data processing and utilization, especially in multi-temporal and multi-sensor cases. In addition to the 3D topographic coordinates, TLS systems also record the backscattered intensity value of each point that provides additional information on the reflectance characteristics of the scanned surface. However, a number of confounding variables, particularly the distance and incidence angle, distort the ability of the original intensity to directly retrieve the target reflectance. This study proposes a new method to model the hemispherical reflectance of natural surfaces from the TLS intensity data by eliminating the effects of incidence angle and distance. The incidence angle effect is corrected by the Oren-Nayar reflectance model which takes individual surface roughness into account whereas the irregular distance effect is eliminated by reference targets without estimating the specific distance-intensity function. The Faro Focus3D 120 terrestrial scanner is utilized in the case study. Six typical natural surfaces are chosen as the experimental objects. Results imply that the proposed method exhibits high accuracy in retrieving reflectance values. The deviation of the retrieved reflectance values from that measured by a spectrometer is approximately 4.29% and the root mean square error (RMSE) is approximately 0.0562.

Using GIS and methods of digital cartography for analyzing battlefield engravings of 17th century

<p style="margin-bottom: 0in; line-height: 100%;"><span style="font-family: Times New Roman,serif;">Iconographic sources depicting Thirty Years’ War battlefields in the Czech lands can be found in historical graphic works printed in the most comprehensive documentary publication of the 17</span><sup><span style="font-family: Times New Roman,serif;">th</span></sup><span style="font-family: Times New Roman,serif;"> century, the Theatrum Europaeum. In this publication, the year 1647 is one of the richest in terms of the number of engravings depicting the course of the war. In addition, the Swedish campaign of the same year left behind the most numerous and best preserved traces in the landscape of the Czech lands. The paper focuses primarily on engravings related to war events at the locations of Cheb, Třebel and Teplá. It presents interim results of interdisciplinary research of these iconographic sources, which involves the tools of spatial analyses, digital terrain modelling and also new possibilities of airborne laser scanning data processing. The main aims of the research, which are also being implemented, are the confirmation of depicted localities and their localization; analyses of the scale and geometrical precision of displayed landscape; estimates of visibility and methods of creating the source materials for engravings; and a detailed comparison with other contemporary or current cartographic sources. </span></p>

MULTIPARAMETER CORRECTION INTENSITY OF TERRESTRIAL LASER SCANNING DATA AS AN INPUT FOR ROCK SURFACE MODELLING

Abstract. A large increase in the creation of 3D models of objects all around us can be observed in the last few years; thanks to the help of the rapid development of new advanced technologies for spatial data collection and robust software tools. A new commercially available airborne laser scanning data in Czech Republic, provided in the form of the Digital terrain model of the fifth generation as irregularly spaced points, enable locating the majority of rock formations. However, the positional and height accuracy of this type of landforms can reach huge errors in some cases. Therefore, it is necessary to start mapping using terrestrial laser scanning with the possibility of adding a point cloud data derived from ground or aerial photogrammetry. Intensity correction and noise removal is usually based on the distance between measured objects and the laser scanner, the incidence angle of the beam or on the radiometric and topographic characteristics of measured objects. This contribution represents the major undesirable effects that affect the quality of acquisition and processing of laser scanning data. Likewise there is introduced solutions to some of these problems.

MULTIPARAMETER CORRECTION INTENSITY OF TERRESTRIAL LASER SCANNING DATA AS AN INPUT FOR ROCK SURFACE MODELLING

A large increase in the creation of 3D models of objects all around us can be observed in the last few years; thanks to the help of the rapid development of new advanced technologies for spatial data collection and robust software tools. A new commercially available airborne laser scanning data in Czech Republic, provided in the form of the Digital terrain model of the fifth generation as irregularly spaced points, enable locating the majority of rock formations. However, the positional and height accuracy of this type of landforms can reach huge errors in some cases. Therefore, it is necessary to start mapping using terrestrial laser scanning with the possibility of adding a point cloud data derived from ground or aerial photogrammetry. Intensity correction and noise removal is usually based on the distance between measured objects and the laser scanner, the incidence angle of the beam or on the radiometric and topographic characteristics of measured objects. This contribution represents the major undesirable effects that affect the quality of acquisition and processing of laser scanning data. Likewise there is introduced solutions to some of these problems.

POTENTIAL OF AIRBORNE IMAGING SPECTROSCOPY AT CZECHGLOBE

Abstract. Ecosystems, their services, structures and functions are affected by complex environmental processes, which are both natural and human-induced and globally changing. In order to understand how ecosystems behave in globally changing environment, it is important to monitor the current status of ecosystems and their structural and functional changes in time and space. An essential tool allowing monitoring of ecosystems is remote sensing (RS). Many ecosystems variables are being translated into a spectral response recorded by RS instruments. It is however important to understand the complexity and synergies of the key ecosystem variables influencing the reflected signal. This can be achieved by analysing high resolution RS data from multiple sources acquired simultaneously from the same platform. Such a system has been recently built at CzechGlobe - Global Change Research Institute (The Czech Academy of Sciences). CzechGlobe has been significantly extending its research infrastructure in the last years, which allows advanced monitoring of ecosystem changes at hierarchical levels spanning from molecules to entire ecosystems. One of the CzechGlobe components is a laboratory of imaging spectroscopy. The laboratory is now operating a new platform for advanced remote sensing observations called FLIS (Flying Laboratory of Imaging Spectroscopy). FLIS consists of an airborne carrier equipped with passive RS systems. The core instrument of FLIS is a hyperspectral imaging system provided by Itres Ltd. The hyperspectral system consists of three spectroradiometers (CASI 1500, SASI 600 and TASI 600) that cover the reflective spectral range from 380 to 2450 nm, as well as the thermal range from 8 to 11.5 μm. The airborne platform is prepared for mounting of full-waveform laser scanner Riegl-Q780 as well, however a laser scanner is not a permanent part of FLIS. In 2014 the installation of the hyperspectral scanners was completed and the first flights were carried out with all sensors. The new hyperspectral imaging system required adaptations in the data pre-processing chain. The established pre-processing chain (radiometric, atmospheric and geometric corrections), which was tailored mainly to the AISA Eagle instrument operated at CzechGlobe since 2004, has been now modified to fit the new system and users needs. Continuous development of the processing chain is now focused mainly on establishing pre-processing of thermal data including emissivity estimation and also on joint processing of hyperspectral and laser scanning data.

POTENTIAL OF AIRBORNE IMAGING SPECTROSCOPY AT CZECHGLOBE

Ecosystems, their services, structures and functions are affected by complex environmental processes, which are both natural and human-induced and globally changing. In order to understand how ecosystems behave in globally changing environment, it is important to monitor the current status of ecosystems and their structural and functional changes in time and space. An essential tool allowing monitoring of ecosystems is remote sensing (RS). Many ecosystems variables are being translated into a spectral response recorded by RS instruments. It is however important to understand the complexity and synergies of the key ecosystem variables influencing the reflected signal. This can be achieved by analysing high resolution RS data from multiple sources acquired simultaneously from the same platform. Such a system has been recently built at CzechGlobe - Global Change Research Institute (The Czech Academy of Sciences). <br><br> CzechGlobe has been significantly extending its research infrastructure in the last years, which allows advanced monitoring of ecosystem changes at hierarchical levels spanning from molecules to entire ecosystems. One of the CzechGlobe components is a laboratory of imaging spectroscopy. The laboratory is now operating a new platform for advanced remote sensing observations called FLIS (Flying Laboratory of Imaging Spectroscopy). FLIS consists of an airborne carrier equipped with passive RS systems. The core instrument of FLIS is a hyperspectral imaging system provided by Itres Ltd. The hyperspectral system consists of three spectroradiometers (CASI 1500, SASI 600 and TASI 600) that cover the reflective spectral range from 380 to 2450 nm, as well as the thermal range from 8 to 11.5 μm. The airborne platform is prepared for mounting of full-waveform laser scanner Riegl-Q780 as well, however a laser scanner is not a permanent part of FLIS. In 2014 the installation of the hyperspectral scanners was completed and the first flights were carried out with all sensors. <br><br> The new hyperspectral imaging system required adaptations in the data pre-processing chain. The established pre-processing chain (radiometric, atmospheric and geometric corrections), which was tailored mainly to the AISA Eagle instrument operated at CzechGlobe since 2004, has been now modified to fit the new system and users needs. Continuous development of the processing chain is now focused mainly on establishing pre-processing of thermal data including emissivity estimation and also on joint processing of hyperspectral and laser scanning data.

AUTOMATIC CREATION OF STRUCTURAL MODELS FROM POINT CLOUD DATA: THE CASE OF MASONRY STRUCTURES

Abstract. One of the fields where 3D modelling has an important role is in the application of such 3D models to structural engineering purposes. The literature shows an intense activity on the conversion of 3D point cloud data to detailed structural models, which has special relevance in masonry structures where geometry plays a key role. In the work presented in this paper, color data (from Intensity attribute) is used to automatically segment masonry structures with the aim of isolating masonry blocks and defining interfaces in an automatic manner using a 2.5D approach. An algorithm for the automatic processing of laser scanning data based on an improved marker-controlled watershed segmentation was proposed and successful results were found. Geometric accuracy and resolution of point cloud are constrained by the scanning instruments, giving accuracy levels reaching a few millimetres in the case of static instruments and few centimetres in the case of mobile systems. In any case, the algorithm is not significantly sensitive to low quality images because acceptable segmentation results were found in cases where blocks could not be visually segmented.

A NEW APPROACH FOR SEGMENTATION-BASED TEXTURING OF LASER SCANNING DATA

Abstract. In recent years, laser scanning systems have been recognized as a fast and accurate technology for the acquisition of high density spatial data. The advent of these systems has reduced the cost and increased the availability of accurate 3D data for mapping, modelling, and monitoring applications. The original laser scanning data does not explicitly provide meaningful information about the characteristics of the scanned surfaces. Therefore, reliable processing procedures are applied for information extraction from these datasets. However, the derived surfaces through laser scanning data processing cannot be effectively interpreted due to the lack of spectral information. To resolve this problem, a new texturing procedure is introduced in this paper to improve the interpretability of laser scanning-derived surfaces using spectral information from overlapping imagery. In this texturing approach, individual planar regions, derived through a laser scanning data segmentation procedure, are textured using the available imagery. This texturing approach, which aims to overcome the computational inefficiency of the previously-developed point-based texturing techniques, is implemented in three steps. In the first step, the visibility of the segmented planar regions in the available imagery is checked and a list of appropriate images for texturing each planar region is established. An occlusion detection procedure is then performed to identify the parts of the segmented regions which are occluding/being occluded by other regions in the field of view of the utilized images. In the second step, visible parts of planar regions are decomposed into parts which should be textured using individual images. Finally, a rendering procedure is performed to texture these parts using available images. Experimental results from real laser scanning dataset and overlapping imagery demonstrate the feasibility of the proposed approach for texturing laser scanning-derived surfaces using images.

An adaptive surface filter for airborne laser scanning point clouds by means of regularization and bending energy

The filtering of point clouds is a ubiquitous task in the processing of airborne laser scanning (ALS) data; however, such filtering processes are difficult because of the complex configuration of the terrain features. The classical filtering algorithms rely on the cautious tuning of parameters to handle various landforms. To address the challenge posed by the bundling of different terrain features into a single dataset and to surmount the sensitivity of the parameters, in this study, we propose an adaptive surface filter (ASF) for the classification of ALS point clouds. Based on the principle that the threshold should vary in accordance to the terrain smoothness, the ASF embeds bending energy, which quantitatively depicts the local terrain structure to self-adapt the filter threshold automatically. The ASF employs a step factor to control the data pyramid scheme in which the processing window sizes are reduced progressively, and the ASF gradually interpolates thin plate spline surfaces toward the ground with regularization to handle noise. Using the progressive densification strategy, regularization and self-adaption, both performance improvement and resilience to parameter tuning are achieved. When tested against the benchmark datasets provided by ISPRS, the ASF performs the best in comparison with all other filtering methods, yielding an average total error of 2.85% when optimized and 3.67% when using the same parameter set.

Предварительная обработка данных мобильного лазерного сканирования в системе IndorCloud

The article gives an idea of the early stages of mobile laser scanning data processing. Before proceeding to the data extraction it is necessary to create an intermediate model — point cloud.

Обработка данных лазерного сканирования

The article gives a practical example of laser scanning data processing to obtain an initial road model, suitable for road maintenance project execution.