• Journal of Korean Society for Atmospheric Environment
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• 제19권E4호
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• pp.149-155
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• 2003

In this study. the amounts of the total precipitable water (TPW) in both global and regional scale are estimated from the MODIS instrument, which is on-board the EOS satellites, Terra and Aqua. The estimation is made from the five near-infrared spectral bands, using a technique employing ratios of water- vapor absorbing channels centered at 0.905, 0.936, 0.940 ${\mu}{\textrm}{m}$ with atmospheric window channels at 0.865 and 1.240 ${\mu}{\textrm}{m}$. Through analyses of monthly and eight-days mean TPW, one can monitor characteristics of seasonal variations as well as amount and distribution (i.e., water resources) of TPW at both global and local regions. Long-term monitoring of TPW is essential to understand the regional variations of water resources in East Asia.

• 한국대기환경학회지
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• 제34권3호
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• 대한공간정보학회지
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• 제20권4호
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• pp.135-143
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• 2012

전조 모니터링, 피해규모 조사, 응급 구조 및 대응, 긴급 복구 등 국가적 재난관리 분야에 주기적으로 지구를 관측하는 원격탐측과 GIS 기반 의사결정 기술의 활용성이 점차 확대되고 있다. 여기에, 광역적이고 준실시간적 대응을 위해 단일 위성센서가 아닌 통합센서가 탑재된 위성의 운용과 각 국가별 우주개발기구간 협력을 통해 다수의 인공위성을 공동 활용함으로써 재난시 적시에 위성영상을 확보하기 위한 여러 방안이 강구되고 있다. 본 연구에서는 지난 2011년 발생했던 국내 폭설재난 대응을 위해 국제재난기구 등 다양한 경로로 수집된 저 고해상도 위성영상을 분석하고 MODIS 영상의 파장대 특성을 고려한 눈지수나 변화탐지 기법을 적용하여 적설지역을 추출하였다. 또한, 작성된 적설분포도와 다양한 공간자료와의 GIS 공간분석을 수행하여 재난상황에서 적시적으로 의사결정을 지원한 국립방재연구원의 현업적용 사례를 제시하였다.

• 대한토목학회논문집
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• 제35권6호
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• pp.1209-1218
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• 2015

전 세계적으로 가뭄 재해가 증가함에 따라 최근 위성영상 자료를 활용한 연구의 필요성이 대두되고 있다. 기존 연구는 대부분 실제 사례와의 연계성이 낮다는 한계점을 가지고 있다. 본 연구에서는 위성영상을 활용하여 지역적 분석을 실시하고, 영상 자료와 표준강수지수(SPI) 및 실제 가뭄 사례의 상관성 분석을 실시하고자 하였다. 국내 주요 가뭄(2001년, 2008-2009년)을 대상으로 각각 동두천과 태백 지역을 선정하였다. 8일 간격의 $0.05^{\circ}$ 공간해상도 MODIS DSI (Drought Severity Index)를 이용하여 SPI 및 수위 자료와의 상관관계 분석을 실시하였다. 동두천의 경우 6개월 DSI는 30일 SPI와 0.71의 상관관계를 나타냈으며, 태백 지역의 6개월 DSI와 90일 SPI의 상관성은 0.40을 보였다. DSI와 대상지역의 관측 저수위를 비교한 결과 6개월 DSI가 평균 65.7% 수준의 적중률을 보였다. 연구를 통하여 위성영상 자료 기반 가뭄지수인 DSI와 기상학적 가뭄지수인 SPI의 상관성을 부분적으로 제시할 수 있었으며, 실제 관측 자료와 비교를 실시한 결과 국내 연구에서의 활용 가능성을 확인하였다.

• 한국농공학회논문집
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• 제60권6호
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• pp.55-63
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• 2018

This paper aimed to characterize the spatial and temporal pattern of agricultural drought in Pre-Kharif season using Vegetation Health Index (VHI) and illustrated drought characteristics in Bangladesh during 2001-2015. VHI was calculated from TCI (Temperature Condition Index) and VCI (Vegetation Condition Index) derived from MODIS Terra satellite data, LST (Land Surface Temperature) and EVI (Enhanced Vegetation Index), respectively. The finding showed that all drought-affected areas were experienced by mild, moderate, severe and extreme droughts in several years of Pre-Kharif seasons. Significant drought events were found in the year of 2002 and 2013. On average, Chittagong district covered the largest drought area in all drought stages, and the fraction of drought area was the highest in Sylhet and Rangpur for Pre-Kharif season. Finally, overlaying annual VHI raster maps resulted in that the most vulnerable district to agricultural drought were Sylhet, Rangpur, and Mymensingh in the northern and eastern regions of Bangladesh.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.651-654
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• 2006

Infrared channels of newly launched Japanese geostationary satellite, MTSAT-1R are compared with well calibrated MODIS/Terra infrared measurements at 3.7, 6.7, 11, 12 ${\mu}m$ bands. There are four steps in this intercalibration method: 1) data collection, 2) spectral response function correction, 3) data collocation, and 4) calculation of mean bias and conversion coefficients. In order to minimize the navigation error of MTSAT-1R, comparisons are made over the area in which the viewing angle of MTSAT-1R is less than 50$^{\circ}$. The calibration method was tested for August 2005 and within the 40$^{\circ}N$-40$^{\circ}S$, 100$^{\circ}$E-180$^{\circ}$E domain. The differences of spectral response functions were corrected through radiative transfer model simulation. Constructing collocated data differences in viewing geometry, observation time and space were taken into account. In order to avoid the radiance variation induced by cloud presence, clear-sky targets are selected as intercalibration target. The mean biases of 11, 12, 6.7, and 3.7 ${\mu}m$ bands are about -0.16, 0.36, 1.31, and -6.69 K, suggesting that accuracies of 3.7 ${\mu}m$ is questionable while other channels are comparable to MODIS

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.487-490
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• 2006

Ocean Color Monitor (OCM) onboard the Indian Remote Sensing Satellite IRS-P4 has been used to retrieve chlorophyll concentration in the Bay of Bengal and the Arabian Sea using a bio-optical algorithm. Cloud masking and atmospheric corrections have been performed before applying mapping function to derive chlorophyll concentration from IRS-P4 OCM data. We have retrieved chlorophyll concentration from OCM, and MODIS during the summer and winter season along the eastern and western coast of India at every 1 degree latitude at increasing distance (25, 50, 100, 150 and 200km) away from the coast as well as near river mouths for the period 2000-2003. We have also studied spatial and temporal dynamics of monthly MODIS Aqua (for period July 2002-April 2004). The seasonal dynamics of chlorophyll concentration over the Bay of Bengal and the Arabian Sea have been discussed using OCM and MODIS for both the coastal region and the open sea.

• 한국대기환경학회지
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• 제20권4호
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• pp.437-450
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• 2004

Extensive forest fire activities occurred across the border in Russia, particularly east of Lake Baikal between the Amur and Lena rivers in May 2003. These forest fires released large amounts of particulates and gases into the atmosphere, resulting in adverse effects on regional air quality and the global radiation budget. Smoke pollution from the Russian fires near Lake Baikal was transported to Korea through Mongolia and eastern China. On 20 May 2003, a number of large fires were burning in eastern Russian, producing a thick, widespread pall of smoke over much of Northeast Asia. In this study, separation technique was used for aerosol retrieval application with imagery from MODIS aboard TERRA satellites. MODIS true-color image shows the location of fires and the grayish color of the smoke plumes over Northeast Asia. Aerosol optical thckness (AOT) retrieved from the MODIS data were compared with fire hot spots, ground-based radiation data and TOMS -based aerosol index data. Large AOT, 2.0-5.0 was observed on 20 May 2003 over Korea due to the influence of the long range transport of smoke aerosol plume from the Russian fires, while surface observed fine mode of aerosol size distribution increased.

• 한국농공학회논문집
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• 제55권6호
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• pp.47-55
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• 2013

The objective of this study is to evaluate the applicability of Communication, Ocean, and Meteorological Satellite (COMS) Geostationary Ocean Color Imager (GOCI) vegetation indices on a quantitative analysis. For evaluation, the vegetation indices such as RVI, NDVI and SAVI were extracted by using COMS GOCI and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) imageries. The 4,000 points using simple random sampling (SRS) method were randomly extracted from land areas except ocean to compare the vegetation indices from two images. The results of linear regression showed that the regression coefficients of RVI, NDVI, and SAVI between COMS GOCI and Terra MODIS were 0.66~0.82, 0.71~0.83, and 0.71~0.83, respectively. Especially, the regression coefficients of RVI (r=0.85), NDVI (r=0.91) and SAVI (r=0.91) were strongly related from September 2011 to January 2012. Thus, COMS GOCI can be substituted for particular periods and it needs to verify additionally.

• 한국농공학회논문집
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• 제54권3호
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• pp.141-148
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• 2012

Food policy is considered as the most basic and central issue for all countries, while making efforts to keep each country's food sovereignty and enhance food self-sufficiency. In the case of Korea where the staple food is rice, the rice yield prediction is regarded as a very important task to cope with unstable food supply at a national level. In this study, Korean paddy Rice yield Prediction Model (KRPM) developed to predict the paddy rice yield using meteorological element and MODIS NDVI. A multiple linear regression analysis was carried out by using the NDVI extracted from satellite image. Six meteorological elements include average temperature; maximum temperature; minimum temperature; rainfall; accumulated rainfall and duration of sunshine. Concerning the evaluation for the applicability of the KRPM, the accuracy assessment was carried out through correlation analysis between predicted and provided data by the National Statistical Office of paddy rice yield in 2011. The 2011 predicted yield of paddy rice by KRPM was 505 kg/10a at whole country level and 487 kg/10a by agroclimatic zones using stepwise regression while the predicted value by KOrea Statistical Information Service was 532 kg/10a. The characteristics of changes in paddy rice yield according to NDVI and other meteorological elements were well reflected by the KRPM.