Special Issue "Terrestrial Laser Scanning"
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A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 May 2011)
Special Issue Editor
Guest Editor
Dr. Derek Lichti
Department of Geomatics Engineering, Undergraduate Studies, Centre for Bioengineering Research and Education, The University of Calgary, Canada
Website: http://www.ucalgary.ca/lichti/
E-Mail: ddlichti@ucalgary.ca
Interests: terrestrial laser scanner calibration; automated 3D point cloud registration; feature extraction from laser scanner point cloud data; 3D range camera imaging; X-ray and optical imaging for bioengineering applications
Special Issue Information
Dear Colleagues,
Terrestrial laser scanning (TLS) is a ground-based, active imaging method that rapidly acquires accurate, dense 3D point clouds of object surfaces by laser rangefinding. The number and variety of remote sensing applications of TLS instruments continues to increase. Static systems operated from atop a surveying tripod are commonly employed for the as-built documentation of industrial plants, the recording of cultural heritage sites, the measurement of natural processes such as sand transport and tree defoliation, structural deformation measurement and the measurement of the human body. Mobile systems comprising integrated laser scanning and platform georeferencing technologies are deployed on road vehicles, rail cars or small water vessels for kinematic data capture. The utilisation and number mobile laser scanning systems have risen dramatically in recent years for rapid corridor mapping and the compilation of asset inventories.
Prospective authors are invited to contribute to this Special Issue of Remote Sensing by submitting an original manuscript of their latest research results in terrestrial laser scanning. Contributions may be from, but not limited to:
- scanner system modelling, calibration, performance evaluation and validation
- algorithms for automated point cloud registration
- techniques for the fusion of TLS data with that of other sensors
- automated feature extraction and object recognition
- mobile terrestrial scanning system developments
- novel applications of static or mobile terrestrial laser scanning
Dr. Derek Lichti
Guest Editor
Submission
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 800 CHF (Swiss Francs).
Keywords
- terrestrial laser scanning
- point clouds
- calibration
- registration
- fusion
- object recognition
- mobile scanning
Published Papers (10 papers)
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Received: 3 December 2010; in revised form: 4 January 2011 / Accepted: 7 January 2011 / Published: 14 January 2011
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Abstract: An empirical approach is proposed in order to evaluate the largest spot spacing allowing the appropriate resolution to recognize the required surface details in a terrestrial laser scanner (TLS) survey. The suitable combination of laser beam divergence and spot spacing for the effective scanning angular resolution has been studied by numerical simulation experiments with an artificial target taken from distances between 25 m and 100 m, and observations of real surfaces. The tests have been performed by using the Optech ILRIS-3D instrument. Results show that the discrimination of elements smaller than a third of the beam divergence (D) is not possible and that the ratio between the used spot-spacing (ss) and the element size (TS) is linearly related to the acquisition range. The zero and first order parameters of this linear trend are computed and used to solve for the maximum efficient ss at defined ranges for a defined TS. Despite the fact that the parameters are obtained for the Optech ILRIS-3D scanner case, and depend on its specific technical data and performances, the proposed method has general validity and it can be used to estimate the corresponding parameters for other instruments. The obtained results allow the optimization of a TLS survey in terms of acquisition time and surface details recognition.
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Received: 10 February 2011; in revised form: 5 March 2011 / Accepted: 8 March 2011 / Published: 14 March 2011
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Abstract: The temporal stability and static calibration and analysis of the Velodyne HDL‑64E S2 scanning LiDAR system is discussed and analyzed. The mathematical model for measurements for the HDL-64E S2 scanner is updated to include misalignments between the angular encoder and scanner axis of rotation, which are found to be a marginally significant source of error. It is reported that the horizontal and vertical laser offsets cannot reliably be obtained with the current calibration model due to their high correlation with the horizontal and vertical offsets. By analyzing observations from two separate HDL-64E S2 scanners it was found that the temporal stability of the horizontal angle offset is near the quantization level of the encoder, but the vertical angular offset, distance offset and distance scale are slightly larger than expected. This is felt to be due to long term variations in the scanner range, whose root cause is as of yet unidentified. Nevertheless, a temporally averaged calibration dataset for each of the scanners resulted in a 25% improvement in the 3D planar misclosure residual RMSE over the standard factory calibration model.
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Received: 10 February 2011; in revised form: 7 March 2011 / Accepted: 8 March 2011 / Published: 17 March 2011
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Abstract: Laser measurements have been used in a fluvial context since 1984, but the change detection possibilities of mobile laser scanning (MLS) for riverine topography have been lacking. This paper demonstrates the capability of MLS in erosion change mapping on a test site located in a 58 km-long tributary of the River Tenojoki (Tana) in the sub-arctic. We used point bars and river banks as example cases, which were measured with the mobile laser scanner ROAMER mounted on a boat and on a cart. Static terrestrial laser scanner data were used as reference and we exploited a difference elevation model technique for describing erosion and deposition areas. The measurements were based on data acquisitions during the late summer in 2008 and 2009. The coefficient of determination (R2) of 0.93 and a standard deviation of error 3.4 cm were obtained as metrics for change mapping based on MLS. The root mean square error (RMSE) of MLS‑based digital elevation models (DEM) for non-vegetated point bars ranged between 2.3 and 7.6 cm after correction of the systematic error. For densely vegetated bank areas, the ground point determination was more difficult resulting in an RMSE between 15.7 and 28.4 cm.
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Received: 1 February 2011; in revised form: 18 March 2011 / Accepted: 21 March 2011 / Published: 29 March 2011
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Abstract: In recent years there has been an increasing demand among home owners for cost effective sustainable energy production such as solar energy to provide heating and electricity. A lot of research has focused on the assessment of the incoming solar radiation on roof planes acquired by, e.g., Airborne Laser Scanning (ALS). However, solar panels can also be mounted on building facades in order to increase renewable energy supply. Due to limited reflections of points from vertical walls, ALS data is not suitable to perform solar potential assessment of vertical building facades. This paper focuses on a new method for automatic solar radiation modeling of facades acquired by Mobile Laser Scanning (MLS) and uses the full 3D information of the point cloud for both the extraction of vertical walls covered by the survey and solar potential analysis. Furthermore, a new method isintroduced determining the interior and exterior face, respectively, of each detected wall in order to calculate its slope and aspect angles that are of crucial importance for solar potential assessment. Shadowing effects of nearby objects are considered by computing the 3D horizon of each point of a facade segment within the 3D point cloud.
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Received: 28 April 2011; in revised form: 16 June 2011 / Accepted: 17 June 2011 / Published: 27 June 2011
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Abstract: This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR systems. Portable LiDAR height profiles and derived metrics and indices (e.g., canopy cover, canopy height) were compared among plots with different fire frequency and fire season treatments within secondary forest and old growth plots. The treatments consisted of transitional season fire with four different return intervals: 1-yr, 2-yr, 3-yr fire return intervals, and fire suppressed plots. The remaining secondary plots were treated using a 2-yr late dormant season fire cycle. The old growth plots were treated using a 2-yr growing season fire cycle. Airborne and portable LiDAR derived canopy cover were consistent throughout the plots, with significantly higher canopy cover values found in 3-yr and fire suppressed plots. Portable LiDAR height profile and metrics presented a higher sensitivity in capturing subcanopy elements than the airborne system, particularly in dense canopy plots. The 3-dimensional structures of the secondary plots with varying fire return intervals were dramatically different to old-growth plots, where a symmetrical distribution with clear recruitment was visible. Portable LiDAR, even though limited to finer spatial scales and specific biases, is a low-cost investment with clear value for the management of forest canopy structure.
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Received: 25 June 2011; in revised form: 29 July 2011 / Accepted: 8 August 2011 / Published: 16 August 2011
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Abstract: Terrestrial LiDAR provides many disciplines with an effective and efficient means of producing realistic three-dimensional models of real world objects. With the advent of mobile terrestrial LiDAR, this ability has been expanded to include the rapid collection of three-dimensional models of large urban scenes. For all its usefulness, it does have drawbacks. One of the major problems faced by the LiDAR industry today is the automatic removal of outlying data points from LiDAR point clouds. This paper discusses the development and combined implementation of two methods of performing outlier detection in georeferenced point clouds. These methods made use of the raw data available from most time-of-flight mobile terrestrial LiDAR scanners in both the temporal and spatial domains. The first method involved a moving fixed interval smoother derived from the well-known position velocity acceleration Kalman Filter. The second method fitted a quadratic curved surface to sections of LiDAR data. The combined use of these routines is discussed through examples with real LiDAR data.
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Received: 1 July 2011; in revised form: 11 August 2011 / Accepted: 15 August 2011 / Published: 25 August 2011
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Abstract: A new 3D acquisition and processing procedure to map RGB, thermal IR and near infrared images (NIR) on a detailed 3D model of a building is presented. The combination and fusion of different data sources allows the generation of 3D thermal data useful for different purposes such as localization, visualization, and analysis of anomalies in contemporary architecture. The classic approach, which is currently used to map IR images on 3D models, is based on the direct registration of each single image by using space resection or homography. This approach is largely time consuming and in many cases suffers from poor object texture. To overcome these drawbacks, a “bi-camera” system coupling a thermal IR camera to a RGB camera has been setup. The second sensor is used to orient the “bi-camera” through a photogrammetric network also including free-handled camera stations to strengthen the block geometry. In many cases the bundle adjustment can be executed through a procedure for automatic extraction of tie points. Terrestrial laser scanning is adopted to retrieve the 3D model building. The integration of a low-cost NIR camera accumulates further radiometric information on the final 3D model. The use of such a sensor has not been exploited until now to assess the conservation state of buildings. Here some interesting findings from this kind of analysis are reported. The paper shows the methodology and its experimental application to a couple of buildings in the main Campus of Politecnico di Milano University, where IR thermography has previously been carried out for conservation and maintenance purposes.
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Received: 1 July 2011; in revised form: 28 July 2011 / Accepted: 23 August 2011 / Published: 16 September 2011
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Abstract: The real and imaginary parts are proposed as an alternative to the usual Polar representation of complex-valued images. It is proven that the transformation from Polar to Cartesian representation contributes to decreased mutual information, and hence to greater distinctiveness. The Complex Scale-Invariant Feature Transform (ℂSIFT) detects distinctive features in complex-valued images. An evaluation method for estimating the uniformity of feature distributions in complex-valued images derived from intensity-range images is proposed. In order to experimentally evaluate the proposed methodology on intensity-range images, three different kinds of active sensing systems were used: Range Imaging, Laser Scanning, and Structured Light Projection devices (PMD CamCube 2.0, Z+F IMAGER 5003, Microsoft Kinect).
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Received: 23 August 2011; in revised form: 3 October 2011 / Accepted: 12 October 2011 / Published: 20 October 2011
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Abstract: The intensity information from terrestrial laser scanners (TLS) has become an important object of study in recent years, and there are an increasing number of applications that would benefit from the addition of calibrated intensity data to the topographic information. In this paper, we study the range and incidence angle effects on the intensity measurements and search for practical correction methods for different TLS instruments and targets. We find that the range (distance) effect is strongly dominated by instrumental factors, whereas the incidence angle effect is mainly caused by the target surface properties. Correction for both effects is possible, but more studies are needed for physical interpretation and more efficient use of intensity data for target characterization.
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Received: 29 November 2011; in revised form: 29 December 2011 / Accepted: 29 December 2011 / Published: 5 January 2012
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Abstract: Terrestrial laser scanning is becoming a standard for 3D modeling of complex scenes. Results of the scan contain detailed geometric information about the scene; however, the lack of semantic details still constitutes a gap in ensuring this data is usable for mapping. This paper proposes a framework for recognition of objects in laser scans; aiming to utilize all the available information, range, intensity and color information integrated into the extraction framework. Instead of using the 3D point cloud, which is complex to process since it lacks an inherent neighborhood structure, we propose a polar representation which facilitates low-level image processing tasks, e.g., segmentation and texture modeling. Using attributes of each segment, a feature space analysis is used to classify segments into objects. This process is followed by a fine-tuning stage based on graph-cut algorithm, which considers the 3D nature of the data. The proposed algorithm is demonstrated on tree extraction and tested on scans containing complex objects in addition to trees. Results show a very high detection level and thereby the feasibility of the proposed framework.
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Last update: 5 April 2011
