• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1385-1394
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• 2022

This study was to analyze the change in albedo by level-2 land cover map for 20 years(2002-2021) using MODerate resolution Imaging Spectroradiometer (MODIS) data. Also, the difference from the MODIS data was analyzed using the 10-year (2012-2021) data of Visible Infrared Imaging Radiometer Suite (VIIRS). For the albedo data of MODIS and VIIRS, daily albedo data, MCD43A3 and VNP43IA, of 500 m spatial resolution of sinusoidal tile grid produced by Bidirectional Reflectance Distribution Function (BRDF) model were prepared for the South Korea range. Reprojection was performed using the code written based on Python 3.9, and the nearest neighbor was applied as the resampling method. White sky albedo and black sky albedo of shortwave were used for analysis. As a result of 20-year albedo analysis using MODIS data, the albedo tends to rise in all land use. Compared to the 2000s (2002-2011), the average albedo of the 2010s (2012-2021) showed the most significant increase of 0.0027 in the forest area, followed by the grass increase of 0.0024. As a result of comparing the albedo of VIIRS and MODIS, it was found that the albedo of VIIRS was larger from 0.001 to 0.1, which was considered to be due to differences in the surface reflectivity according to the time of image capture and sensor characteristics.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.521-529
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• 2012

The evapotranspiration (ET) is one of the most important factor in the hydrological cycle. In this study, remote sensing based ET algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) was considered. Then, Priestley-Taylor algorithm was used for estimation of potential evapotranspiration in South Korea, and its spatial distribution was analyzed. Overall applicability between estimated potential evapotranspiration and weather station pan evaporation in Nakdong river basin was represented. The results using small pan showed that correlation coefficient in Pohang and Moonkyung Station was 0.70 and 0.55, respectively. However, the results using large pan showed correlation coefficient in Pohang and Moonkyung Station was 0.62 and 0.52, respectively.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.553-564
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• 2018

Water use efficiency (WUE) is the amount of carbon uptake per unit of water use, which is a key measure of the functions of terrestrial ecosystems, as it is related to both the hydrologic and carbon cycles. Furthermore, it can vary with many factors, such as climate conditions and land cover characteristics, in different regions. In this study, we aim to understand the spatial and temporal variations in WUE on the Korean Peninsula as well as the associated response to drought. The Moderate Resolution Imaging Spectroradiometer (MODIS)-derived gross primary productivity (GPP) and evapotranspiration (ET) datasets and climate data were used to derive a drought index. Based on the monthly WUE, we found that WUE decreased during the monsoon summer in all regions and for all vegetation types. Furthermore, the annual WUE was negatively correlated with the drought index, with increasing correlation coefficients from the northern region to the southern region of the Korean Peninsula.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.242-245
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• 2009

본 연구는 한반도 국토 전역을 모니터링 하기 위해 MODIS(Moderate Resolution Imaging Spectroradiometer) 위성영상을 이용하는데 있어서 필요한 기본적 자료처리 및 모니터링 시스템 구축을 목표로 한다. 현재 MODIS관련 product는 대부분 NASA에서 제공하는 알고리즘을 구현하여 제작되며 이러한 product들은 여러 웹싸이트에 접근하여 획득하도록 되어있다. 이러한 방식은 장기적으로 국토를 모니터링 하는데 필요한 자료를 원활하게 공급하지 못하게 되는 단점을 가지고 있다. 그러므로 이 연구는 한반도의 국토환경을 모니터링 하는데 MODIS 자료를 원활히 공급하기 위한 처리 시스템을 구축하고자 한다. 본 연구에서는 Windows환경을 기반으로 사용자 인터페이스를 제공하고 다양한 MODIS 관련 모듈을 내부적으로 자동화 처리하여 보다 쉽게 사용할 수 있도록 개선하였다. 특히 MODIS 원시영상(Production Data Set) Level0 취득부터 보정된 영상자료 Level1B까지의 자동화 처리에 중점을 두었고, Level2이후의 주로 육상(Land)부분에 해당하는 자료를 생성하는 부분을 구현한다. 이러한 MODIS 자료의 생성 이후에 국토 모니터링에 필요한 토지 피복 변화, 산불 탐지 등의 정보를 생성하는 알고리즘 구현 등으로 범위를 확장하려고 한다.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.305-316
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• 2010

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensor has 36 bands at 250m, 500m, 1km spatial resolution. However, 500m or 1km MODIS data exhibits a few limitations when low resolution data is applied at small areas that possess complex land cover types. In this study, we produce seven 250m spectral bands by fusing two MODIS 250m bands into five 500m bands. In order to recommend the best fusion method by which one acquires MODIS data, we compare seven fusion methods including the Brovey transform, principle components algorithm (PCA) fusion method, the Gram-Schmidt fusion method, the least mean and variance matching method, the least square fusion method, the discrete wavelet fusion method, and the wavelet-PCA fusion method. Results of the above fusion methods are compared using various evaluation indicators such as correlation, relative difference of mean, relative variation, deviation index, peak signal-to-noise ratio index and universal image quality index, as well as visual interpretation method. Among various fusion methods, the local mean and variance matching method provides the best fusion result for the visual interpretation and the evaluation indicators. The fusion algorithm of 250m MODIS data may be used to effectively improve the accuracy of various MODIS land products.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.271-276
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• 2003

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) of Terra and Aqua satellites, launched in December 1999 and May 2002, has been directly received by Korea Aerospace Research Institute (KARI) ground station facility from July 2002. 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 $\mu\textrm{m}$ and 14.235 $\mu\textrm{m}$, 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 satellite imagery obtained through the MODIS will be utilized for many application such as national territorial management, agriculture, natural environment, atmosphere and ocean, etc. In this study is to introduce various application field of MODIS imagery and data processing system.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1483-1490
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• 2023

We analyzed the potential for joint utilization of Visible Infrared Imaging Radiometer Suite (VIIRS) satellite imagery Normalized Difference Vegetation Index (NDVI) in crop assessment, considering the aging of MODerate resolution Imaging Spectroradiometer (MODIS) satellites. Over 11 years from 2012 to 2022, we examined the characteristics of NDVI changes in corn and soybean cultivation areas in Illinois, USA. VIIRS and MODIS satellite imagery NDVI exhibited a high correlation coefficient of over 0.98. However, during periods of rapid crop growth or decline, VIIRS NDVI showed values approximately 0.12 to 0.14 higher than MODIS. Estimating crop anomaly classes based on NDVI, we observed similar trends in corn and soybean crop anomaly classes in 2018 and 2019. However, in 2022, there appeared to be a significant divergence in crop anomaly classes, suggesting the need for further investigation. The correlation coefficients between MODIS and VIIRS satellite imagery NDVI and corn and soybean yields were consistently high, exceeding 0.8, indicating the potential for quantity estimation using both MODIS and VIIRS satellite imagery. Specifically, for VIIRS NDVI, excluding the increasing trend in crop quantity estimation for soybeans enhanced the correlation, and compared to MODIS, it showed a consistently high correlation with quantity from approximately 16 days earlier, indicating the potential for early estimation.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1035-1046
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• 2022

This study evaluated the applicability of multi-resolution data fusion for land-cover classification. In the applicability evaluation, a spatial time-series geostatistical deconvolution/fusion model (STGDFM) was applied as a multi-resolution data fusion model. The study area was selected as some agricultural lands in Iowa State, United States. As input data for multi-resolution data fusion, Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite images were used considering the landscape of study area. Based on this, synthetic Landsat images were generated at the missing date of Landsat images by applying STGDFM. Then, land-cover classification was performed using both the acquired Landsat images and the STGDFM fusion results as input data. In particular, to evaluate the applicability of multi-resolution data fusion, two classification results using only Landsat images and using both Landsat images and fusion results were compared and evaluated. As a result, in the classification result using only Landsat images, the mixed patterns were prominent in the corn and soybean cultivation areas, which are the main land-cover type in study area. In addition, the mixed patterns between land-cover types of vegetation such as hay and grain areas and grass areas were presented to be large. On the other hand, in the classification result using both Landsat images and fusion results, these mixed patterns between land-cover types of vegetation as well as corn and soybean were greatly alleviated. Due to this, the classification accuracy was improved by about 20%p in the classification result using both Landsat images and fusion results. It was considered that the missing of the Landsat images could be compensated for by reflecting the time-series spectral information of the MODIS images in the fusion results through STGDFM. This study confirmed that multi-resolution data fusion can be effectively applied to land-cover classification.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.251-257
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• 2004

The Electro-Optical Camera(EOC) image of the first Korea Multi-Purpose Satellitel(KOMPSAT-1) has both high resolution and convenient acquisition of research data, but on the other hand it has a defect of one band image. Fortunately, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data are receiving every day at the Korea Aerospace Research Institute (KARI). Therefore, this paper performed an effective merging for survey of reclaimed land using the high-resolution (6.6m) KOMPSAT-1 EOC image and the multispectral MODIS image data. According this paper prepared map of reclaimed lands in Western Coast of North Korea as quantitative(position and form) survey of reclaimed lands of North Korea using merged image. The use of KOPSAT-1 EOC image and MODIS images was found to be economical such using of large scale areas as reclaimed land or according easy to collect information and such north korea as inaccessible areas like as receiving every day.