• Title/Summary/Keyword: 태양 에너지 예측

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The Tendency Analysis of Albedo by Land Cover Over Northeast Asia Using MODIS 16-Day Composited Albedo data (MODIS 16-Day Albedo 자료를 이용한 동북아시아 지역의 토지피복 별 알베도 변화 분석)

  • Park, Eun-Bin;Han, Kyung-Soo;Lee, Chang-Suk;Pi, Kyung-Jin
    • Korean Journal of Remote Sensing
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    • v.28 no.5
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    • pp.501-508
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    • 2012
  • Albedo is known as a factor that directly impacts on the surface energy balance one of the elements of earth radiation balance. The change of albedo includes the change of soil moisture, vegetation, solar zenith angle, snow, and so on. In addition, it operates as a crucial path to understanding feedback mechanisms between radiation balance and its influence on climate and vegetation dynamics and therefore, observing the variation of albedo is a one of the essential procedures for anticipating climate change. In this study, we used MODIS 16-Day composited Albedo data from 2001 to 2011 years with the purpose of observing the change of albedo over Northeast Asia. According to the tendency of albedo for 11 years, albedo in the area of an active vegetation has increased in near-infrared (NIR) domain and decreased in visible (VIS) domain. On the basis of local changes in vegetation in 2002, the both area of the Gobi Desert and the Manchuria was enormously changed and chosen the research area and furthermore, the vegetation of both regions had deteriorated due to the change of the minimum value since 2010.

An Improved Validation Technique for the Temporal Discrepancy when Estimated Solar Surface Insolation Compare with Ground-based Pyranometer: MTSAT-1R Data use (표면도달일사량 검증 시 발생하는 시간 불일치 조정을 통한 정확한 일사량 검증: MTSAT-1R 자료 이용)

  • Yeom, Jong-Min;Han, Kyung-Soo;Lee, Chang-Suk;Kim, Do-Yong
    • Korean Journal of Remote Sensing
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    • v.24 no.6
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    • pp.605-612
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    • 2008
  • In this study, we estimate solar surface insolation (SSI) by using physical methods with MTSAT-1R data. SSI is regarded as crucial parameter when interpreting solar-earth energy system, climate change, and agricultural production predict application. Most of SSI estimation model mainly uses ground based-measurement such as pyranometer to tune the constructed model and to validate retrieved SSI data from optical channels. When compared estimated SSI with pyranometer measurements, there are some systemic differences between those instruments. The pyranometer data observed upward-looking hemispherical solid angle and distributed hourly measurements data which are averaged every 2 minute instantaneous observation. Whereas MTSAT-1R channels data are taken instantaneously images at fixed measurement time over scan area, and are pixel-based observation with a much smaller solid angle view. Those temporal discrepancies result from systemic differences can induce validation error. In this study, we adjust hour when estimate SSI to improve the retrieved accurate SSI.