• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.140-140
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• 2016

수분 이용효율(Water Use Efficiency, WUE)은 식생이 흡수한 수분 중 증발산에 이용한 비율로, 육상생태계의 수문학적 순환 및 탄소 순환의 기능을 측정할 수 있는 중요한 지표이다. 또한 이는 특정 지역의 기후 조건이나 토지 피복과 같은 다양한 요인에 따라 변할 수 있다. 본 연구에서는 한반도에서 2010년부터 2014년까지의 기후 요인(강수, 기온)과 토지 피복에 따른 WUE의 변화를 살펴본다. MODerate resolution Imaging Spectroradiometer (MODIS) 기반 총일차생산성(Gross Primary Productivity, GPP), 증발산량(Evapotranspiration, ET), 잎면적지수(Leaf Area Index, LAI)와 Willmot의 기상자료 등 대상지역에 대한 격자 자료를 사용한다. 구체적으로 숲, 초원, 농지와 같이 다양한 토지 피복 조건에 대한 월간 및 연간 WUE(=GPP/ET)를 산정하고, 이의 LAI나 기후 조건(강수, 기온)과의 관계를 분석하고자 상관성 및 요인 분석을 진행한다. 기후 조건 및 토지 피복 조건을 고려한 15년간 한반도에서의 WUE의 변화에 대한 분석은 앞으로의 수자원 관리 및 산림 정책에 활용할 수 있을 것으로 판단된다.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.554-556
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• 2005

Meteorological imager on the Multi-functional Transport Satellite (MTSAT-IR), which has been operating formally since 28 June 2005, was intercalibrated with a polar orbit satellite [Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS)] as a well-calibrated instrument. The intercalibration method used in this study was developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS). This was done for the infrared window channels. The differences of MTSAT-IR and MODIS were are -0.26 K for $11\;\mu m-IR$ window channel, 0.40 K for $12\;\mu m-IR$, window channel, and -0.67 K for $6.7\;\mu m-water$ vapor channel.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.5
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• pp.67-77
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• 2007

The images of MODerate resolution Imaging Spectroradiometer (MODIS) that provide wider swath and shorter revisit frequency than Land Satellite (Landsat) and Satellite Pour I' Observation de la Terre (SPOT) has been used fer land cover classification with better spatial resolution than National Oceanic and Atmosphere Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR)'s images. Due to the advantages of MODIS, several researches have conducted, however the results for the land cover classification using MODIS images have less accuracy of classification in small areas because of low spatial resolution. In this study, uncertainty of paddy fields classification using MODIS images was conducted in the region of Gyeonggi-do and the relation between this uncertainty of estimating paddy fields and topographical factors was also explained. The accuracy of classified paddy fields was compared with the land cover map of Environmental Geographic Information System (EGIS) in 2001 classified using Landsat images. Uncertainty of paddy fields classification was analyzed about the elevation and slope from the 30m resolution Digital Elevation Model (DEM) provided in EGIS. As a result of paddy classification, user's accuracy was about 41.5% and producer's accuracy was 57.6%. About 59% extracted paddy fields represented over 50 uncertainty in one hundred scale and about 18% extracted paddy fields showed 100 uncertainty. It is considered that several land covers mixed in a MODIS pixel influenced on extracted results and most classified paddy fields were distributed through elevation I, II and slope A region.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.101-115
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• 2021

The purpose of this study is to evaluate the compatibility of the vegetation index between the two satellites and the applicability of agricultural monitoring by comparing and verifying NDVI (Normalized Difference Vegetation Index) based on Sentinel-2 and Terra MODIS (Moderate Resolution Imaging Spectroradiometer). Terra MODIS NDVI utilized 16-day MOD13Q1 data with 250 m spatial resolution, and Sentinel-2 NDVI utilized 10-day Level-2A BOA (Bottom Of Atmosphere) data with 10 m spatial resolution. To compare both NDVI, Sentinel-2 NDVIs were reproduced at 16-day intervals using the MVC (Maximum Value Composite) technique. As a result of time series NDVIs based on two satellites for 2019 and compare by land cover, the average R² (Coefficient of determination) and RMSE (Root Mean Square Error) of the entire land cover were 0.86 and 0.11, which indicates that Sentinel-2 NDVI and MODIS NDVI had a high correlation. MODIS NDVI is overestimated than Sentinel-2 NDVI for all land cover due to coarse spatial resolution. The high-resolution Sentinel-2 NDVI was found to reflect the characteristics of each land cover better than the MODIS NDVI because it has a higher discrimination ability for subdivided land cover and land cover with a small area range.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.251-251
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• 2016

인공위성을 이용한 가뭄연구에는 전지구적으로 운용되는 GPM (Global Precipitation Measurement) 위성, AQUA/TERRA 위성의 MODIS (MODerate resolution Imaging Spectroradiometer) 센서 등에서 수집된 관측 자료가 이용된다. 그러나 전지국적으로 관측된 위성 자료는 자료를 생산 제공하는 기관에 따라 자료의 파일포맷 (NetCDF, HDF5, GeoTIFF 등), 자료의 투영법 (projection) 등이 상이하다. 그러므로 가뭄연구에 다중위성자료를 활용하고자 하는 지리정보시스템(Geographic Information System: GIS)에 대한 전문지식이 부족한 연구자는 자료의 표준화 (파일포맷과 투영변환 등) 과정으로 인해 원활한 연구수행이 어렵다. MODIS 위성자료의 경우에는 일반적으로 많이 사용되는 횡단메르카토르 도법 (Transverse Mercator Projection: TM) 대신 시뉴소이드 도법 (sinusoidal projection)을 이용한다. 그래서 미국 지질조사국은 MODIS 자료의 재투영(reprojection)을 위한 전용 소프트웨어인 MRT (MODIS Reprojection Tool)를 배포하고 있다. 본 연구에서는 무료/오픈소스 소프트웨어를 활용하여 시뉴소이드 도법이 적용된 MODIS 자료의 수집, 재투영, 파일포맷 변환 등을 자동으로 처리하는 기법을 개발하여 가뭄활용에 이용하고자 하였으며, MODIS MOD09GA/MOD11A1 자료를 이용하여 효율성을 검증하였다.

• 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 Wetlands Research
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• v.21 no.spc
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• pp.123-133
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• 2019

This study analyzed the surface temperature mitigation effect of wetlands during cold waves (below -12℃ from January to February) and heat waves (above 33℃ from July to August) in 2018. We used Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Daytime and Nighttime Land Surface Temperature (LST) product, and the maximum and minimum air temperature observed at 86 stations of Korea Meteorological Administration (KMA). For the cold wave analysis, the LST of Terra MODIS nighttime was the highest at forest area with -12.7℃, followed by upland crop and wetland areas of -12.9℃ and -13.0℃ respectively. The urban area showed the lowest value of -14.4℃. During the heat wave, the urban area was the highest with + 34.6℃ in Aqua MODIS LST daytime. The wetland area was + 33.0℃ showing - 1.6℃ decrease comparing with urban area.

• Journal of Korea Water Resources Association
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• v.49 no.11
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• pp.903-912
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• 2016

Accurate understanding and estimating Evapotranspiration (ET) is essential for understanding the mechanism of water cycle and water budget. ET has been analyzed by many researchers in worldwide while Ground-based ET has limiation in analyzing the spatio-temporal pattrens of ET. Thus, many researches have been conducted to represent the spatio-temporal variation of ET by using hydrometeorological variables estimated from remote sensing datasets. Previous remote sensing based ET algorithms, however, have disadvantage in that various hydrometeological input datasets were required. In this study, actual ET was estimated by MODIS-based Rn and MS-PT algorithm requiring relatively less input data than previous method. The result confirmed that the observed $R_N$ and latent heat flux from the eddy-covariance based fluxtowers located at CFK and SMK showed high correlation with the estimated $R_N$ and ET. The average determination coefficients ($R^2$) of ET estimated from satellite dataset over study periods were 0.77 (0.72-0.81) in Cheongmi (CFK) and 0.70 (0.67-0.78) in Sulma (SMK), respectively. Comparing with the actual ET of two flux tower sites, however, SMK showed more overestimated patterns than CFK due to the vegetation and radiation related errors.

• Journal of Wetlands Research
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• v.13 no.2
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• pp.171-179
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• 2011

The main objective of this study is to estimate of the vegetation response induced by climate change to soil moisture. We investigated a relationship between vegetation activity and climate variables using Moderate Resolution Imaging Spectroradiometer (MODIS)-retrieved Normalized Difference Vegetation Index (NDVI) and soil moisture. NDVI which extracted from MODIS 13 Vegetation Indices Product was considered as an useful parameter to figure out a relationship with two types of soil moisture, which were observed at Rural Development Administration sites and estimated from Advanced Microwave Scanning Radiometer E (AMSR-E) satellite imagery. The correlation of MODIS-NDVI and ground measured soil moisture were observed, became much stronger when compared to soil moisture values with time lag (5days, 10days, 15days). The correlation patterns between NDVI and soil moisture with different time lag were related to soil texture. The results from this study will be useful to understand the role of vegetation in water balance control in various scales from regional to global climate change.