• Title/Summary/Keyword: MODIS Satellite

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Applicability of Multi-Temporal MODIS Images for Drought Assessment in South Korea (봄 가뭄 평가를 위한 다중시기 MODIS 영상의 적용성 분석)

  • Park, Jung-Sool;Kim, Kyung-Tak;Lee, Jin-Hee;Lee, Kyu-Sung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.4
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    • pp.176-192
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    • 2006
  • The need for a systematic drought management has increased since last countrywide drought in 2001. Naturally various studies for establishing drought plan and preventing drought disaster have been conducted. MODIS image provided by Terra satellite has effective spatial and temporal resolutions to observe spatial and temporal characteristics of a region. MODIS data products are easy for preprocessing and correcting geometrically and provide various data set in regular which are applicable for drought monitoring. In this study, Ansung river and the upstream of South Han river basin was chosen for case study to identify and assess spring drought. The multi-period MODIS image and accumulated precipitation were used to detect not only the drought year but also the vegetation change of normal year and the result were compared with various spatial data. The result shows NDVI and LSWI with is more appropriate than LST for assesing spring drought in Korea and two month cumulative precipitation has moderate relationship with drought. It is necessary to use MODIS image which has same period and same space for effective drought analysis because drought is also affected by landover and altitude.

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Analysis of Precipitable water over Global and East Asia using MODIS satellite data (MODIS 위성자료를 이용한 전구 및 동아시아의 가강수량 분석)

  • Lee, Sang-Hun;Park, Seon-K.;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1635-1639
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    • 2010
  • 기후변화가 수자원에 미치는 영향을 파악하기 위해서는 물 순환 및 물 수지의 변화 경향 파악이 필수적이며, 대기 중의 가강수량 파악은 가뭄 호우 등에 대한 기본 조사로서 수자원 연구에 필요하다. 본 연구에서는 MODIS 위성자료로부터 가강수량을 산출하여 검증하고, 전구 및 동아시아의 분포 특성 및 변화 경향을 분석하였다. MODIS 위성자료는 NASA의 홈페이지로부터 입수하여 가강수량을 산출하였고, 산출한 가강수량은 NCEP Reanalysis2 자료를 이용하여 검증하였다. MODIS 위성자료를 이용하여 전구 가강수량의 경년변화 및 분포 분석을 실시한 결과 가강수량의 분포는 ITCZ의 움직임과 잘 일치하였고, 6월에 가장 많은 가강수량을 나타내며 10월에 가장 적은 가강수량을 나타냈다. 경년변화는 2000년대 중반까지는 증가하는 경향을 보이고 있었지만 최근 3년 정도는 감소하는 추세를 보이고 있다. MODIS 위성자료를 이용하여 동아시아 지역 가강수량의 경년변화 및 분포 분석을 실시한 결과 가강수량의 분포는 계절적인 특징을 잘 나타내고 있으며, 7월에 가장 많은 가강수량을 나타내고 있으며 11월에 가장 적은 가강수량을 나타내고 있고, 경년변화는 큰 변화는 보이지 않았다. MODIS 위성으로부터 산출한 가강수량과 표면온도를 비교한 결과 가강수량은 계절적인 특징은 거의 비슷한 변화를 가지고 있으며 년 변화에서는 동아시아 가을의 변화가 통계적으로 유의한 양의 상관관계를 가지고 있었으며, 동아시아 가을의 가강수량은 표면온도와 함께 증가하는 경향을 나타내고 있다.

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Estimation of South Korea Spatial Soil Moisture using TensorFlow with Terra MODIS and GPM Satellite Data (Tensorflow와 Terra MODIS, GPM 위성 자료를 활용한 우리나라 토양수분 산정 연구)

  • Jang, Won Jin;Lee, Young Gwan;Kim, Seong Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.140-140
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    • 2019
  • 본 연구에서는 Terra MODIS 위성자료와 Tensorflow를 활용해 1 km 공간 해상도의 토양수분을 산정하는 알고리즘을 개발하고, 국내 관측 자료를 활용해 검증하고자 한다. 토양수분 모의를 위한 입력 자료는 Terra MODIS NDVI(Normalized Difference Vegetation Index)와 LST(Land Surface Temperature), GPM(Global Precipitation Measurement) 강우 자료를 구축하고, 농촌진흥청에서 제공하는 1:25,000 정밀토양도를 기반으로 모의하였다. 여기서, LST와 GPM의 자료는 기상청의 종관기상관측지점의 LST, 강우 자료와 조건부합성(Conditional Merging, CM) 기법을 적용해 결측치를 보간하였고, 모든 위성 자료의 공간해상도를 1 km로 resampling하여 활용하였다. 토양수분 산정 기술은 인공 신경망(Artificial Neural Network) 모형의 딥 러닝(Deep Learning)을 적용, 기계 학습기반의 패턴학습을 사용하였다. 패턴학습에는 Python 라이브러리인 TensorFlow를 사용하였고 학습 자료로는 농촌진흥청 농업기상정보서비스에서 101개 지점의 토양수분 자료(2014 ~ 2016년)를 활용하고, 모의 결과는 2017 ~ 2018년까지의 자료로 검증하고자 한다.

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Aerosol Direct Radiative Forcing by Three Dimensional Observations from Passive- and Active- Satellite Sensors (수동형-능동형 위성센서 관측자료를 이용한 대기 에어러솔의 3차원 분포 및 복사강제 효과 산정)

  • Lee, Kwon-Ho
    • Journal of Korean Society for Atmospheric Environment
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    • v.28 no.2
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    • pp.159-171
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    • 2012
  • Aerosol direct radiative forcing (ADRF) retrieval method was developed by combining data from passive and active satellite sensors. Aerosol optical thickness (AOT) retrieved form the Moderate Resolution Imaging Spectroradiometer (MODIS) as a passive visible sensor and aerosol vertical profile from to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) as an active laser sensor were investigated an application possibility. Especially, space-born Light Detection and Ranging (Lidar) observation provides a specific knowledge of the optical properties of atmospheric aerosols with spatial, temporal, vertical, and spectral resolutions. On the basis of extensive radiative transfer modeling, it is demonstrated that the use of the aerosol vertical profiles is sensitive to the estimation of ADRF. Throughout the investigation of relationship between aerosol height and ADRF, mean change rates of ADRF per increasing of 1 km aerosol height are smaller at surface than top-of-atmosphere (TOA). As a case study, satellite data for the Asian dust day of March 31, 2007 were used to estimate ADRF. Resulting ADRF values were compared with those retrieved independently from MODIS only data. The absolute difference values are 1.27% at surface level and 4.73% at top of atmosphere (TOA).

RETRIEVING AEROSOL AMOUNT FROM GEOSTATIONARY SATELLITE

  • Yoon, Jong-Min;Kim, Jhoon
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.232-235
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    • 2006
  • Using 30 days of hourly visible channel data and DIScrete Ordinate Radiative Transfer (DISORT) model (6S), Aerosol optical depth (AOD) at $0.55{\mu}m$ was retrieved over the East Asia. In contrast with the AOD retrieval using low-earth-orbit satellites such as MODIS (Moderate-Res olution Spectroradiometer) or MISR (Multiangle Imaging SpectroRadiometer), this algorithm with geostationary satellite can improve the monitoring of AOD without the limitation of temporal resolution. Due to the limited number of channels in the conventional meteorological imager onboard the geostationary satellite, an AOD retrieval algorithm utilizing a single visible channel has been introduced. This single channel algorithm has larger retrieval error of AOD than other multiple-channel algorithm due to errors in surface reflectance and atmospheric property. In this study, the effects of manifold atmospheric and surface properties on the retrieval of AOD from the geostationary satellite, are investigated and compared with the AODs from AERONET and MODIS. To improve the accuracy of retrieved AOD, efforts were put together to minimize uncertainties through extensive sensitivity tests. This algorithm can be utilized to retrieve aerosol information from previous geostationary satellite for long-term climate studies.

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Monitoring and Forecasting the Eyjafjallajökull Volcanic Ash using Combination of Satellite and Trajectory Analysis (인공위성 관측자료와 궤적분석을 이용한 Eyjafjallajökull 화산재 감시와 예측)

  • Lee, Kwon Ho
    • Journal of Korean Society for Atmospheric Environment
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    • v.30 no.2
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    • pp.139-149
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    • 2014
  • A new technique, namely the combination of satellite and trajectory analysis (CSTA), for exploring the spatio-temporal distribution information of volcanic ash plume (VAP) from volcanic eruption. CSTA uses the satellite derived ash property data and a matching forward-trajectories, which can generate airmass history pattern for specific VAP. In detail, VAP properties such as ash mask, aerosol optical thickness at 11 ${\mu}m$ ($AOT_{11}$), ash layer height, and effective radius from the Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite were retrieved, and used to estimate the possibility of the ash forecasting in local atmosphere near volcano. The use of CSTA for Iceland's Eyjafjallaj$\ddot{o}$kull volcano erupted in May 2010 reveals remarkable spatial coherence for some VAP source-transport pattern. The CSTA forecasted points of VAP are consistent with the area of MODIS retrieved VAP. The success rate of the 24 hour VAP forecast result was about 77.8% in this study. Finally, the use of CSTA could provide promising results for VAP monitoring and forecasting by satellite observation data and verification with long term measurement dataset.

Estimation of Satellite-based Spatial Evapotranspiration and Validation of Fluxtower Measurements by Eddy Covariance Method (인공위성 데이터 기반의 공간 증발산 산정 및 에디 공분산 기법에 의한 플럭스 타워 자료 검증)

  • Sur, Chan-Yang;Han, Seung-Jae;Lee, Jung-Hoon;Choi, Min-Ha
    • Korean Journal of Remote Sensing
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    • v.28 no.4
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    • pp.435-448
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    • 2012
  • Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a sensitive hydrological factor with outer circumstances. Though both direct measurements with an evaporation pan and a lysimeter, and empirical methods using eddy covariance technique and the Bowen ratio have been widely used to observe ET accurately, they have a limitation that the observation can stand for the exact site, not for an area. In this study, remote sensing technique is adopted to compensate the limitation of ground observation using the Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral sensor mounted on Terra satellite. We improved to evapotranspiration model based on remote sensing (Mu et al., 2007) and estimated Penman-Monteith evapotranspiration considering regional characteristics of Korea that was using only MODIS product. We validated evapotranspiration of Sulma (SMK)/Cheongmi (CFK) flux tower observation and calculation. The results showed high correlation coefficient as 0.69 and 0.74.

Mapping Snow Depth Using Moderate Resolution Imaging Spectroradiometer Satellite Images: Application to the Republic of Korea

  • Kim, Daeseong;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.34 no.4
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    • pp.625-638
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    • 2018
  • In this paper, we derive i) a function to estimate snow cover fraction (SCF) from a MODIS satellite image that has a wide observational area and short re-visit period and ii) a function to determine snow depth from the estimated SCF map. The SCF equation is important for estimating the snow depth from optical images. The proposed SCF equation is defined using the Gaussian function. We found that the Gaussian function was a better model than the linear equation for explaining the relationship between the normalized difference snow index (NDSI) and the normalized difference vegetation index (NDVI), and SCF. An accuracy test was performed using 38 MODIS images, and the achieved root mean square error (RMSE) was improved by approximately 7.7 % compared to that of the linear equation. After the SCF maps were created using the SCF equation from the MODIS images, a relation function between in-situ snow depth and MODIS-derived SCF was defined. The RMSE of the MODIS-derived snow depth was approximately 3.55 cm when compared to the in-situ data. This is a somewhat large error range in the Republic of Korea, which generally has less than 10 cm of snowfall. Therefore, in this study, we corrected the calculated snow depth using the relationship between the measured and calculated values for each single image unit. The corrected snow depth was finally recorded and had an RMSE of approximately 2.98 cm, which was an improvement. In future, the accuracy of the algorithm can be improved by considering more varied variables at the same time.

UPWELLING FILAMENTS AND THEIR ROLE IN CROSSFRONTAL WATER EXCHANGE

  • Kostianoy, A.G.;Soloviev, D.M.
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.954-957
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    • 2006
  • Satellite data (thermal and color imagery) show that offshore flowing filaments off the west coasts of North America, North and South Africa can influence significantly the cross-frontal mixing in the coastal upwelling zones. To evaluate this role, we investigated structure, dynamics and behavior of surface filaments in the Canary and Benguela upwelling regions on the base of daily satellite IR and VIS imagery (AVHRR NOAA, MODIS-Aqua). It was found that seasonal variability of the filaments location depends on intra-annual shift of general upwelling intensity along the coast. The main statistical characteristics of filaments - length, width, temperature anomaly and estimates of velocity were obtained. Estimates of cross-frontal water exchange due to filamentation based on the statistical data show that these coherent structures play a major role in the water and particle exchange between coastal zone and the open ocean in both upwelling regions.

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Monitoring of the Volcanic Ash Using Satellite Observation and Trajectory Analysis Model (인공위성 자료와 궤적분석 모델을 이용한 화산재 모니터링)

  • Lee, Kwon-Ho;Jang, Eun-Suk
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.13-24
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    • 2014
  • Satellite remote sensing data have been valuable tool for volcanic ash monitoring. In this study, we present the results of application of satellite remote sensing data for monitoring of volcanic ash for three major volcanic eruption cases (2008 Chait$\acute{e}$n, 2010 Eyjafjallaj$\ddot{o}$kull, and 2011 Shinmoedake volcanoes). Volcanic ash detection products based on the Moderate Resolution Imaging Spectro-radiometer (MODIS) observation data using infrared brightness temperature difference technique were compared to the forward air mass trajectory analysis by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. There was good correlation between MODIS volcanic ash image and trajectory lines after the volcanic eruptions, which support the feasibility of using the integration of satellite observed and model derived data for volcanic ash forecasting.