• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.935-943
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• 2014

Normalized Difference Vegetation Index (NDVI) used as input data for various hydrologic models plays a key role in understanding the variation of Hydrometeological parameters and Interaction between surface and atmosphere. Many studies have been conducted to estimate accurate remotely-sensed NDVI using spectral characteristics of vegetation. In this study, we conducted comparative analysis between Communication, Ocean and Meteorological Satellite and MOderate-Resolution Imaging Spectroradiometer (MODIS) NDVI. For comparison, Maximum Value Composite (MVC) was used to estimate 8-day and 16-day composite COMS NDVI. Both 8-day and 16-day COMS NDVI showed high statistical results compared with MODIS NDVI. Based on the results in this study, it can be concluded that COMS can be widely applicable for further ecological and hydrological studies.

• Journal of the Korean Geographical Society
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• v.38 no.6
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• pp.935-948
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• 2003

The State Soil Geographic (STATSGO) database is a valuable source for assessment of soil properties at a state level. Using GIS techniques, eight physical soil properties were extracted from the database, including available water capacity, clay content, soil depth, slope, depth to water table, drainage, texture, and permeability. The influences of these soil properties on drought severity, which was estimated by NDVI departures from normal, were determined over western-central Kansas. Study results showed that seven soil properties had significant relationships with drought severity with correlation coefficients, ranging from -0.89 to 0.85. Thermal emission signals from the Moderate Resolution Imaging Spectroradiometer (MODIS) had a significant relationship with drought severity expressed by NDVI departure from normal and represented spatial progression of drought over time well. High thermal signals, indicating high soil moisture deficit, emerged in the western region and their spatial distribution changed over time. Different sets of soil factors influenced drought severity among early-drying and late-drying areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.6-6
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• 2016

최근 전 지구적인 기후 변화에 따라 수문 순환을 이루고 있는 다양한 수문 기상 인자들의 변동성에 영향을 미치고 있다. 특히, 증발산은 수문순환을 구성하는 중요한 인자로서 대기와 지표간의 상호 작용을 파악하기 위해서는 이에 대한 정확한 이해 및 산정이 필수적이다. 일반적으로 증발산량을 산정하기 위해서 증발 접시 및 에디 공분산 기반 플럭스 타워에서 관측된 지점 자료만을 이용하여 증발산량의 변동성을 파악하는 연구들이 수행되어왔다. 그러나 지점 자료만을 이용하여 증발산량을 산출하게 되면 공간적인 변동성을 파악하는데 있어서 한계점이 발생하게 된다. 이러한 제약 사항을 해결하기 위해서, 인공위성 기반의 수문 기상인자를 물리식 기반 증발산량 산정식의 입력 자료로 구축하여 증발산량을 산정하고 이에 대한 시 간적인 변동성을 파악하는 연구들이 활발히 이루어지고 있다. 인공위성 기반 증발산량 산정 알고리즘의 대표적인 예로 공기동역학적 항과 에너지 수지 항들을 동시에 고려할 수 있는 Penman-Monteith 방법을 근간으로 수정하여 만들어낸 Remote Sensing based Penman-Monteith (RS-PM) 알고리즘이 있다. 그러나 RS-PM 기반의 증발산량 경우 태양복사열, 풍속, 온도, 습도와 같은 많은 수문기상인자들이 입력 자료를 요구한다. 이에 따라, 본 연구에서는 기존의 방법에 비해 상대적으로 적은 입력 자료를 사용하는 Modified Satellite-Based Priestley-Taylor (MS-PT) algorithm의 적용성을 평가하기 위해 MODerate-Resolution Imaging Spectroradiometer (MODIS) 자료를 이용하여 한반도에서 순복사에너지 (Net radiation) 및 실제 증발산량 (Actual evapotranspiration)을 산정하였다. 또한, 이에 대한 검증을 위해 청미천 유역에 설치되어있는 에디 공분산 기반 플럭스 타워에서 관측된 순복사 에너지 및 실제 증발산량에 대한 통계적 검증을 실시하였다.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1491-1495
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• 2023

This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.729-735
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• 2023

The Moderate resolution Imaging Spectroradiometer (MODIS) is a multispectral sensor that has been actively researched in various fields using diverse land and atmospheric products. MODIS was first launched over 20 years ago, and the demand for novel sensors that can produce data comparable to that obtained using MODIS has continuously increased. In this study, land products obtained using the Visible Infrared Imaging Radiometer Suite (VIIRS) of the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched in 2011 were introduced, including land surface temperature and vegetation indices such as the normalized difference vegetation index and enhanced vegetation index. These land products were compared with existing data obtained using MODIS to verify their local applicability in South Korea. Based on spatiotemporal monitoring of an extreme drought period in South Korea and the application of VIIRS land products, our results indicate that VIIRS can effectively replace MODIS multispectral sensors for agricultural drought monitoring.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.409-431
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• 2014

In this study, the characteristics in the simulation of high-resolution coastal weather, i.e. sea surface wind (SSW) and significant wave height (SWH), were studied in a southeastern coastal region of Korea using the WRF and SWAN models. This analyses was performed based on the effects of various input factors in the WRF and SWAN model during M-Case (moderate days with average 1.8 m SWH and $8.4ms^{-1}$ SSW) and R-Case (rough days with average 3.4 m SWH and $13.0ms^{-1}$ SSW) according to the strength of SSW and SWH. The effects of topography (TP), land cover (LC), and sea surface temperature (SST) for the simulation of SSW with the WRF model were somewhat high on v-component winds along the coastline and the adjacent sea of a more detailed grid simulation (333 m) during R-Case. The LC effect was apparent in all grid simulations during both cases regardless of the strength of SSW, whereas the TP effect had shown a difference (decrease or increase) of wind speed according to the strength of SSW (M-Case or R-Case). In addition, the effects of monthly mean currents (CR) and deepwater design waves (DW) for the simulation of SWH with the SWAN model predicted good agreement with observed SWH during R-Case compared to the M-Case. For example, the effects of CR and DW contributed to the increase of SWH during R-Case regardless of grid resolution, whereas the differences (decrease or increase) of SWH occurred according to each effect (CR or DW) during M-Case.

• Medical Lasers
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• v.10 no.4
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• pp.229-237
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• 2021

Background and Objectives To assess the effectiveness of overnight orthokeratology (OK) in myopia using a new contact lens design over a one-month wearing period. Materials and Methods Participants were required to have myopia between -3.00 and -7.50D and astigmatism ≤ 2.00 D to participate in the study. The participants underwent OK with the White OK lens^® (Interojo, Pyungtek, Korea), which has a 6-curve lens design. Participants were assessed at weeks 1, 2, and 4 using slit-lamp bio-microscopy, and tested for refraction, uncorrected distance visual acuity, and corneal topography. Success was defined as achieving a Logarithm of the Minimum Angle of Resolution (logMAR) ≤ 0.1. Results A total of 46 eligible subjects with a mean age of 23.11 ± 7.89 years were recruited. Baseline logMAR was 1.18 ± 0.30 and a consistent decrease in logMAR was observed from week 1 to week 4. The success rate was 95.35% at week 4. The mean sphere significantly decreased from a mean pre-fitting value of -4.58 ± 1.28 D to a mean value of -0.65 ± 0.69 D at week 4 (p < 0.0001). Statistically significant corneal flattening was detected during keratometry at week 4. Conclusion Overnight OK with the White OK lens is effective for the correction of moderate and high myopia with astigmatism over a one-month wearing period.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.201-220
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• 2016

In this study, the net solar radiation fluxes at the surface are retrieved by updating an existing algorithm to be applicable for MODerate resolution Imaging Spectroradiometer (MODIS) observations, in which linear relationships between the solar radiation reflected from the top of atmosphere and the net surface solar radiation are employed. The results of this study have been evaluated through intercomparison with existing Clouds and the Earth's Radiant Energy System (CERES) data products and ground-based data from pyranometers at Gangneung-Wonju National University (GWNU) and the Southern Great Plains (SGP) of observatory of Atmospheric Radiation Measurement (ARM) site. Prior to the comparison of the surface radiation energy in relation to the energy balance of the earth, the radiation energy of the upper part of the atmosphere was compared. As a result, the coefficient of determination was over 0.9, showing considerable similarity, but the Root-Mean-Square-Deviation (RMSD) value was somewhat different, and the downward and net solar-radiation energy also showed similar results. The surface solar radiation data measured from pyranometers at Gangneung-Wonju National University (GWNU) and Atmospheric Radiation Measurement (ARM) observatory are used to validate the solar radiation data produced in this study. When compared to the GWNU, The results of this study show smaller RMSD values than CERES data, showing slightly better agreements with the surface data. On the other hand, when compared with the data from ARM SGP observatory, the results of this study bear slightly larger RMSD values than those for CERES. The downward and net solar radiation estimated by the algorithm of this study at a high spatial resolution are expected to be very useful in the near future after refinements on the identified problems, especially for those area without ground measurements of solar radiation.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.511-524
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• 2014

In this study, we investigated the statistical occupations and interannual variations of land cover types over Northeast Asian region using the 12 years (2001-2012) MODerate Resolution Imaging Spectroradiometer(MODIS) land cover data sets. The spatial resolution and land cover types of MODIS land cover data sets are 500 m and 17, respectively. The 12-year average shows that more than 80% of the analysis region is covered by only 3 types of land cover, cropland (36.96%), grasslands (23.14%) and mixed forests (22.97%). Whereas, only minor portion is covered by cropland/natural vegetation mosaics (6.09%), deciduous broadleaf forests (4.26%), urban and built-up (2.46%) and savannas (1.54%). Although sampling period is small, the regression analysis showed that the occupations of evergreen needleleaf forests, deciduous broadleaf forests and mixed forests are increasing but the occupations of woody savannas and savannas are decreasing. In general, the pixels where the land cover types are classified differently with year are amount to more than 10%. And the interannual variations in the occupations of land cover types are most prominent in cropland (1.41%), mixed forests (0.82%) and grasslands (0.73%). In addition, the percentage of pixels classified as 1 type for 12 years is only 57% and the other pixels are classified as more than 2 types, even 9 types. The annual changes in the classification of land cover types are mainly occurred at the almost entire region, except for the eastern and northwestern parts of China, where the single type of land cover located. When we take into consider the time scale needed for the land cover changes, the results indicate that the MODIS land cover data sets over the Northeast Asian region should be used with caution.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.132-139
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• 2007

The Moderate Resolution Imaging Spectroradiometer (MODIS) regularly provides the eight-day gross primary productivity (GPP) at 1 km resolution. In this study, we evaluated the uncertainties of MODIS GPP caused by errors associated with the Data Assimilation Office (DAO) meteorology and a biophysical variable (fraction of absorbed photosynthetically active radiation, FPAR). In order to recalculate the improved GPP estimate, we employed ground weather station data and reconstructed cloud-free FPAR. The official MODIS GPP was evaluated as +17% higher than the improved GPP. The error associated with DAO meteorology was identified as the primary and the error from the cloud-contaminated FPAR as the secondary constituent in the integrative uncertainty. Among various biome types, the highest relative error of the official MODIS GPP to the improved GPP was found in the mixed forest biome with RE of 20% and the smallest errors were shown in crop land cover at 11%. Our results indicated that the uncertainty embedded in the official MODIS GPP product was considerable, indicating that the MODIS GPP needs to be reconstructed with the improved input data of daily surface meteorology and cloud-free FPAR in order to accurately monitor vegetation productivity in Korea.