• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.403-410
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• 2011

Consistent observation with high temporal and spatial resolution is required for an efficient monitoring of coastal environments. Remote monitoring system installed on the ground is capable of simultaneous observation of wide coastal area and consistent observation with high frequency, which a small number of in-situ measurements cannot manage. This paper studies two typical ground based coastal monitoring system, marine radar and camera system. Marine radar can produce time series of frequency spectrum by integrating wave number spectrum calculated from spatial and temporal variation of waves in the radar image. The time averaged radar images of waves can analyze wave breaking zone, rip currents and location of littoral bars. Camera system can observe temporal variation of foam generation originated from coastal contamination as well as shoreline changes. By extracting the part of foams from rectified images, quantitative analysis of temporal foam variation can be done. By using the two above systems of different characteristics, synergetic benefit can be achieved.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.87-97
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we proposed to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collected two new video datasets, and proposed a new deep learning architecture named Temporal and Spatial Segment Networks (TSSN) for rainfall depth recognition. Under TSSN, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. Also, the proposed TSSN architecture outperforms other architectures implemented in this paper.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1041-1047
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• 2023

Temporal bone CT, which is a high-resolution CT, uses a high tube voltage and a thin section thickness, so the scan dose is higher than that of adjacent areas. Accordingly, we applied changes to the reconstruction algorithm among the test conditions to find an algorithm with excellent sensitivity to lesions while reducing the test dose, and investigated its significance and the possibility of providing basic clinical data. As a result, when the tube voltage was lowered to 100 kVp and applied, the dose was reduced by about 35.6%, and when the definition algorithm was applied to the raw data acquired at 100 kVp, the SNR and CNR were excellent, and a statistically significant difference was shown when compared to other algorithms(p<0.05). And as a result of comparing structural similarity, the SSIM index was analyzed as 0.776, 0.813, and 0.741 for each ROI. Therefore, we believe that applying algorithm changes to temporal bone CT scans can partially reduce the dose generated from CT scans and are very meaningful in terms of basic clinical data.

• Atmosphere
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• v.33 no.5
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• pp.441-456
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• 2023

The mobile observation method, in which a meteorological drone observes while ascending, can observe the vertical profile of wind at 1 m-interval. In addition, since continuous flights are possible at time intervals of less than 30 minutes, high-resolution observation data can be obtained both spatially and temporally. In this study, we verify the accuracy of mobile observation data from meteorological drone (drone) and fill the spatio-temporal observation gaps in the lower atmosphere. To verify the accuracy of mobile observation data observed by drone, it was compared with rawinsonde observation data. The correlation coefficients between two equipment for a wind speed and direction were 0.89 and 0.91, and the root mean square errors were 0.7 m s^-1 and 20.93°. Therefore, it was judged that the drone was suitable for observing vertical profile of the wind using mobile observation method. In addition, we attempted to resolve the observation gaps in the lower atmosphere. First, the vertical observation gaps of the wind profiler between the ground and the 150 m altitude could be resolved by wind observation data using the drone. Secondly, the temporal observation gaps between 3-hour interval in the rawinsonde was resolved through a drone observation case conducted in Taean-gun, Chungcheongnam-do on October 13, 2022. In this case, the drone mobile observation data every 30-minute intervals could observe the low-level jet more detail than the rawinsonde observation data. These results show that the mobile observation data of the drone can be used to fill the spatio-temporal observation gaps in the lower atmosphere.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.149-158
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• 2017

Fine temporal and spatial resolution of image data are necessary to monitor the phenology of vegetation. However, there is no single sensor provides fine temporal and spatial resolution. For solve this limitation, researches on spatiotemporal data fusion methods are being conducted. Among them, FSDAF (Flexible spatiotemporal data fusion) can fuse each band in high accuracy.In thisstudy, we applied MODIS NDVI and Landsat NDVI to enhance time resolution of NDVI based on FSDAF algorithm. Then we proposed the possibility of utilization in vegetation phenology monitoring. As a result of FSDAF method, the predicted NDVI from January to December well reflect the seasonal characteristics of broadleaf forest, evergreen forest and farmland. The RMSE values between predicted NDVI and actual NDVI (Landsat NDVI) of August and October were 0.049 and 0.085, and the correlation coefficients were 0.765 and 0.642 respectively. Spatiotemporal data fusion method is a pixel-based fusion technique that can be applied to variousspatial resolution images, and expected to be applied to various vegetation-related studies.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.169-181
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• 1997

In this paper, we propose and discuss about image enhancement techniques for MPEG-4. which represents very low bit-rate, content-based. and object-based hierarchical audio-visual coding standard. The proposed enhancement technique removes undesired artifacts arising in the compression procedure and increase resolution in both spatial and temporal domains. In order to remove undesired artifacts. we divide the MPEG-4 video algorithm in two parts: MPEG-2 like part and the new part. For removing artifacts caused by the first part. we adopt the conventional blocking artifacts algorithm developed for MPEG-2. On the other hand for removing artifacts caused by the second part. we provide a new degradation model. and propose the corresponding image restoration method. For increasing resolution of the MPEG-4 images, we propose a general framework of multichannel image interpolation process. which includes both spatial and temporal interpolations. As the MPEG-4 standard is under development. various sophisticated techniques are considered. but research on image enhancement techniques is relatively underestimated. By this reason. additional image enhancement techniques will become very important issue in realization phase of MPEG-4.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.553-564
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• 2018

Water use efficiency (WUE) is the amount of carbon uptake per unit of water use, which is a key measure of the functions of terrestrial ecosystems, as it is related to both the hydrologic and carbon cycles. Furthermore, it can vary with many factors, such as climate conditions and land cover characteristics, in different regions. In this study, we aim to understand the spatial and temporal variations in WUE on the Korean Peninsula as well as the associated response to drought. The Moderate Resolution Imaging Spectroradiometer (MODIS)-derived gross primary productivity (GPP) and evapotranspiration (ET) datasets and climate data were used to derive a drought index. Based on the monthly WUE, we found that WUE decreased during the monsoon summer in all regions and for all vegetation types. Furthermore, the annual WUE was negatively correlated with the drought index, with increasing correlation coefficients from the northern region to the southern region of the Korean Peninsula.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.6 s.237
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• pp.671-686
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• 2005

The transient nature and complex geometries of two-phase gas-liquid flows cause fundamental difficulties when measuring flow velocity using an electromagnetic flowmeter. Recently, a current-sensing flowmeter was introduced to obtain measurements with high temporal resolution (Ahn et al.). In this study, current-sensing flowmeter theory was applied to measure the fast velocity transients in slug flows. The velocity fields of axisymmetric gas-liquid slug flow in a vertical pipe were obtained using Volume-of-Fluid (VOF) method, and the virtual potential distributions for the electrodes of finite size were also computed using the finite volume method for simulating slug flow. The output signal prediction for slug flow was carried out from the velocity and virtual potential (or weight function) fields. The flowmeter was numerically calibrated to obtain the cross-sectional liquid mean velocity at an electrode plane from the predicted output signal. Two calibration parameters are proposed for this procedure: a flow pattern coefficient and a localization parameter. The flow pattern coefficient was defined by the ratio of the liquid resistance between the electrodes for two-phase flow with respect to that for single-phase flow, and the localization parameter was introduced to avoid errors in the flowmeter readings caused by liquid acceleration or deceleration around the electrodes. These parameters were also calculated from the computed velocity and virtual potential fields. The results can be used to obtain the liquid mean velocity from the slug flow signal measured by a current-sensing flowmeter.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.714-725
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• 2003

The theory of the current-type electromagnetic flowmeter for a high temporal resolution was developed for two-phase flow measurements. To predict the output of the current-type flowmeter, the three-dimensional virtual potential distribution C and the newly introduced flow pattern coefficient f were derived and computed. The output of flowmeter depends on the liquid conductivity (sensitive to temperature) and flow configurations of the two-phase flow with the sinusoidal excitation over 100 Hz. The flow pattern coefficient was specially devised to separate the dependency on the flow configuration of the two-phase flow from that on the liquid conductivity which can be expressed with the calibration of single-phase flow. Using the finite difference method, the three-dimensional virtual potential distributions were computed for the electrode of finite size. By taking derivative of the virtual potential, the weight functions were evaluated and compared with existing analytic series solution for the point-electrode. There was a reasonable correspondence between the present and existing results. In addition, the flow pattern coefficients were evaluated for annular flows with various film thicknesses, and compared with the experimental results by the impedance spectroscopy. The numerical results agreed well with the experimental data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.306-309
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• 2007

Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations (J-OFURO) includes global ocean surface heat flux data derived from satellite data and are used in many studies related to air-sea interaction. Recently latent heat flux data version 2 was constructed in J-OFURO. In version 2 many points are improved compared with version 1. A bulk algorithm used for estimation of latent heat flux is changed from Kondo (1975) to COASRE 3.0(Fairall et al., 2005). In version 1 we used NCEP reanalysis data (Reynolds and Smith, 1994) as SST data. However, the temporal resolution of the data is weekly and considerably low. Recently there are many kinds of global SST data because we can obtain SST data using a microwave radiometer sensor such as TRMM/MI and Aqua/AMSR-E. Therefore, we compared many SST products and determined to use Merged satellite and in situ data Global Daily (MGD) SST provided by Japan Meteorological Agency. Since we use wind speed and specific humidity data derived from one DMSP/SSMI sensor in J-OFURO, we obtain two data at most one day. Therefore, there may be large sampling errors for the daily-mean value. In order to escape this problem, multi-satellite data are used in version 2. As a result we could improve temporal resolution from 3-days mean value in version 1 to daily-mean value in version 2. Also we used an Optimum Interpolation method to estimate wind speed and specific humidity data instead of a simple mean method. Finally the data period is extended to 1989-2004. In this presentation we will introduce latent heat flux data version 2 in J-OFURO and comparison results with other surface latent heat flux data such as GSSTF2 and HOAPS etc. Moreover, we will present validation results by using buoy data.