scholarly journals MULTI-TARGET DETECTION FROM FULL-WAVEFORM AIRBORNE LASER SCANNER USING PHD FILTER

2016 ◽  
Vol XLI-B5 ◽  
pp. 647-652
Author(s):  
T. Fuse ◽  
D. Hiramatsu ◽  
W. Nakanishi
Keyword(s):  
Target Detection ◽  
A Priori ◽  
Laser Scanner ◽  
Real Data ◽  
Bayesian Filtering ◽  
Probability Hypothesis Density ◽  
Airborne Laser Scanner ◽  
Full Waveform ◽  
Airborne Laser ◽  
A New Technique

We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD) filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions simultaneously. PHD filter overcomes some limitations of conventional Gaussian decomposition method; PHD filter doesn’t require a priori knowledge on the number of targets, assumption of parametric form of the intensity distribution. In addition, it can take a similarity between successive irradiations into account by modelling relative positions of the same targets spatially. Firstly we explain PHD filter and particle filter implementation to it. Secondly we formulate the multi-target detection problem on PHD filter by modelling components and parameters within it. At last we conducted the experiment on real data of forest and vegetation, and confirmed its ability and accuracy.

scholarly journals MULTI-TARGET DETECTION FROM FULL-WAVEFORM AIRBORNE LASER SCANNER USING PHD FILTER

2016 ◽  
Vol XLI-B5 ◽  
pp. 647-652
Author(s):  
T. Fuse ◽  
D. Hiramatsu ◽  
W. Nakanishi
Keyword(s):  
Target Detection ◽  
A Priori ◽  
Laser Scanner ◽  
Real Data ◽  
Bayesian Filtering ◽  
Probability Hypothesis Density ◽  
Airborne Laser Scanner ◽  
Full Waveform ◽  
Airborne Laser ◽  
A New Technique

We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD) filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions simultaneously. PHD filter overcomes some limitations of conventional Gaussian decomposition method; PHD filter doesn’t require a priori knowledge on the number of targets, assumption of parametric form of the intensity distribution. In addition, it can take a similarity between successive irradiations into account by modelling relative positions of the same targets spatially. Firstly we explain PHD filter and particle filter implementation to it. Secondly we formulate the multi-target detection problem on PHD filter by modelling components and parameters within it. At last we conducted the experiment on real data of forest and vegetation, and confirmed its ability and accuracy.

On analysis and visualization of full-waveform airborne laser scanner data

2005 ◽  
Author(s):  
Ulf Soederman ◽  
Asa Persson ◽  
Johanna Toepel ◽  
Simon Ahlberg
Keyword(s):  
Laser Scanner ◽  
Scanner Data ◽  
Airborne Laser Scanner ◽  
Full Waveform ◽  
Airborne Laser

scholarly journals ON GROUND SURFACE EXTRACTION USING FULL-WAVEFORM AIRBORNE LASER SCANNER FOR CIM

2015 ◽  
Vol XL-4/W5 ◽  
pp. 159-163
Author(s):  
K. Nakano ◽  
H. Chikatsu
Keyword(s):  
Spatial Information ◽  
Laser Scanner ◽  
Ground Surface ◽  
Positioning Systems ◽  
Surface Extraction ◽  
Airborne Laser Scanner ◽  
Full Waveform ◽  
Airborne Laser ◽  
Laser Scanners ◽  
Forested Areas

Satellite positioning systems such as GPS and GLONASS have created significant changes not only in terms of spatial information but also in the construction industry. It is possible to execute a suitable construction plan by using a computerized intelligent construction. Therefore, an accurate estimate of the amount of earthwork is important for operating heavy equipment, and measurement of ground surface with high accuracy is required. A full-waveform airborne laser scanner is expected to be capable of improving the accuracy of ground surface extraction for forested areas, in contrast to discrete airborne laser scanners, as technological innovation. For forested areas, fundamental studies for construction information management (CIM) were conducted to extract ground surface using full-waveform airborne laser scanners based on waveform information.

scholarly journals REFERENCE VALUE PROVISION SCHEMES FOR ATTENUATION CORRECTION OF FULL-WAVEFORM AIRBORNE LASER SCANNER DATA

2015 ◽  
Vol II-3/W5 ◽  
pp. 65-72 ◽  
Author(s):  
K. Richter ◽  
R. Blaskow ◽  
N. Stelling ◽  
H.-G. Maas
Keyword(s):  
Laser Pulse ◽  
Attenuation Correction ◽  
Laser Scanner ◽  
Reference Value ◽  
Space Representation ◽  
Airborne Laser Scanner ◽  
Full Waveform ◽  
Airborne Laser ◽  
Lower Amplitude ◽  
Pulse Echo

The characterization of the vertical forest structure is highly relevant for ecological research and for better understanding forest ecosystems. Full-waveform airborne laser scanner systems providing a complete time-resolved digitization of every laser pulse echo may deliver very valuable information on the biophysical structure in forest stands. To exploit the great potential offered by full-waveform airborne laser scanning data, the development of suitable voxel based data analysis methods is straightforward. Beyond extracting additional 3D points, it is very promising to derive voxel attributes from the digitized waveform directly. However, the ’history’ of each laser pulse echo is characterized by attenuation effects caused by reflections in higher regions of the crown. As a result, the received waveform signals within the canopy have a lower amplitude than it would be observed for an identical structure without the previous canopy structure interactions (Romanczyk et al., 2012). <br><br> To achieve a radiometrically correct voxel space representation, the loss of signal strength caused by partial reflections on the path of a laser pulse through the canopy has to be compensated by applying suitable attenuation correction models. The basic idea of the correction procedure is to enhance the waveform intensity values in lower parts of the canopy for portions of the pulse intensity, which have been reflected in higher parts of the canopy. To estimate the enhancement factor an appropriate reference value has to be derived from the data itself. Based on pulse history correction schemes presented in previous publications, the paper will discuss several approaches for reference value estimation. Furthermore, the results of experiments with two different data sets (leaf-on/leaf-off) are presented.

Classification of vegetation in an open landscape using full-waveform airborne laser scanner data

2015 ◽  
Vol 41 ◽  
pp. 76-87 ◽  
Author(s):  
Cici Alexander ◽  
Balázs Deák ◽  
Adam Kania ◽  
Werner Mücke ◽  
Hermann Heilmeier
Keyword(s):  
Laser Scanner ◽  
Scanner Data ◽  
Airborne Laser Scanner ◽  
Full Waveform ◽  
Airborne Laser

scholarly journals Estimation of Vegetation-Induced Flow Resistance for Hydraulic Computations Using Airborne Laser Scanning Data

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1864
Author(s):  
Peter Mewis
Keyword(s):  
Laser Scanning ◽  
Flow Resistance ◽  
Laser Scanner ◽  
Airborne Laser Scanning ◽  
Density Parameter ◽  
Vegetation Density ◽  
Airborne Laser Scanner ◽  
Airborne Laser ◽  
Bed Roughness ◽  
Available Information

The effect of vegetation in hydraulic computations can be significant. This effect is important for flood computations. Today, the necessary terrain information for flood computations is obtained by airborne laser scanning techniques. The quality and density of the airborne laser scanning information allows for more extensive use of these data in flow computations. In this paper, known methods are improved and combined into a new simple and objective procedure to estimate the hydraulic resistance of vegetation on the flow in the field. State-of-the-art airborne laser scanner information is explored to estimate the vegetation density. The laser scanning information provides the base for the calculation of the vegetation density parameter ωp using the Beer–Lambert law. In a second step, the vegetation density is employed in a flow model to appropriately account for vegetation resistance. The use of this vegetation parameter is superior to the common method of accounting for the vegetation resistance in the bed resistance parameter for bed roughness. The proposed procedure utilizes newly available information and is demonstrated in an example. The obtained values fit very well with the values obtained in the literature. Moreover, the obtained information is very detailed. In the results, the effect of vegetation is estimated objectively without the assignment of typical values. Moreover, a more structured flow field is computed with the flood around denser vegetation, such as groups of bushes. A further thorough study based on observed flow resistance is needed.

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