• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.51-60
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• 2020

The purpose of this study is to determine the spatial and temporal resolutions that can represent land surface characteristics comprised of various land use using Landsat/AMSR2-based soil moisture data. We estimated the Landsat (30 m×30 m)-based soil moisture values using the soil moisture regression model. Then, the Landsat (30 m×30 m)-based soil moisture (reference values) were resampled to the relatively coarse resolutions from 1 km to 4 km, respectively. Comparing the reference values to the resampled soil moisture values, we confirmed that uncertainties were increased with the spatial resolutions of 2 km~4 km indicating that the spatial resolution of 1 km×1 km is required to represent the complicated land surface. Also, the AMSR2 soil moisture values have less uncertainties compared to SMAP data with the temporal resolution of 1~2 days. Thus, our findings can be useful for various areas such as agriculture, hydrology, forest, etc.

• New & Renewable Energy
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• v.7 no.1
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• pp.22-28
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• 2011

The surface solar radiations were calculated and analyzed with spatial resolutions (4 km and 1 km) using by GWNU (Gangneung-Wonju National University) solar radiation model. The GWNU solar radiation model is used various data such as aerosol optical thickness, ozone amount, total precipitable water and cloud factor are retrieved from Moderate Resolution Imaging Spectrometer (MODIS), Ozone Monitoring Instrument (OMI), MTSAT-1R satellite data and output of the Regional Data Assimilation Prediction System(RDAPS) model by Korea Meteorological Administration (KMA), respectively. The differences of spatial resolutions were analyzed with input data (especially, cloud factor from MTSAT-1R satellite). And the Maximum solar radiation by GWNU model were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud factor.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• IE interfaces
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• v.18 no.1
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• pp.82-87
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• 2005

Most of virtual reality systems ask users to control 3D objects or to navigate 3D world using 3D controllers. To maximize the human performance in the control, the design of virtual reality system and its input and output devices should be optimized. In this study, an experiment was designed to investigate the effects of three resolution factors of a virtual reality system on the human performance. Six subjects conducted the experiment for the factors; two frame rates, three spatial resolutions, and three pictorial contents. The result showed that the greater the spatial resolution was, the higher the human performance was. For the temporal resolution, fixed frame rate at 18 Hz was better than the varied maximized frame rate. For the pictorial contents, the virtual space with orientation cues marked the greatest performance than the other two conditions; the virtual space without any orientation cue and the virtual space like real world. These results could be applied for the design of virtual reality systems.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.689-705
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• 2016

This paper proposed an realtime total monitoring platform for various kind of multi weather radars to analyze and predict weather phenomenons and prevent meteorological disasters. Our platform is designed to process each weather radar data on each radar site to minimize overloads from conversion and transmission of large volumed radar data, and to set observers up the definitive radar data via public framework server separately. By proposed method, weather radar data having different spatial or temporal resolutions can be automatically synchronized with there own spatio-temporal domains on public GIS platform having only one spatio-temporal criterion. Simulation result shows that our method facilitates the realtime weather monitoring from weather radars having various spatio-temporal resolutions without other data synchronization or assimilation processes. Moreover, since this platform doesn't require some additional computer equipments or high-technical mechanisms it has economic efficiency for it's systemic constructions.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.181-184
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• 2000

가상현실 시스템은 대부분 가상세계에 대해 사용자의 3차원 제어작업을 요구하게 된다. 이때 3차원 제어작업을 효과적으로 하기 위한 입출력장치의 최적 설계는 매우 중요하다. 본 연구에서는 3차원 표시장치의 주요 설계요소인 공간적 해상도(spatial resolution), 시간적 해상도(temporal resolution or frame rate), 가상세계의 복잡도가 3차원 제어작업의 인간성능에 미치는 영향을 알아보았다. 이를 위해 3 조건의 화면 해상도, 2 조건의 프레임 레이트(18 Hz고정과 18Hz 이상 변동 최대화 조건), 3 조건의 가상세계 복잡도에 대한 18 조합에 대한 실험을 실시하였다. 실험결과 18Hz 로 고정된 프레임 레이트 조건이 프레임 레이트를 그 이상 최대로 하는 것보다 더 좋은 제어성능을 보였다. 화면 해상도는 높을수록 제어성능이 향상되었다. 가상세계의 복잡도에서는 방향정보만 주는 경우가 방향 정보가 없는 경우나 너무 많은 정보가 있는 경우보다 나은 성능을 보였다. 이러한 실험결과는 가상환경 시스템의 표시장치나 가상세계 설계에 참조될 수 있을 것이다.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1931-1942
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• 2021

As the utility of an optical satellite image with a high spatial resolution (i.e., fine-scale) has been emphasized, recently, various studies of the land surface monitoring using those have been widely carried out. However, the usefulness of fine-scale satellite images is limited because those are acquired at a low temporal resolution. To compensate for this limitation, the spatiotemporal data fusion can be applied to generate a synthetic image with a high spatio-temporal resolution by fusing multiple satellite images with different spatial and temporal resolutions. Since the spatio-temporal data fusion models have been developed for mid or low spatial resolution satellite images in the previous studies, it is necessary to evaluate the applicability of the developed models to the satellite images with a high spatial resolution. For this, this study evaluated the applicability of the developed spatio-temporal fusion models for KOMPSAT-3A and Sentinel-2 images. Here, an Enhanced Spatial and Temporal Adaptive Fusion Model (ESTARFM) and Spatial Time-series Geostatistical Deconvolution/Fusion Model (STGDFM), which use the different information for prediction, were applied. As a result of this study, it was found that the prediction performance of STGDFM, which combines temporally continuous reflectance values, was better than that of ESTARFM. Particularly, the prediction performance of STGDFM was significantly improved when it is difficult to simultaneously acquire KOMPSAT and Sentinel-2 images at a same date due to the low temporal resolution of KOMPSAT images. From the results of this study, it was confirmed that STGDFM, which has relatively better prediction performance by combining continuous temporal information, can compensate for the limitation to the low revisit time of fine-scale satellite images.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.

• Proceedings of the KSRS Conference
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• v.2
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• pp.563-566
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• 2006

In order for the evaluation and analysis of the spring drought which has been periodically occurring in Korean peninsula since 2000, the use of satellite image data is increasing to investigate temporal and spatial characteristics of the drought areas. The recent spring droughts in south Korea have some characteristics. It last for short period in spring when the activity of vegetation is not lively and it have large areal deviation in the severity of drought. In this study, considering the characteristics of the spring drought in Korean peninsular, the MODIS satellite image data which has superior spatial and radiometric resolutions was used for the analysis of the spring drought. In two basins having different spatial characteristics, the drought events were selected and their severities were analyzed using the MODIS NDVI, LSWI, and daily rainfall data since 2000, and the spatial characteristics of the drought area were analyzed using the DEM, land cover, and digital forest map of the study areas.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.51-57
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• 2005

The currently operating NASA/GFZ Gravity Recovery and Climate Experiment (GRACE) mission is designed to measure small mass changes over a large spatial scale, including the mapping of continental water storage changes and other geophysical signals in the form of monthly temporal gravity field. The European Space Agency's Gravity field and steady state Ocean Circulation Explorer (GOCE) space gravity gradiometer (SGG) mission is anticipated to determine the mean Earth gravity field with an unprecedented geoid accuracy of several cm (rms) with wavelength of 130km or longer. In this paper, we present a summary of present GRACE studies for the recovery of hydrological signals in the Amazon basin using alternative processing and filtering techniques, and local inversion to enhance the temporal and spatial resolutions by two-folds or better. Simulation studies for the potential GRACE detection of slow deformations due to Nazca-South America plate convergence and glacial isostatic adjustment (GIA) signals show that these signals are at present difficult to detect without long-term data averaging and further improvement of GRACE measurement accuracy.