[A-CG36] Terrestrial monitoring using new-generation geostationary satellites

[ACG36-P04] Developing a New Vegetation Index to Monitor Spring Phenology of Deciduous Forests by the Collaboration of LEO and GEO Satellites

*Sasagawa Taiga¹, Kenlo Nasahara² (1.Graduate School of Science and Technology, University of Tsukuba, 2.Faculty of Life and Environmental Sciences, University of Tsukuba)

Keywords:Vegetation phenology, Himawari-8, GCOM-C, Phenological Eyes Network (PEN), FLiES, Leafing

Vegetation phonology plays an important role in biosphere-atmosphere-hydrosphere interactions. Satellite remote sensing techniques have provided global-scale phenology with vegetation indices such as the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Green Red Vegetation Index (GRVI). However, phenology monitoring with these vegetation indices is strongly affected by snowmelt because these vegetation indices are usually obtained from the combination of band reflectances centered on "different wavelengths," which represent not only vegetation phenology but also snowmelt. Therefore, we proposed a new vegetation index obtained from the combination of band reflectances centered on "similar wavelengths" with "different bandwidths" for robust phenology monitoring. In this research, we aimed to evaluate the availability of the vegetation index obtained from reflectances at similar wavelengths with different bandwidths (hereafter, bandwidth-based vegetation index) for monitoring the start of season (SOS) with in-situ measurements, model simulations, and actual satellite data at the Takayama site of Gifu University. We used the red-band reflectance value of GCOM-C/SGLI and Himawari-8/AHI. In-situ and simulation experiments showed that the red-band vegetation index successfully detected SOS, but the values of the red-band vegetation index were highly dependent on the satellite and sun angle. Our experiments with actual satellite data also detected the SOS without the effects of snowmelt around the Takayama site. We will continue to evaluate the bandwidth-based vegetation index in other vegetation types, such as grassland and deciduous needle-leaf forest, in the future. Our work has provided new insights into monitoring vegetation phenology using a bandwidth-based vegetation index and the availability of collaboration between low-Earth orbit satellites and geostationary satellites.