• 제목/요약/키워드: MODIS data

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MODIS DBMS구축 및 DB data입력 S/W 개발

  • 이동한;김민아;전정남
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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    • pp.101-106
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    • 2003
  • 본 논문에서는 현재 한국항공우주연구원에서 수신, 저장하고 있는 MODIS 영상자료에 대한 DBMS (DataBase Management System) 구축 및 DB (DataBase) data 입력 S/W 개발 결과에 대해 설명한다. 우선, MODIS 영상자료의 DBMS를 구축하기 위한 DB table를 설계하였고, 이를 근거로 Oracle 9i를 사용하여 MODIS DBMS를 구축하여 운영 중이다. MODIS DBMS에 자동으로 MODIS 영상자료의 DB data들이 입력되도록 하기 위해, 첫 번째로 Visual C++를 사용하여서 MODIS DB table에 대한 DB data를 추출하는 ‘getatt.exe’ S/W를 개발하였고, 두 번째로 Visual Basic의 ADO를 사용하여서 ‘getatt.exe’ S/W로 추출된 DB data를 MODIS DBMS에 입력하는 S/W를 개발을 마무리하였으며, ‘getatt.exe’ S/W와 MODIS DBMS 입력 S/W를 한 개의 S/W로 통합하는 작업이 완료되어, 지금현재 한국항공우주연구원 내에서 정상적으로 MODIS DBMS가 운영 중이다.

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MODIS 총일차생산성 산출물의 오차요인 분석: 입력기상자료의 영향 (Errors of MODIS product of Gross Primary Production by using Data Assimilation Office Meteorological Data)

  • 강신규;김영일;김영진
    • 한국농림기상학회지
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    • 제7권2호
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    • pp.171-183
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    • 2005
  • In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

Development of MODIS Data Application System

  • Lim, Hyo-Suk;Lee, Seon-Gu;Seo, Doo-Cheon;Lee, Dong-Han;Kim, Mi-Na;Kim, Yong-Seung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.347-351
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    • 2002
  • The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra and Aqua satellites, launched in 1999 and 2002, is directly received by Korea Aerospace Research Institute (KARI) ground station facility. BURI engineers develop a system to receive direct broadcast downlink from MODIS to provide near-realtime, remotely-sensed, spaceborne data to the user community in Korea. MODIS scans a swath width of 2330 km that is sufficiently wide to cover Korean peninsular, Yellow and East Sea at once. The MODIS has 36 spectral bands between 0.415 fm and 14.235 $\mu$m, i.e. through the visible into the thermal infrared. MODIS has been observed active fires, floods, smoke transport, dust storms, severe storms since February of 2000. The KARI is preparing for distribution of direct broadcasted MODIS data to users in Korea. The MODIS database system will be designed and developed by KARI engineer for data service from year of 2003. MODIS data user group will be organized from $\.{O}$ctober to December 2002.

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Accuracy Assessment of Atmospheric Sounding Data from Terra/MODIS

  • Lee, Mi-Suk;Kim, Young-Seup;Kwon, Byung-Hyuk;Hong, Ki-Man;Park, Kyung-Won
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.201-203
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    • 2003
  • Two MODIS instruments on board the Terra and Aqua Satellites are operational for global remote sensing of the land, ocean and atmosphere. Atmospheric sounding data with a high spatial resolution from MODIS will provide a wealth of useful information. The vertical air temperature and moisture data were retrieved using the MODIS data, and compared with the radiosonde data obtained in the Korean Peninsula. The correlation coefficient are 0.99 and 0.89 for air temperature and moisture cases, respectively. Air temperature data were relatively good agreement, but the moisture data from MODIS were underestimated.

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MODIS 대기자료를 활용한 남북한 기상관측소에서의 냉방도일 추정 (The use of MODIS atmospheric products to estimate cooling degree days at weather stations in South and North Korea)

  • 유병현;김광수;이지혜
    • 한국농림기상학회지
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    • 제21권2호
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    • pp.97-109
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    • 2019
  • 적산 온도는 작물 재배 의사결정 지원을 위해 대상지역 주변 기상 관측소의 자료를 활용하여 산정되어 왔다. 한편 Moderate Resolution Imaging Spectroradiometer (MODIS) 자료로부터 공간적인 온도 자료를 바탕으로 특정 지점의 적산 온도 자료를 생산할 수 있다. 본 연구의 목적은 MODIS 자료를 처리하는 도구를 개발하고 이를 바탕으로 작물의 고온 피해도 및 시설의 냉방 요구도 분석에 활용될 수 있는 냉방도일을 계산하고자 하였다. R 스크립트를 사용하여 특정지역의 MODIS 기온자료를 생성하는 모듈들을 작성하였다. 해당 스크립트들은 격자자료의 좌표계 변환과 자료들의 공간적인 통합 기능들을 가지고 있었다. 온도 수직 분포 자료로부터 지표 기압에 해당하는 온도를 추출하는 기능은 rgdal과 RcppArmadillo등의 패키지를 활용하여 구현되었다. 또한 냉방도일 및 일평균온도 추정을 위해 MODIS 기온 자료, day of year, 및 위도를 입력 자료로 사용하는 random forest (RF) 모형을 남한 지역의 24개 지점에 대하여 훈련하였다. 인공위성 자료 별로 훈련된 RF 모형을 사용하여 한반도 지역의 일별 냉방도일을 계산하였다. 특히, 북한지역에 24개 지점에 대해 검증한 결과, MODIS 자료를 바탕으로 추정된 지역별 평균 연간 냉방도일은 관측값 변이의 96%를 설명할 수 있었다. 이러한 결과는 MODIS 자료로부터 유효적산온도 및 난방도일 등 다른 농림 기상 모형의 입력자료 생산을 지원할 수 있다는 것을 암시하였다.

최근 MODIS 식생지수 자료(2006-2008)를 이용한 동아시아 지역 지면피복 분류 (Land Cover Classification over East Asian Region Using Recent MODIS NDVI Data (2006-2008))

  • 강전호;서명석;곽종흠
    • 대기
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    • 제20권4호
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    • pp.415-426
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    • 2010
  • A Land cover map over East Asian region (Kongju national university Land Cover map: KLC) is classified by using support vector machine (SVM) and evaluated with ground truth data. The basic input data are the recent three years (2006-2008) of MODIS (MODerate Imaging Spectriradiometer) NDVI (normalized difference vegetation index) data. The spatial resolution and temporal frequency of MODIS NDVI are 1km and 16 days, respectively. To minimize the number of cloud contaminated pixels in the MODIS NDVI data, the maximum value composite is applied to the 16 days data. And correction of cloud contaminated pixels based on the spatiotemporal continuity assumption are applied to the monthly NDVI data. To reduce the dataset and improve the classification quality, 9 phenological data, such as, NDVI maximum, amplitude, average, and others, derived from the corrected monthly NDVI data. The 3 types of land cover maps (International Geosphere Biosphere Programme: IGBP, University of Maryland: UMd, and MODIS) were used to build up a "quasi" ground truth data set, which were composed of pixels where the three land cover maps classified as the same land cover type. The classification results show that the fractions of broadleaf trees and grasslands are greater, but those of the croplands and needleleaf trees are smaller compared to those of the IGBP or UMd. The validation results using in-situ observation database show that the percentages of pixels in agreement with the observations are 80%, 77%, 63%, 57% in MODIS, KLC, IGBP, UMd land cover data, respectively. The significant differences in land cover types among the MODIS, IGBP, UMd and KLC are mainly occurred at the southern China and Manchuria, where most of pixels are contaminated by cloud and snow during summer and winter, respectively. It shows that the quality of raw data is one of the most important factors in land cover classification.

Derivation of SST using MODIS direct broadcast data

  • Chung, Chu-Yong;Ahn, Myoung-Hwan;Koo, Ja-Min;Sohn, Eun-Ha;Chung, Hyo-Sang
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.638-643
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    • 2002
  • MODIS (MODerate-resolution Imaging Spectroradiometer) onboard the first Earth Observing System (EOS) satellite, Terra, was launched successfully at the end of 1999. The direct broadcast MODIS data has been received and utilized in Korea Meteorological Administration (KMA) since february 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). To produce the MODIS SST operationally, we used a simple cloud mask algorithm and MCSST algorithm. By using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST, a new set of MCSST coefficients was derived. And we tried to analyze the current NASA's PFSST and new MCSST algorithms by using the collocated buoy observation data. Although the number of collocated data was limited, both algorithms are highly correlated with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua that is the second EOS satellite. To use the MODIS standard cloud mask algorithm to get better SST coefficients is going to be prepared.

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Development of Terra MODIS data pre-processing system on WWW

  • Takeuchi, W.;Nemoto, T.;Baruah, P.J.;Ochi, S.;Yasuoka, Y.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.569-572
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    • 2002
  • Terra MODIS is one of the few space-borne sensors currently capable of acquiring radiometric data over the range of view angles. Institute of Industrial Science, University of Tokyo, has been receiving Terra MODIS data at Tokyo since May 2001 and Asian Institute of Technology at Bangkok since May 2001. They can cover whole East Asia and is expected to monitor environmental changes regularly such as deforestation, forest fires, floods and typhoon. Over eight hundred scenes have been archived in the storage system and they occupy 2 TB of disk space so far. In this study, MODIS data processing system on WWW is developed including following functions: spectral subset (250m, 500m, 1000m channels), radiometric correction to radiance, spatial subset of geocoded data as a rectangular area with latitude-longitude grid system in HDF format, generation of a quick look file in JPEG format. Users will be notified just after all the process have finished via e-mail. Using this system enables us to process MODIS data on WWW with a few input parameters and download the processed data by FTP access. An easy to use interface is expected to promote the use of MODIS data. This system is available via the Internet on the following URL from September 1 2002, "http : //webmodis.iis.u-tokyo.ac.jp/".

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Terra/Aqua MODIS LST와 기온과의 상관성 분석: 한파 및 폭염 발생 기간을 중심으로 (Correlation Analysis between Terra/Aqua MODIS LST and Air Temperature: Mainly on the Occurrence Period of Heat and Cold Waves)

  • 정지훈;이용관;이지완;김성준
    • 한국지리정보학회지
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    • 제22권4호
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    • pp.197-214
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    • 2019
  • 본 연구에서는 Terra/Aqua MODIS LST(Moderate Resolution Imaging Spectroradiometer Land Surface Temperature)의 Daytime, Nighttime 자료와 기상청 기상관측소 86개 지점에 대한 최고, 최저 및 평균기온을 이용하여 두 자료 사이의 상관성을 분석하고, 한파 및 폭염 발생 기간의 특성을 집중적으로 분석하였다. 모든 자료는 2008년부터 2018년까지 총 11년간 일별로 구축하였으며, Pearson 상관계수(Pearson correlation coefficient, R)와 평균제곱근오차(Root Mean Square Error, RMSE)를 이용하여 상관성 분석을 수행하였다. 시계열 분석 결과, 대상 기간 전체에서 기온과 MODIS LST 간의 변동 양상은 유사하였고, 최고 기온과 MODIS 자료의 R 0.9 이상, 평균기온과 최저 기온과는 0.8 이상으로 기온과 MODIS LST 사이의 상관성은 높은 것으로 나타났다. 특히, 최고 기온은 Terra MODIS LST Daytime과 정확도가 제일 높고, 최저 기온은 Terra MODIS LST Nighttime과 상관성이 제일 높은 것으로 분석되었다. 한파 기간에는 Terra/Aqua MODIS 모두 주간 자료보다 야간 자료의 상관성이 더 높은 것으로 분석되었으며, 특히 Terra MODIS LST Nighttime과의 상관성이 좋은 것으로 분석되었다. 폭염 기간에는 Aqua MODIS LST Daytime 자료가 가장 좋은 것으로 분석되었으나, 전체적인 R이 0.5보다 낮아 추후 활용을 위해서는 식생이나 토지이용, 고도 등 다른 요소를 활용한 추가 분석이 필요할 것으로 판단된다.

Application Studies for Active Fire Monitoring over Korea Using MODIS Direct Broadcast Data

  • Song J.H.;Kim Y.S.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.410-414
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    • 2004
  • The MODIS Land Rapid Response System (RRS) has been developed to provide rapid access to MODIS data globally, with initial emphasis on 250 m color composite imagery and active fire data. Fire detection is based on a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. This algorithm examines each pixel of the MODIS swath, and ultimately assigns to each one of the following classes: missing data, cloud, water, non-fire, fire, or unknown. In this paper, we introduce the MODIS Rapid Response System established at the Korea Aerospace Research Institute (KARI) and present some application results for Korea using the direct broadcast data acquired at KARI ground station.

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