Correcting Airborne Laser Scanning Intensity Data

Vain, Ants; Kaasalainen, Sanna

doi:10.5772/15026

Cited by 12 publications

(9 citation statements)

References 13 publications

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“…Researchers can choose the above-mentioned algorithms for outlier detection and intensity correction. In this research, the main factor that influenced intensity value was clouds [58], which may cause some points to have a smaller intensity value than their neighboring points. In this case, an extended localminimum method [16] was employed to filter outliers in terms of both elevation and intensity values.…”

Section: B Data Sources and Preparationmentioning

confidence: 99%

“…In addition to the noise from the elevation value, the intensity value may also be influenced by such factors as atmosphere and clouds. Vain and Kaasalainen [58] introduced different factors that may influence the intensity and the methodology for intensity correction. Researchers can choose the above-mentioned algorithms for outlier detection and intensity correction.…”

Section: B Data Sources and Preparationmentioning

confidence: 99%

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An Object-Based Method for Urban Land Cover Classification Using Airborne Lidar Data

Chen

Gao

2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Airborne Lidar (Light detection and ranging) data have been widely used for classifying different land cover types. However, few researchers have conducted urban land cover classification using discrete airborne Lidar data as the sole data source. This research explores the possibility of applying airborne Lidar data to land cover classification in urban areas. The elevation difference and intensity difference between the first and last return, which may not work efficiently in pixelbased classification, were employed as two key attributes at the object level. Since tree objects have a much larger proportion of returns which show the elevation and intensity difference, the two indicators were used to classify the most indistinguishable land cover types, buildings and trees. In addition, height and intensity information were integrated to classify other land cover types. A case study was conducted in the city of Cambridge and eight urban land cover types were classified with an overall accuracy of 93.6%. Each land cover type was classified with an accuracy of between 80% and 100% and among these types, the accuracy of more than 90% for trees and buildings was satisfactory.

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Section: B Data Sources and Preparationmentioning

confidence: 99%

Section: B Data Sources and Preparationmentioning

confidence: 99%

An Object-Based Method for Urban Land Cover Classification Using Airborne Lidar Data

Chen

Gao

2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Several methods have been proposed, including data-and model-driven methods [13], [16] to correct the intensity data of TLS. According to [12], factors that affect the intensity data of ALS are basic physics (such as initial pulse energy, atmospheric loss, range, and angle of incidence), surface properties (such as moisture of the object), and instrumental signal processing [such as automatic gain control (AGC)]. However, for close-range TLS, atmospheric transmission effects can be neglected.…”

Section: Literature Reviewmentioning

confidence: 99%

“…intensity correction of laser scanning systems [12]- [15]. Because the fundamental principles are similar, some of the factors that affect the intensity data of airborne systems also affect terrestrial systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Intensity Correction of Terrestrial Laser Scanning Data by Estimating Laser Transmission Function

Fang

Huang

Zhang

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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Intensity information, recorded by laser scanning, shows great potential for research and applications (e.g., object recognition and registration of images to 3-D models). Multiple studies not only show the significance and possibility of correcting the intensity value but also highlight the existing problems, i.e., that the near-distance and angle-of-incidence effects prevent the practical correction of a terrestrial laser scanner (TLS). In this paper, we explore the near-distance corrections for Z+F Imager5006i, a commercially available coaxial TLS, and propose a corresponding method to correct the range or distance effects on its output intensity data. This method estimates the parameters of customized range-intensity equations using a novel sample data collection design. Using the angle-of-incidence correction method, practical intensity corrections were conducted on TLS point cloud data from white walls and Mogao Grottoes, Dunhuang, China. The results were visualized and show the effectiveness of the proposed method. In addition, we analyzed the new problems that emerge after correction and outline further studies.

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“…The back-scattered intensity decreases inversely proportional to the square of range for a surface with a normal incidence angle Rees, 2013]. Additionally, for a Lambertian scatterer, the back-scattered intensity decreases with the cosine of incidence angle as already observed by Pfeifer et al [2008] and Vain and Kaasalainen [2011]. Then, the correction of intensity is computed with Equation 1 for each point of the six scans:…”

Section: Lidar Intensity Correction Methodsmentioning

confidence: 99%

Geological mapping and fold modeling using Terrestrial Laser Scanning point clouds: application to the Dents-du-Midi limestone massif (Switzerland)

Matasci

Carrea

Abellán

et al. 2015

European Journal of Remote Sensing

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Geological mapping in vertical rock faces is extremely challenging because of access difficulties and limited possibilities of recognition, localization and measurement of features at large distance with traditional tools. Moreover, vertical areas can be of primary interest since they often display good quality outcrops and relevant geological information. This study focuses on the detailed remote identification of rock types and fold structures using intensity values acquired by Terrestrial Laser Scanning. A correction of the intensity is proposed proportional to the square of the range and to the cosine of the incidence angle. Furthermore, two methods of remote lithological mapping in 3D have been developed using a manual and a semi-automatic approach. Both delivered good results that are consistent with the spatial distribution of rock-types and allowed us to generate an accurate 3D lithological map of Dents-du-Midi massif (Valais, Swiss Alps). The bedding orientation near the hinge of a Km scale fold was measured on LiDAR data in order to define the fold axis. Then, the result was used to build a model of the hinge in 3D.

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Correcting Airborne Laser Scanning Intensity Data

Cited by 12 publications

References 13 publications

An Object-Based Method for Urban Land Cover Classification Using Airborne Lidar Data

An Object-Based Method for Urban Land Cover Classification Using Airborne Lidar Data

Intensity Correction of Terrestrial Laser Scanning Data by Estimating Laser Transmission Function

Geological mapping and fold modeling using Terrestrial Laser Scanning point clouds: application to the Dents-du-Midi limestone massif (Switzerland)

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