• Atmosphere
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• v.18 no.4
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• pp.287-297
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• 2008

The vertical profiles and optical properties of Asian dust are investigated using ground-based measurements from 1998 to 2002. Vertical profiles of aerosol extinction coefficient are evaluated using MPL (Micro Pulse Lidar) data. Optical parameters such as aerosol optical thickness ($\tau$), ${\AA}ngstr\ddot{o}m$ exponent ($\alpha$), single scattering albedo ($\omega$), refractive index, and volume size distribution are analyzed with sun/sky radiometer data for the same period. We can separate aerosol vertical profiles into three categories. First category named as 'Asian dust case', which aerosol extinction coefficient is larger than $0.15km^{-1}$ and dust layer exists from surface up to 3-4km. Second category named as 'Elevated aerosol case', which aerosol layer exists between 2 and 6km with 1-2.5km thickness, and extinction coefficient is smaller than $0.15km^{-1}$. Third category named as 'Clear sky case', which aerosol extinction coefficient appears smaller than $0.15km^{-1}$. and shows that diurnal variation of background aerosol in urban area. While optical parameters for first category indicate that $\tau$ and $\alpha$ are $0.63{\pm}0.14$, $0.48{\pm}0.19$, respectively. Also, aerosol volume concentration is increased for range of 1 and $4{\mu}m$, in coarse mode. Optical parameters for second category can be separated into two different types. Optical properties of first type are very close to Asian dust cases. Also, dust reports of source region and backward trajectory analyses assure that these type is much related with Asian dust event. However, optical properties of the other type are similar to those of urban aerosol. For clear sky case, $\tau$ is relatively smaller and $\alpha$ is larger compare with other cases. Each case shows distinct characteristics in aerosol optical parameters.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.212-222
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• 2021

In this study, the flow resistance coefficient was calculated considering the physical properties and distribution characteristics of floodplain vegetation, and the effect of floodplain vegetation distribution on flow characteristics was analyzed by reflecting it in a two-dimensional numerical simulation. The three-dimensional point clouds of vegetation acquired using ground lidar were analyzed to apply floodplain vegetation's physical properties to the existing formula for vegetation flow resistance calculation. The floodplain vegetation distribution in the modeling was divided into locally distributed and fully distributed conditions in the floodplain. As a result of the simulation of the study site, the flow resistance coefficient of floodplain vegetation was found to have a value of about five times or more compared to the flow resistance coefficient of the main channel bed when the design flood occurs based on Manning's n coefficient. Also, it affected the hydraulic characteristics in the main channel and floodplain.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.116-121
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• 2017

In this paper, a Raman spectrometer is designed to detect chemicals contaminating the ground. The system is based on Raman spectroscopy, which is spectral analysis of scattered light from chemicals, induced by a laser. The system consists of a transmitting-optics module with a laser to induce Raman-scattered light from the sample, a receiving-optics module to collect the scattered light, and a spectrograph to separate the collected light into a wavelength spectrum. The telescope, a part of the receiving-optics module, is designed to produce a focal spot in the same position for variable measurement distances using the code V simulator, considering the distance change between the system and the road. The Raman spectra of 12 chemicals on a glass surface and on a concrete sample were measured. Intensity differences between the Raman spectra acquired on a glass surface and on a concrete sample were observed, but the characteristics of the spectra according to the chemicals on them were similar. Additionally, the Raman spectrum of PTFE (polytetrafluoroethylene) was measured at various distances. The measured and simulated optical throughputs were similar. In conclusion, it is confirmed that with this system the Raman spectrum can be measured, irrespective of the distance change.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.1-15
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• 2002

Atmospheric aerosols interact with sunlight and affect the global radiation balance that can cause climate change through direct and indirect radiative forcing. Because of the spatial and temporal uncertainty of aerosols in atmosphere, aerosol characteristics are not considered through GCMs (General Circulation Model). Therefor it is important physical and optical characteristics should be evaluated to assess climate change and radiative effect by atmospheric aerosols. In this study GMS-5 satellite data and surface measurement data were analyzed using a radiative transfer model for the Yellow Sand event of April 7~8, 2000 in order to investigate the atmospheric radiative effects of Yellow Sand aerosols, MODTRAN3 simulation results enable to inform the relation between satellite channel albedo and aerosol optical thickness(AOT). From this relation AOT was retreived from GMS-5 visible channel. The variance observations of satellite images enable remote sensing of the Yellow Sand particles. Back trajectory analysis was performed to track the air mass from the Gobi desert passing through Korean peninsular with high AOT value measured by ground based measurement. The comparison GMS-5 AOT to ground measured RSR aerosol optical depth(AOD) show that for Yellow Sand aerosols, the albedo measured over ocean surfaces can be used to obtain the aerosol optical thickness using appropriate aerosol model within an error of about 10%. In addition, LIDAR network measurements and backward trajectory model showed characteristics and appearance of Yellow Sand during Yellow Sand events. These data will be good supporting for monitoring of Yellow Sand aerosols.