• 한국측량학회지
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• 제35권4호
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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.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 춘계학술발표회 논문집
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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.

• 대한공간정보학회지
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• 제14권2호
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• pp.55-62
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• 2006

현재 물부족 국가로 분류되고 있는 우리나라 현실에서 가뭄은 재해 관리에 있어서 중요한 요소가 되고 있다. 위성영상은 광역의 지표면에 대해 오랜 시간 동안 주기적으로 자료를 취득할 수 있게 해주므로, 이를 가뭄의 관측에 활용하면 유용한 결과를 얻을 가능성이 크다. 본 연구에서는 광역의 가뭄현상을 해석하는 데 있어서 위성영상을 활용하는 방안을 제시하고자 하였다. 따라서, 미국 NASA에서 제공하는 MODIS 자료의 식생지수(NDVI)자료를 이용하여 광역의 증발산량을 산정하는 방법을 개발하였다. 위성영상을 이용하여 산정된 증발산량 분포를 강우 분포자료 및 잠재증발산량 분포자료와 결합하여 기후학적 물수지를 산정하였으며, 이를 기반으로 대상지역의 가뭄을 효과적으로 분석할 수 있었다. 본 연구의 결과는 가뭄 해석에 있어서의 위성영상의 활용도를 높이는 데 기여를 할 것이다.

• 대한원격탐사학회지
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• 제28권3호
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• pp.277-285
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• 2012

The GOCI imagery can be an effective alternative to monitor short-term changes over terrestrial environments. This study aimed to assess the radiometric characteristics of the GOCI multispectral imagery for land applications. As an initial approach, we compared GOCI at-sensor radiance with MODIS data obtained simultaneously. Dynamic range of GOCI radiance was larger than MODIS over land area. Further, the at-sensor radiance over various land surface targets were tested by vicarious calibration. Surface reflectance were directly measured in field using a portable spectrometer and indirectly derived from the atmospherically corrected MODIS product over relatively homogeneous sites of desert, tidal flat, bare soil, and fallow crop fields. The GOCI radiance values were then simulated by radiative transfer model (6S). In overall, simulated radiance were very similar to the actual radiance extracted from GOCI data. Normalized difference vegetation index (NDVI) calculated from the GOCI bands 5 and 8 shows very close relationship with MODIS NDVI. In this study, the GOCI imagery has shown appropriate radiometric quality to be used for various land applications. Further works are needed to derive surface reflectance over land area after atmospheric correction.

• 대한원격탐사학회지
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• 제39권6_1호
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• pp.1483-1490
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• 2023

Aqua/ MODerate resolution Imaging Spectroradiometer (MODIS) 위성의 노후화에 따라 Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) 위성영상을 활용한 작황 평가 가능성을 분석하기 위해 미국 일리노이주 옥수수, 콩 재배지를 대상으로 2012년부터 2022년까지 11년동안 Normalized Difference Vegetation Index (NDVI) 변화 특성을 분석하였다. MODIS, VIIRS NDVI는 0.98 이상의 높은 상관계수를 보였다. 그러나 작물이 급격히 성장, 쇠락하는 시기에는 VIIRS NDVI가 MODIS에 비해 0.12~0.14 정도 높은 값을 보였다. NDVI를 기반으로 생육이상 등급을 추정한 결과 2018, 2019년 옥수수, 콩의 생육이상 등급은 유사한 변화 경향을 보였다. 그러나 2022년에는 생육등급의 차이가 커지는 것으로 나타났다. MODIS 및 VIIRS 위성영상 NDVI와 옥수수, 콩 수량의 상관계수는 0.8 이상의 높은 값을 보여 MODIS 위성영상뿐 아니라 VIIRS 위성영상을 활용한 수량 추정 가능성을 확인할 수 있었다. VIIRS 위성영상 NDVI의 경우 콩 수량 추정에서 작물 증가 추세를 제외하는 것이 상관성을 높여주는 것으로 나타났으며, MODIS에 비해서 NDVI와 수량의 상관성이 16일 정도 이른 시기부터 높은 경향을 보여 조기 추정에 대한 가능성도 확인할 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.398-401
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• 2005

Droughts have been an important factor in disaster management in Korea because she has been grouped into nations of lack of water. Satellite imagery can be applied to droughts monitoring because it can afford periodic data for large area for long time. This study aims to develop a method to analyze droughts in large area using satellite imagery. We estimated evapotranspiration in large area using NDVI data acquired from satellite imagery. For satellite imagery, we dealt with MODIS data operated by NASA. As the result of this study, we improved the usability of satellite imagery, especially in drought analysis.

• 한국측량학회지
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• 제26권3호
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• pp.219-225
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• 2008

원자력 발전소의 주변 지역은 해안지역이고 비교적 광범위하므로, 환경 변화를 감시하는데 많은 어려움이 있다. Landsat ETM+영상은 해상도가 30m 급이나 온도정보 추출에 있어 대기보정을 못하는 문제를 가지고 있다. MODIS 영상의 경우 2개의 적외선 밴드를 이용하여 대기보정된 비교적 적확한 온도를 추출할 수 있으나 해상도가 1km이다. 따라서, 두 위성영상의 자료를 이용한다면 대기보정된 고해상도의 온도자료를 추출할 수 있다. 본 연구에서는 대상지역의 Landsat ETM+영상에 대하여 기하보정을 수행하고, 방사휘도 및 온도를 산정한 후 MODIS영상을 이용하여 대기보정을 수행하였다. 그 결과 울진 원자력발전소 주변 연근해 지역과 온배수의 영향을 받지 않는 동쪽으로 5km 떨어진 동일 면적의 지역과 비교하여 보았을 때 약 $3.5^{\circ}C$ 높은 것을 알 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.598-601
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• 2006

Satellite imagery may contain large regions covered with atmospheric aerosol. A high-resolution satellite imagery affected by non-homogenous aerosol cover should be processed for land cover study and perform the radiometric calibration that will allow its future application for Korea Multi-Purpose Satellite (KOMPSAT) data. In this study, aerosol signal was separated from high resolution satellite data based on the reflectance separation method. Since aerosol removal has a good sensitivity over bright surface such as man-made targets, aerosol optical thickness (AOT) retrieval algorithm could be used. AOT retrieval using Look-up table (LUT) approach for utilizing the transformed image to radiometrically compensate visible band imagery is processed and tested in the correction of satellite scenery. Moderate Resolution Imaging Spectroradiometer (MODIS), EO-1/HYPERION data have been used for aerosol correction and AOT retrieval with different spatial resolution. Results show that an application of the aerosol detection for HYPERION data yields successive aerosol separation from imagery and AOT maps are consistent with MODIS AOT map.

• 대한원격탐사학회지
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• 제22권5호
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• pp.379-383
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• 2006

Satellite imagery may contain large regions covered with atmospheric aerosol. A highresolution satellite imagery affected by non-homogenous aerosol cover should be processed for land cover study and perform the radiometric calibration that will allow its future application for Korea Multi-Purpose Satellite (KOMPSAT) data. In this study, aerosol signal was separated from high resolution satellite data based on the reflectance separation method. Since aerosol removal has a good sensitivity over bright surface such as man-made targets, aerosol optical thickness (AOT) retrieval algorithm could be used. AOT retrieval using Look-up table (LUT) approach for utilizing the transformed image to radiometrically compensate visible band imagery is processed and tested in the correction of satellite scenery. Moderate Resolution Imaging Spectroradiometer (MODIS), EO-l/HYPERION data have been used for aerosol correction and AOT retrieval with different spatial resolution. Results show that an application of the aerosol detection for HYPERION data yields successive aerosol separation from imagery and AOT maps are consistent with MODIS AOT map.

• 대한원격탐사학회지
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• 제28권3호
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• pp.287-296
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• 2012

Although low spatial resolution satellite images like MODIS and GOCI can be important to observe land surface, it is often difficult to visually interpret the imagery because of the low contrast by prevailing cloud covers. We proposed a simple and adaptive stretching algorithm to enhance image contrast over land areas in cloudy images. The proposed method is basically a linear algorithm that stretches only non-cloud pixels. The adaptive linear stretch method uses two values: the low limit (L) from image statistics and upper limit (U) from low boundary value of cloud pixels. The cloud pixel value was automatically determined by pre-developed empirical function for each spectral band. We used MODIS and GOCI images having various types of cloud distributions and coverage. The adaptive contrast stretching method was evaluated by both visual interpretation and statistical distribution of displayed brightness values.