• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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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.

• Proceedings of the KSRS Conference
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• 2002.10a
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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.

• Proceedings of the KSRS Conference
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• 2003.11a
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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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.97-109
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• 2019

Degree days have been determined using temperature data measured at nearby weather stations to a site of interest to produce information for supporting decision-making on agricultural production. Alternatively, the data products of Moderate Resolution Imaging Spectroradiometer (MODIS) can be used for estimation of degree days in a given region, e.g., Korean Peninsula. The objective of this study was to develop a simple tool for processing the MODIS product for estimating cooling degree days (CDD), which would help assessment of heat stress conditions for a crop as well as energy requirement for greenhouses. A set of scripts written in R was implemented to obtain temperature profile data for the region of interest. These scripts had functionalities for processing spatial data, which include reprojection, mosaicking, and cropping. A module to extract air temperature at the surface pressure level was also developed using R extension packages such as rgdal and RcppArmadillo. Random forest (RF) models, which estimate mean temperature and CDD with a different set of MODIS data, were trained at 34 sites in South Korea during 2009 - 2018. Then, the values of CDD were calculated over Korean peninsula during the same period using those RF models. It was found that the CDD estimates using the MODIS data explained >74% of the variation in the CDD measurements at the weather stations in North Korea as well as South Korea. These results indicate that temperature data derived from the MODIS atmospheric products would be useful for reliable estimation of CDD. Our results also suggest that the MODIS data can be used for preparation of weather input data for other temperature-based agro-ecological models such as growing degree days or chill units.

• Atmosphere
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• v.20 no.4
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.197-214
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• 2019

In this study, the correlation analysis was conducted between observed air temperature (maximum, minimum, and mean air temperature) and the daytime and nighttime data of Terra/Aqua MODIS LST(Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) for 86 weather stations. All the data of the recent 11 years from 2008 to 2018 were prepared with daily base. In particular, the characteristics of the cold and heat waves incidence period in 2018 were analyzed. The correlation analysis was performed using the Pearson correlation coefficient(R) and root mean square error(RMSE). As a result of time series analysis, the trend between observed air temperature and MODIS LST were similar, showing the correlation above 0.9 in maximum temperature, above 0.8 in mean and minimum temperature. Especially, the maximum temperature was found to have the highest accuracy with Terra MODIS LST daytime, and the minimum temperature had the highest correlation with Terra MODIS LST nighttime. During the cold wave period, both Terra and Aqua MODIS LST showed higher correlations with nighttime data than daytime data. For the heat wave period, the Aqua MODIS LST daytime data was good, but the overall R was below 0.5. Additional analysis is necessary for further study considering such as land cover and elevation characteristics.

• Proceedings of the KSRS Conference
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• 2002.10a
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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.

• Proceedings of the KSRS Conference
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• 2002.10a
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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/".

• Proceedings of the KSRS Conference
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• 2004.10a
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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.