Radiometric Calibration of Terrestrial Laser Scanners with External Reference Targets

Kaasalainen, Sanna; Krooks, Anssi; Kukko, Antero; Kaartinen, Harri

doi:10.3390/rs1030144

Cited by 125 publications

(125 citation statements)

References 25 publications

Supporting

Mentioning

123

Contrasting

Order By: Relevance

“…However, many confounding variables distort the capability of the original intensity to directly retrieve the target characteristics, of which the instrumental mechanism, atmospheric conditions, target surface properties, and data acquisition geometry plays a significant and dominant role [17,18]. During one campaign period, instrumental configurations are kept constant and atmospheric attenuation can be ignored.…”

Section: Introductionmentioning

confidence: 99%

Specular Reflection Effects Elimination in Terrestrial Laser Scanning Intensity Data Using Phong Model

Tan

Cheng

2017

Remote Sensing

View full text Add to dashboard Cite

Abstract:The intensity value recorded by terrestrial laser scanning (TLS) systems is significantly influenced by the incidence angle. The incidence angle effect is an object property, which is mainly related to target scattering properties, surface structures, and even some instrumental effects. Most existing models focus on diffuse reflections of rough surfaces and ignore specular reflections, despite that both reflections simultaneously exist in all natural surfaces. Due to the coincidence of the emitter and receiver in TLS, specular reflections can be ignored at large incidence angles. On the contrary, at small incidence angles, TLS detectors can receive a portion of specular reflections. The received specular reflections can trigger highlight phenomenon (hot-spot effects) in the intensity data of the scanned targets, particularly those with a relatively smooth or highly-reflective surface. In this study, a new method that takes diffuse and specular reflections, as well as the instrumental effects into consideration, is proposed to eliminate the specular reflection effects in TLS intensity data. Diffuse reflections and instrumental effects are modeled by a polynomial based on Lambertian reference targets, whereas specular reflections are modeled by the Phong model. The proposed method is tested and validated on different targets scanned by the Faro Focus 3D 120 terrestrial scanner. Results imply that the coefficient of variation of the intensity data from a homogeneous surface is reduced by approximately 38% when specular reflections are considered. Compared with existing methods, the proposed method exhibits good feasibility and high accuracy in eliminating the specular reflection effects for intensity image interpretation and 3D point cloud representation by intensity.

show abstract

Section: Introductionmentioning

confidence: 99%

Specular Reflection Effects Elimination in Terrestrial Laser Scanning Intensity Data Using Phong Model

Tan

Cheng

2017

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Intensities should be calibrated with an external reference if the aim is to develop an effective intensity-based filter. Radiometric calibration would be needed to find a sequence of corrections that convert the raw intensity information into a value proportional or equivalent to target reflectance [31]. Furthermore, and according to the manufacturer's information, the digital value of the intensity also depends on the parameters of the analogue to digital conversion.…”

Section: Discussionmentioning

confidence: 99%

Correction of Erroneous LiDAR Measurements in Artificial Forest Canopy Experimental Setups

Cifuentes

Zande

Salas

et al. 2014

Forests

View full text Add to dashboard Cite

Terrestrial laser scanning (TLS) data makes possible to directly characterize the three-dimensional (3D) distribution of canopy foliage elements. The scanned edges of these elements may result in incorrectly point measurements (i.e., "ghost points") impacting the quality of point cloud data. Therefore, estimation of the ghost points' spatial visibilities, measurement of their characteristics and their removal are essential. In order to quantify the improvements on data quality, a method is developed in this study to efficiently correct for ghost points. Since the occurrence of ghost points is governed by a number of factors, (e.g., scanning resolution and distance, object properties, incident angle); the developed method is based on the analysis of the effects of these factors under controlled conditions where canopy-like objects (i.e., leaves, branches and layers of leaves) were scanned using a continuous-wave TLS system that employs phase-shift technology. Manual extraction of ghost points was done in order to calculate the relative amount of ghost points per scan, or ghost points ratio (gpr). The gpr values were computed in order to: (i) analyze their relationships with variables representing the above factors; and (ii) be used as a reference to evaluate the performance of filters used for extraction of ghost points. The ghost points' occurrence was modeled by fitting regression models using different predictor variables OPEN ACCESSForests 2014, 5 1566 that represent the variables under study. The obtained results indicated that reduced models with three predictors were suitable for gpr estimation in artificial leaves and in artificial branches, with a relative root mean squared error (RMSE) of 4.7% and 3.7%, respectively; while the full model with four predictors was appropriate for artificial layers of leaves, with relative RMSE of 4.5%. According to the statistical analysis, scanning distance was identified as the most important variable for modeling ghost points occurrence. Results indicated that optimized distance-based filters relative to the scanning distance have improved the outcomes in ghost points detection, in comparison to standard filtering criteria. These results suggest that more accurate characterization of forest canopy 3D structures can be achieved by removing ghost points using the new developed method.

show abstract

“…This is expressed by the different shapes of the curves when plotting intensity against range for scanners from different manufacturers, e.g. RIEGL and Optech (Pfeifer et al, 2008), FARO (Kaasalainen et al, 2008) or devices from Leica (Kaasalainen et al, 2011;Kaasalainen et al, 2009). For the present study we use a FARO Focus 3D S120 scanner.…”

Section: Intensity Effects Of Tls Datamentioning

confidence: 99%

“…This extensive procedure requires multiple targets of known and varying reflectivity and is separate from any field measurements. Kaasalainen et al (2011), Kaasalainen et al (2009) and Kaasalainen et al (2008) published a series of studies which also make use of reference targets in order to calibrate intensity. They observe the relationship between intensity and different interactive variables in detail.…”

Section: General Overviewmentioning

confidence: 99%

“…For the present study we use a FARO Focus 3D S120 scanner. In the studies of Kaasalainen et al (2011), Kaasalainen et al (2009) and Kaasalainen et al (2008), a FARO scanner is used as well, but a different model. Since the shape of the intensity-range graphs are very similar to ours (see Figure 5), we assume that similar system-specific alterations are applied.…”

Section: Intensity Effects Of Tls Datamentioning

confidence: 99%

See 1 more Smart Citation

TLS Field Data Based Intensity Correction for Forest Environments

Heinzel

Huber

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:Terrestrial laser scanning (TLS) is increasingly used for forestry applications. Besides the three dimensional point coordinates, the 'intensity' of the reflected signal plays an important role in forestry and vegetation studies. The benefit of the signal intensity is caused by the wavelength of the laser that is within the near infrared (NIR) for most scanners. The NIR is highly indicative for various vegetation characteristics. However, the intensity as recorded by most terrestrial scanners is distorted by both external and scanner specific factors. Since details about system internal alteration of the signal are often unknown to the user, model driven approaches are impractical. On the other hand, existing data driven calibration procedures require laborious acquisition of separate reference datasets or areas of homogenous reflection characteristics from the field data. In order to fill this gap, the present study introduces an approach to correct unwanted intensity variations directly from the point cloud of the field data. The focus is on the variation over range and sensor specific distortions. Instead of an absolute calibration of the values, a relative correction within the dataset is sufficient for most forestry applications. Finally, a method similar to time series detrending is presented with the only pre-condition of a relative equal distribution of forest objects and materials over range. Our test data covers 50 terrestrial scans captured with a FARO Focus 3D S120 scanner using a laser wavelength of 905 nm. Practical tests demonstrate that our correction method removes range and scanner based alterations of the intensity.

show abstract

Radiometric Calibration of Terrestrial Laser Scanners with External Reference Targets

Cited by 125 publications

References 25 publications

Specular Reflection Effects Elimination in Terrestrial Laser Scanning Intensity Data Using Phong Model

Specular Reflection Effects Elimination in Terrestrial Laser Scanning Intensity Data Using Phong Model

Correction of Erroneous LiDAR Measurements in Artificial Forest Canopy Experimental Setups

TLS Field Data Based Intensity Correction for Forest Environments

Contact Info

Product

Resources

About