JpGU-AGU Joint Meeting 2017

講演情報

[EE] 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] [EE] Satellite Land Surface Reflectance at Medium/High Resolution: Algorithms, Validation & Applications

2017年5月22日(月) 15:30 〜 17:00 201A (国際会議場 2F)

コンビーナ:Jean-Claude Roger(University of Maryland College Park)、Eric Vermote(NASA Goddard Space Flight Center)、祖父江 真一(宇宙航空研究開発機構)、Ferran Gascon(European Space Agency (ESA))、座長:Roger Jean-Claude(University of Maryland College Park)、座長:祖父江 真一(宇宙航空研究開発機構)、座長:Vermote Eric(NASA Goddard Space Flight Center)

16:30 〜 16:45

[MAG33-04] A Generic Approach For Inversion And Validation Of Surface Reflectance Over Land: Application To Landsat 8 And Sentinel 2.

*Eric Vermote1Jean-Claude Roger2sergii skakun2belen franch2 (1.NASA Goddard Space Flight Center / Code 619、2.University of Maryland / Department of Geographical Sciences)

キーワード:radiative transfer, aerosol, surface reflectance

This paper presents a generic approach developed to derive surface reflectance over land from a variety of sensors. This method relies on the inversion of the radiative transfer equation in the Lambertian case, with no adjacency effects, that account for a simplified coupling of the absorption by atmospheric gases and scattering by molecules and aerosols as implemented in the 6SV radiative transfer code. The processing code relies on look-up tables generated by 6SV, for which the accuracy (~1%) has been well documented in several papers. The code uses ancillary data such as pressure and gas concentrations but relies on a per pixel inversion of the aerosol properties to assure the best possible accuracy for the surface reflectance, as aerosols can be highly variable both in space and time. This new aerosol inversion builds on the extensive dataset acquired by the Terra platform, combining MODIS and MISR to derive an explicit and dynamic map of band ratio’s between blue and red channels and is a refinement of the operational approach used for MODIS and LANDSAT over the past 15 years. The aerosol inversion is generic and applicable to a variety of sensors. We use this approach to derive Landsat 8 and Sentinel 2 surface reflectance products. We then present the validation approach and results using AERONET data. Finally, we conclude by analyzing the consistency of the time-series of surface reflectance combining both sensors over agricultural areas and exploring the potential application of this new product.