日本地球惑星科学連合2023年大会

講演情報

[E] 口頭発表

セッション記号 M (領域外・複数領域) » M-AG 応用地球科学

[M-AG33] Satellite Land Physical Processes Monitoring at Medium/High/Very High Resolution

2023年5月24日(水) 09:00 〜 10:15 103 (幕張メッセ国際会議場)

コンビーナ:Jean-Claude Roger(University of Maryland College Park)、Shinichi Sobue(Japan Aerospace Exploration Agency)、Eric Vermote(NASA Goddard Space Flight Center)、Ferran Gascon(European Space Agency)、Chairperson:Jean-Claude Roger(University of Maryland College Park)、Eric Vermote(NASA Goddard Space Flight Center)

09:15 〜 09:30

[MAG33-02] Toward a Consistent Data Records from Coarse, Medium and High Spatial Resolution Earth Observation Satellites
Toward a Consistent Data Records from Coarse, Medium and High Spatial Resolution Earth Observation Satellites

*Eric Vermote1、Sergii Skakun2,1、Jean-Claude Roger1,2 (1.NASA Goddard Space Flight Center、2.University of Maryland, Dept. of Geographical Sciences)

キーワード:fundamental earth observation data record, remote sensing, atmospheric correction, validation, consitency/interoperability, climate data record

Surface reflectance is one of the key products used in developing several higher-order land products, such as Vegetation Indices, Albedo and LAI/FPAR, it is therefore seminal to detecting trends in the biosphere and land surface and has been classed by NOAA as a “Fundamental Climate Data Record (FDCR) for Land”. Building a long-term surface reflectance data record of climate quality implies combining different instruments, sensors and satellites, accounting for different spatial resolutions and spectral characteristics, assuring consistent calibration, and correcting for atmospheric and directional effects. As the spatial resolution issue is addressed by aggregating the original data to a resolution still suitable for climate studies (e.g. 0.05 degree latitude, longitude), the instrument calibration becomes the first major hurdle one has to go through before being able to proceed any further.

In this work, we are using robust reflectance data records and inter-comparison methods that we have developed over the past several years (consisting of atmospheric correction, cloud screening, directional effect correction and spectral normalization) to establish and verify the inter-consistency of the reflectance products from the AVHRR sensors on-board NOAA 7, 9, 11, 14, 16, 17 and 18, the MODIS sensors on-board Aqua and Terra and the VIIRS sensors on-board Suomi-NPP and JPSS1 as well as OLCI/SLSTR from Sentinel 3. These approaches are also applied to high spatial resolution dataset from Landsat 8, Sentinel 2A, 2B and Planet Lab.