EXPLORING HOW DESIS IMAGERY CAN ENHANCE THE CHARACTERIZATION OF LAND SURFACE PHENOLOGIES IN MONTANE PASTURES

Abstract

Abstract. DESIS products offer information-rich images, but these data are rarely acquired for most sites. We explored how these image “jewels” fit within dense image time series of higher spatial resolution but lower spectral resolution data to enhance the characterization of the land surface phenologies exhibited by montane pastures in central Kyrgyzstan. We used surface reflectance data at 5 m spatial resolution from the French-Israeli VENμS mission over the NARYN intensive observation site from 2019 and 2020. Upon evaluating the quality of the DESIS data, we found substantial geolocation problems in multiple images and limitations in some of the Quality-2 masks. Here we have reported on these problems and focused analysis on the DESIS images from 2020 that substantially overlap the NARYN footprint, occurred during the growing season, and had sufficiently low cloud cover to enable comparisons. We calculated multiple vegetation indices enabled by the spectral resolution of the VENμS bands, having averaged the DESIS bands to correspond to the VENμS bands. Of the 12 ground locations we had sampled in July 2021, just four locations had sufficient DESIS data in 2020 to characterize the growing season. Comparison of the higher spatio-temporal resolution of the VENμS data with the lower spatio-temporal resolution of the DESIS data revealed that DESIS can capture the broad outlines of land surface phenology and spatial heterogeneity of the landscape with responses comparable to VENμS, but it could not reveal the finer temporal resolution of transhumance dynamics. DESIS data merit further analysis in other highland pasture areas.