Extraction of Objects from Terrestrial Laser Scans by Integrating Geometry Image and Intensity Data with Demonstration on Trees

Barnea, Shahar; Filin, Sagi

doi:10.3390/rs4010088

Cited by 19 publications

(9 citation statements)

References 29 publications

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“…The main applications include deriving the basic characteristics of a forest stand. To determine the position, the diameter at breast height, the height and the basal area of trees, we can use methods based on finding and measuring cross-sections of standing trees (Bienert et al 2006), cluster analyses, analyses of the geometric properties of the point cloud (Brolly & Király 2009), voxel data structures (Moskal & Zheng 2012), as well as complex approaches which use the distance, intensity and color of points (Barnea & Filin 2012).…”

Section: Introductionmentioning

confidence: 99%

Use of terrestrial laser scanning to evaluate the spatial distribution of soil disturbance by skidding operations

Koreň¹,

Slančík²,

Suchomel³

et al. 2015

iForest

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Section: Introductionmentioning

confidence: 99%

Use of terrestrial laser scanning to evaluate the spatial distribution of soil disturbance by skidding operations

Koreň¹,

Slančík²,

Suchomel³

et al. 2015

iForest

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“…Two main methods of transformation of point clouds to the raster form are described in the literature. The first comprises TLS data processing to the central projection [11] and the second method relies upon conversion of the point cloud to the form of a spherical image [7,8,12,[35][36][37]].…”

Section: Point Cloud Representationmentioning

confidence: 99%

“…Conversion of a point cloud to the form of a spherical image is the most frequently applied method, implemented in many commercial software tools [7,8,12,[35][36][37]. Raw data are used for processing, and generation of raster images with the maximum resolution does not require interpolation of the coordinate values for pixels.…”

Section: A Spherical Imagementioning

confidence: 99%

The Influence of the Cartographic Transformation of TLS Data on the Quality of the Automatic Registration

Markiewicz

Zawieska

2019

Applied Sciences

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This paper discusses the issue of the influence of cartographic Terrestrial Laser Scanning (TLS) data conversion into feature-based automatic registration. Automatic registration of data is a multi-stage process, it is based on original software tools and consists of: (1) Conversion of data to the raster form, (2) register of TLS data in pairs in all possible combinations using the SURF (Speeded Up Robust Features) and FAST (Features from Accelerated Segment Test) algorithms, (3) the quality analysis of relative orientation of processed pairs, and (4) the final bundle adjustment. The following two problems, related to the influence of the spherical image, the orthoimage and the Mercator representation of the point cloud, are discussed: The correctness of the automatic tie points detection and distribution and the influence of the TLS position on the completeness of the registration process and the quality assessment. The majority of popular software applications use manually or semi-automatically determined corresponding points. However, the authors propose an original software tool to address the first issue, which automatically detects and matches corresponding points on each TLS raster representation, utilizing different algorithms (SURF and FAST). To address the second task, the authors present a series of analyses: The time of detection of characteristic points, the percentage of incorrectly detected points and adjusted characteristic points, the number of detected control and check points, the orientation accuracy of control and check points, and the distribution of control and check points. Selection of an appropriate method for the TLS point cloud conversion to the raster form and selection of an appropriate algorithm, considerably influence the completeness of the entire process, and the accuracy of data orientation. The results of the performed experiments show that fully automatic registration of the TLS point clouds in the raster forms is possible; however, it is not possible to propose one, universal form of the point cloud, because a priori knowledge concerning the scanner positions is required. If scanner stations are located close to one another in raster images or in spherical images, Mercator projections are recommended. In the case where fragments of the surface are measured under different angles from different distances and heights of the TLS, orthoimages are suggested.

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“…Besides, terrestrial laser scanning (TLS) has been used for forest biomass assessment in recent years. The application of TLS provides a fast, efficient and accurate means for the determination of basic inventory parameters such as the number and the position of trees, DBH, tree height and crown shape parameters [5][6][7][8][9][10][11][12]. Both measurements from the airborne LiDAR and TLS require ground validation, however, the instruments used to carry out ground truth collection are subject to measurement errors.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Uncertainty of Tree Height and Aboveground Biomass From Terrestrial Laser Scanner and Hypsometer Using Airborne LiDAR Data in Tropical Rainforests

Ojoatre

Zhang

Hussin

et al. 2019

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

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Tree height is one of the key parameters for estimating forest aboveground biomass (AGB). Traditionally, the tree height is measured by hypsometers, which are widely used to validate Terrestrial Laser Scanner (TLS) and Airborne LiDAR (ALS). However, the measurements from hypsometers are subject to huge uncertainties in comparison with TLS and ALS. The error associated with the height measurements propagate into the AGB estimation models, and eventually downgrade the accuracy of estimated AGB and the subsequent carbon stock. In this research, we test the use of Hypsometer, TLS and ALS in a tropical lowland rainforest to measure the height (H) and Diameter at Breast Height (DBH) and take Airborne LiDAR as a benchmark with high accuracy and fidelity in height measurements. The results revealed that, the field height measured by hypsometer underestimated the tree height with RMSE of 3.11, whereas the TLS underestimated height with RMSE of 1.61, when Airborne LiDAR was used as a benchmark to validate the field measurement and TLS. Due to significant differences in derived height measurements, the AGB and carbon stock also varied remarkably with values of 146.33 Mg and 68.77 Mg from field measurements, 170.86 Mg and 80.31 Mg from TLS, 179.85 Mg and 84.53 Mg using the Airborne LiDAR. Considering the Airborne LiDAR measurement as the most accurate, the AGB and carbon stock from field measurement represent 85.55% of total AGB and carbon stock estimation from Airborne LiDAR. Meanwhile, TLS measurements reflect 95.02% of AGB and carbon stock benchmarked with the measurements from Airborne LiDAR data. The results demonstrate the huge uncertainty in height measurement of large trees in comparison with small trees indicated by the significant differences. It was concluded that AGB and carbon stocks are sensitive to height measurement errors derived from various methods for measuring the tree height, the size of trees as large trees are difficult to

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Extraction of Objects from Terrestrial Laser Scans by Integrating Geometry Image and Intensity Data with Demonstration on Trees

Cited by 19 publications

References 29 publications

Use of terrestrial laser scanning to evaluate the spatial distribution of soil disturbance by skidding operations

Use of terrestrial laser scanning to evaluate the spatial distribution of soil disturbance by skidding operations

The Influence of the Cartographic Transformation of TLS Data on the Quality of the Automatic Registration

Assessing the Uncertainty of Tree Height and Aboveground Biomass From Terrestrial Laser Scanner and Hypsometer Using Airborne LiDAR Data in Tropical Rainforests

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