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\begin{document}

\title{Generating Daily Gap-filled BRDF Adjusted Surface Reflectance Products
with 10 m Resolution Using Geostationary Satellite}



\author[1]{Juwon Kong}%
\author[1]{Youngryel Ryu}%
\author[1]{Sungchan Jeong}%
\author[1]{Wonseok Choi}%
\author[1]{Henock Mamo}%
\affil[1]{Seoul National University}%


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  \date{June 13, 2024}


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\begin{abstract}
Continuous observations from geostationary satellites have been utilized
to understand land surface seasonal dynamics and fill data gaps caused
by clouds. However, the limited spatial resolution of geostationary
satellite products constrained the processes of detecting the
terrestrial changes in landscape scale, particularly over heterogeneous
areas. Moreover, the variation of sun-target-sensor geometry in
geostationary satellites results in diurnal changes in surface
reflectance products. To overcome the limitations of geostationary
satellite products over heterogeneous areas, we conducted the series of
processes: 1) characterizing the effect of the solar and viewing
geometry in surface reflectance using the bidirectional reflectance
distribution function (BRDF), 2) harmonizing the satellite products from
different platforms into a seamless product, and 3) fusing the different
satellite products to enhance the spatial resolution of geostationary
satellite products. Finally, we adopted spatial and temporal gap-filling
methods to achieve daily gap-filled surface reflectance products. For
robust application, the results from the integrated process were
evaluated in both space and time using hyperspectral maps derived from
unmanned aerial vehicle (UAV) and in situ tower-based continuous
spectral measurements. We expect the geostationary satellite products
with high spatial resolution to uncover the cloud-bound areas towards
sensing the changes of the Earth in space and time.%
\end{abstract}%



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