• Spatial Information Research
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• v.16 no.1
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• pp.19-32
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• 2008

Usually in South Korea, land cover type and topographic undulation are frequently changed even in a narrow area. However, most of researches using aerial LIDAR(LIght Detection And Ranging) data in abroad had been acquired in the study areas to be changed infrequently. This research was performed to explore reconstruction methodologies of 3D surface models considering the distribution of land cover type and topographic undulation. Composed of variously undulatory forests, rocky river beds and man-made land cover such as streets, trees, buildings, parking lots and so on, an area was selected for the research. First of all, the area was divided into three zones based on land cover type and topographic undulation using its aerial ortho-photo. Then, aerial LIDAR data was clipped by each zone and different 3D modeling processes were applied to each clipped data before integration of each models and reconstruction of overall model. These kinds of processes might be effectively applied to landscape management, forest inventory and digital map composition. Besides, they would be useful to resolve less- or over-extracted problems caused by simple rectangle zoning when an usual data processing of aerial LIDAR.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.23-31
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• 2020

It is essential to estimate the vehicle localization for an autonomous safety driving. In particular, since LIDAR provides precise scan data, many studies carried out to estimate the vehicle localization using LIDAR and pre-generated map. The road marking always exists on the road because of provides driving information. Therefore, it is often used for map information. In this paper, we propose to generate the Gaussian mixture map based on road-marking information and localization method using this map. Generally, the probability distributions map stores the single Gaussian distribution for each grid. However, single resolution probability distributions map cannot express complex shapes when grid resolution is large. In addition, when grid resolution is small, map size is bigger and process time is longer. Therefore, it is difficult to apply the road marking. On the other hand, Gaussian mixture distribution can effectively express the road marking by several probability distributions. In this paper, we generate Gaussian mixture map and perform vehicle localization using Gaussian mixture map. Localization performance is analyzed through the experimental result.

• ETRI Journal
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• v.33 no.4
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• pp.547-557
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• 2011

This study presents an approach for extracting boundaries of various buildings, which have concave boundaries, inner yards, non-right-angled corners, and nonlinear edges. The approach comprises four steps: building point segmentation, boundary tracing, boundary grouping, and regularization. In the second and third steps, conventional algorithms are improved for more accurate boundary extraction, and in the final step, a new algorithm is presented to extract nonlinear edges. The unique characteristics of airborne light detection and ranging (LIDAR) data are considered in some steps. The performance and practicality of the presented algorithm were evaluated for buildings of various shapes, and the average omission and commission error of building polygon areas were 0.038 and 0.033, respectively.

• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.185-189
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• 2010

A micro-pulse LIDAR system (MPL) was employed to measure the aerosol over Pudong, Shanghai from July 2008 to January 2009. Based on Fernald method, aerosol optical variables such as extinction coefficient were retrieved and analyzed. Results show that aerosol exists mainly in low layers; aerosol loading reaches its maximum in the afternoon, and then decreases with time until its minimum at night. Most of the aerosol concentrates in the layer below 3 km, and optical extinction coefficient in the layer below 2 km contributes 84.25% of that below 6 km. Two extinction coefficient peaks appear in the near surface layer up to 500 m and in the level around 1000 m. Aerosol extinction coefficient shows a seasonal downward trend from summer to winter.

• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.178-184
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• 2010

We present linear particle depolarization ratios (LPDRs) retrieved from measurements with an AERONET Sun photometer at the Gwangju Institute of Science and Technology (GIST), Korea ($35.10^{/circ}N$, $126.53^{\circ}E$) between 19 October and 3 November 2009. The Sun photometer data were classified into three categories according to ${\AA}$ngstr$\ddot{o}$ exponent and size distribution: 1) pure Asian dust (19 October 2009), 2) Asian dust mixed with urban pollution observed in the period from 20-26 October 2009, and 3) clean conditions (3 November). We show that the LPDRs can be used to distinguish among Asian dust, mixed aerosol, and non-Asian dust in the atmosphere. The mean LPDR of the pure Asian dust case is 23 %. Mean LPDRs are 13 % for the mixed case. The lowest mean LPDR is 6 % in the clean case. We compare our results to vertically resolved LPDRs (at 532 nm) measured by a Raman LIDAR system at the same site. In most cases, we find good agreement between LPDRs derived with Sun photometer and measured by LIDAR.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.301-306
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• 2010

Recently GIS is not only displaying and servicing data on the 2D, but also is changing rapidly to display and service 3D data. Also 3D related technology is developing actively. For display of 3D data, terrain DTM has become a basis. Generally, to acquire DTM, users are using LIDAR data or digital map's contour line. However, if using these data for producing DTM, users need to additional cost and data lead time. And hard to update terrain data. For possibility of solving these problem, this study did DTM extraction with automatic matching for aerial photograph, and analysed the result with measurement of Orthometric height and excuted accuracy through DTM(which extracted from digital photogrammetric technique). As a result, we can get a high accuracy of RMSE (0.215m).

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.43-58
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• 1998

The Kwinana Shoreline Fumigation Experiment (KSFE) took place at Fremantle, WA, Australia between January 23 and February 8, 1995. The CSIRO DAR LIDAR measured plume sections from near the Kwinana Power Station (KPS) stacks to up to about 5 km downstream. It also measured boundary layer aerosols and the structure of the boundary layer on some occasions. Both stages A and C of KPS were used as tracers at different times. The heart of the LIDAR system is a Neodymium-doped Yttrium-aluminum-garnet (Nd:YAG) laser operating at a fundamental wavelength of 1064 nm, with harmonics of 532 nm and 355 nm. For these experiments the third harmonic was used because the UV wavelength at 355 nm is eye safe beyond about 50 m. The laser fires a pulse of light 6 ns in duration (about 1.8 m long) and with an energy (at the third harmonic) of about 70 mJ. This pulse subsequently scattered and absorbed by both air molecules and particles in the atmosphere. A small fraction of the laser beam is scattered back to the LIDAR, collected by a telescope and detected by a photo-multiplier tube. The intensity of the signal as a function of time is a measure of the particle concentration as a function of distance along the line of the laser shot. The smoke plume was clearly identifiable in the scans both before and after fumigation in the thermal internal boundary layer (TIBL). Both power station plumes were detected. Over the 9 days of operation, 1,568 plumes scans (214 series) were performed. Essentially all of these will provide instantaneous plume heights and widths, and there are many periods of continuous operation over several hours when it should be possible to compile hourly average plume statistics as well. The results of four days LIDAR observations of the dispersion of smoke plume in the TIBL at a coastal site are presented for the case of stages A and C.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.158-164
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• 2015

Lane detection is one of the key parts among autonomous vehicle technologies because lane keeping and path planning are based on lane detection. Camera is used for lane detection but there are severe limitations such as narrow field of view and effect of illumination. On the other hands, Lidar sensor has the merits of having large field of view and being little influenced by illumination because it uses intensity information. Existing researches that use methods such as Hough transform, histogram hardly handle multiple lanes in the co-occuring situation of lanes and road marking. In this paper, we propose a method based on RANSAC and regularization which provides a stable and precise detection result in the co-occuring situation of lanes and road marking in highway scenarios. This is performed by precise lane point extraction using circular model RANSAC and regularization aided least square fitting. Through quantitative evaluation, we verify that the proposed algorithm is capable of multi lane detection with high accuracy in real-time on our own acquired road data.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1681-1690
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• 2020

A scanning lidar system has been developed. The system has two wavelength observation channels of 532 and 1064 nm and is capable of 360-degree horizontal scanning observation. In addition, an analysis method that can classify the measured particle as an indicator of coarse-mode particle (PM2.5-10) and an indicator of fine-mode particles (PM2.5) and calculate the mass concentration of each has been developed by using the backscatter coefficient at two wavelengths. It was applied to the data calculated by observation. The mass concentrations of PM10 and PM2.5, which showed a distribution of 22-110 ㎍/㎥ and 7-78 ㎍/㎥, respectively, were successfully calculated in the Ulsan Onsan Industrial Complex using the developed scanning lidar system. The analyzed results showed similar values to the mass concentrations measured on the ground around the lidar observation area, and it was confirmed that high concentrations of 80-110 ㎍/㎥ and 60-78 ㎍/㎥ were measured at points discharged from factories, respectively.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.265-274
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• 2006

Extracting ground points is the kernel of DTM generation being considered as one of the most popular LIDAR applications. The previous extraction approaches can be mostly characterized as a point based approach, which sequentially examines every individual point to determine whether it is measured from ground surfaces. The number of examinations to be performed is then equivalent to the number of points. Particularly in a large set, the heavy computational requirement associated with the examinations is obviously an obstacle to employing more sophisticated criteria for the examination. To reduce the number of entities to be examined and produce more robust results, we developed an approach based on features rather than points, where a feature indicates an entity constructed by grouping some points. In the proposed approach, we first generate a set of features by organizing points into surface patches and grouping the patches into surface clusters. Among these features, we then attempt to identify the ground features with the criteria based on the attributes of the features. The points grouped into these identified features are labeled ground points, being used for DTM generation afterward. The Proposed approach was applied to many real airborne LIDAR data sets. The analysis on the results strongly supports the prominent performance of the proposed approach in terms of not only the computational requirement but also the quality of the DTM.