• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1087-1091
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• 2008

Evapotranspiration (ET) is an important factor while simulating daily streamflow in hydrological models. The LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably in the estimation of ET, for example, when using FAO Penman Monteith equation. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAIs from MODIS satellite data are avaliable, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. The 4 years (2001-2004) MODIS LAI data were prepared for the evaluation of continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungjudam watershed ($6661.58\;km^2$) located in the upstream of Han river basin of South Korea. From the model results, the FAO Penman Monteith ET was affected by the MODIS LAIs. Especially for the ET of deciduous forest, the Total ET was 33.9 % lager than coniferous forest for the 3.8 % lager of LAI. The watershed average LAI caused a 7.0 % decrease in average soil moisture of the watershed and 14.3 % decrease of ground water recharge.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.264-274
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• 2009

Concentration of Air Quality Models (CMAQ) has a deep connection with emissions and wind fields. In particular the wind field is highly affected by local topography and plays an important role in transport and dispersion of contaminants from the pollution sources. The purpose of this study is to examine the impact of interpolation on Air quality model. This study was designed to evaluate enhancement of MM5 and CMAQ predictions by using Four Dimensional Data Assimilation (FDDA), the SONDE data and the national meteorological station and the MODerate resolution Imaging Spectroradiometer (MODIS). The alternative meteorological fields predicted with and without MODIS data were used to simulate spatial and temporal variations of ozone in combined with CMAQ on June 2006. The result of this study indicated that data assimilation using MODIS data provided an attractive method for generating realistic meteorological fields and dispersion fields of ozone in the Korea peninsular, because MODIS data in 10 km domain are grid horizontally and vertically. In order to ensure the success of Air quality model, it is necessary to FDDA using MODIS data.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.383-383
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• 2017

간척지는 바다와 접하는 하구언, 개벌로 이루어진 해안 등을 농공상업용지로 개간한 토지로서 간척지 이용에 있어 가장 우선적으로 용수공급 방안 수립이 고려되어야 한다. 해안유출지하수(submarine groundwater discharge)는 지하수 담수체가 존재하는 마지막 장소로 염해가 없는 청정수질 용수이다. 해안유출지하수 발생 구간을 탐지하기 위해 실측자료의 시공간적 한계를 극복할 수 있는 인공위성 영상을 활용한 원격탐사 기법을 이용하여 광역규모의 다양한 자료를 이용하고자 한다. MODIS (Moderate-Resolution Imaging Spectroradiometer)는 지구 생물권 활동에 관한 자료를 제공하는 미항공우주국 Terra EOS (Earth Observation system)위성의 주센서로 해양, 육상과 대기 분야에 적용이 가능한 다목적 센서이다. MODIS는 36개의 밴드를 이용하여 대기, 지표, 해양 관련 다양한 정보들을 제공하고 있다. 본 연구에서는 간척지의 효율적인 용수공급을 위한 해안유출지하수의 최적 개발 및 이용을 위해 MODIS MOD11 product 지표면온도(Land Surface Temperature; LST), MODIS MOD13 product 식생지수(Normalized Difference Vegetation Index; NDVI), 기상청의 지중온도와 실측자료를 이용하여 새만금 간척지를 대상으로 해안유출지하수 발생 구간을 탐지하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.446-446
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• 2022

본 연구에서는 MODIS(MODerate resolution Imaging Spectroradiometer) 다중 위성영상을 기반으로 전국 시공간 토양수분 및 토양수분 기반의 가뭄지수 SWDI(Soil Water Deficit Index)를 산정하였다. 시공간 토양수분의 산정을 위해 입력자료로 MODIS 위성의 지표면온도(Land Surface Temperature, LST), 증발산 및 식생(Enhanced Vegetation Index, EVI; Fraction of Photosynthetically Active Radiation, FPAR; Leaf Area Index, LAI; Normalized Difference Vegetation Index, NDVI) 관련 산출물 자료와 지상 관측자료인 일 단위 강수량 자료를 구축하였다. MODIS 위성영상은 산출물별로 제공되는 QC(Quality Control) 영상을 활용해 보정을 수행하였고, 공간 강수량 자료는 기상청에서 제공하는 전국 92개 지점의 종관기상관측자료를 구축하여 공간보간기법인 역거리가중법을 적용해 생성하였다. 실측 토양수분은 농촌진흥청에서 제공하는 76개 지점의 토양 깊이 10 cm에 설치된 TDR(Time Domain Reflectomerty) 센서에서 측정된 토양수분 자료를 활용하였으며, 토양수분 모의 시 토양 속성을 고려하기 위해 국립농업과학원에서 제공하는 토양도를 구축하여 활용하였다. 토양수분 산정 모형은 다중선형회귀모형(Multiple Linear Regression Model, MLRM)을 활용하였으며, 계절 및 토성에 따른 회귀식을 산정하였다. 회귀식 기반의 토양수분과 토성별 포장용수량 및 영구위조점 값을 이용하여 SWDI를 산정하고, 실제 가뭄 발생 시기 및 지역과의 비교하고자 한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.313-318
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• 2017

Land surface temperature is essential for monitoring abnormal climate phenomena such as UHI (Urban Heat Islands), and for modeling weather patterns. However, the quality of surface temperature obtained from the optical space imagery is affected by many factors such as, revisit period of the satellite, instance of capture, spatial resolution, and cloud coverage. Landsat 8 imagery, often used to obtain surface temperatures, has a high resolution of 30 meters (100 meters rearranged to 30 meters) and a revisit frequency of 16 days. On the contrary, MODIS imagery can be acquired daily with a spatial resolution of about 1 kilometer. Many past attempts have been made using both Landsat and MODIS imagery to complement each other to produce an imagery of improved temporal and spatial resolution. This paper applied machine learning methods and performed downscaling which can obtain daily based land surface temperature imagery of 30 meters.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1466-1470
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• 2010

토양수분은 지표의 다양한 과정을 통제하는 중요한 수문학적 변수며 이에 신뢰할 수 있는 토양수분의 정보를 습득하는 것은 매우 중요하다. 그러나 정확한 토양수분의 실측자료는 그 설치비용과 인력부족으로 매우 빈약하여 이를 대체할 만한 정보를 획득하기 위한 연구 또한 부족하다. 요즘, 많은 수문모형의 개발로 토양 수분 또한 결과물로써 많이 이용된다. 그러나 모형에서 모의된 토양수분의 신뢰성을 판단할 때는 실측자료를 이용하는 것이 가장 이상적이나, 토양수분의 실측값이 부족하므로, 유역의 토양수분 실측자료 대신 모의된 토양수분을 적용할 필요가 있다. 이에 따라 본 연구에서는 우리나라 소양강댐 유역에 대하여 SWAT(Soil and Water Assessment Tool) 모형을 이용하여 실측 토양수분자료를 최대한 활용함으로써 토양수분을 모의하였다. 또한 모의된 토양수분을 Terra MODIS NDVI(Normalized Difference Vegetation Index)와 LST(Land Surface Temperature)과의 상관성을 계절별, 월별로 분석하여 그 관계식을 도출하고자 하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.145-157
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• 2015

In 2015, drought was at the worst stage of devastation in Soyanggang Dam watershed. The purpose of this study is to trace the drought area around Soyanggang dam watershed by using Terra MODIS image because it has the ability of spatio-temporal dynamics. The MODIS indices, which included the enhanced vegetation index (NDVI), were extracted from MODIS product MOD13 16-day composite datasets with a spatial resolution of 250m from 2010.01.01 to 2015.06.30. We found that application of Vegetation Condition Index (VCI) and Standardized Vegetation Index (SVI) was suitable for monitoring the drought area. The result can be used to acquire the drought data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of drought effects.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.128-141
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• 2010

Drought indices such as SPI(Standard Precipitation Index) and PDSI(Palmer Drought Severity Index) estimated using ground observations are not enough to describe detail spatial distribution of drought condition. In this study, the drought index with improved spatial resolution was estimated by using the CART algorithm and ancillary data such as MODIS NDVI, MODIS LST, land cover, rainfall, average air temperature, SPI, and PDSI data. Estimated drought index using the proposed approach for the year 2008 demonstrates better spatial information than that of traditional approaches. Results show that the availability of satellite imageries and various associated data allows us to get improved spatial drought information using a data mining technique and ancillary data and get better understanding of drought condition and prediction.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.571-581
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• 2008

The sea fog occurs frequently in the west coast of Korea in spring and summer. This study focused on the detection of sea fog using MODIS satellite images. We presented a method for sea fog detection based on the homogeneity level between low stratus and sea fog, which was that the top surface of sea fog had a homogeneous aspect while that of low stratus had a heterogenous aspect. The results showed that the both homogeneity of $11{\mu}m$ brightness temperature (BT) and brightness temperature difference (BTD, $BT_{3.7{\mu}m}-BT_{11{\mu}m}$) were available to discriminate sea fog from low stratus. The frequency of difference between BT in fog/stratus area and BT in clear area provided reasonable result. In addition, the threshold values of standard deviations of BT and BTD in the fog/stratus area were applicable to differentiate fog from low stratus.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.149-160
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• 2015

A comparative study was conducted for alternative consecutive procedures of detection of cloud-contaminated pixels and gap-filling and smoothing of time-series data to produce high-quality gapless satellite vegetation index (i.e. Normalized Difference Vegetation Index, NDVI). Performances of five alternative methods for detecting cloud contaminations were tested with ground-observed cloudiness data. The data gap was filled with a simple linear interpolation and then, it was applied two alternative smoothing methods (i.e. Savitzky-Golay and Wavelet transform). Moderate resolution imaging spectroradiometer (MODIS) data were used in this study. Among the alternative cloud detection methods, a criterion of MODIS Band 3 reflectance over 10% showed best accuracy with an agreement rate of 85%, which was followed by criteria of MODIS Quality assessment (82%) and Band 3 reflectance over 20% (81%), respectively. In smoothing process, the Savitzky-Golay filter was better performed to retain original NDVI patterns than the wavelet transform. This study demonstrated an operational framework of gapdetection, filling, and smoothing to produce high-quality satellite vegetation index.