20.500.12556/DiRROS-14274 Empirical approach for modelling tree phenology in mixed forests using remote sensing : Phenological events are good indicators of the effects of climate change, since phenological phases are sensitive to changes in environmental conditions. Although several national phenological networks monitor the phenology of different plant species, direct observations can only be conducted on individual trees, which cannot be easily extended over large and continuous areas. Remote sensing has often been applied to model phenology for large areas, focusing mostly on pure forests in which it is relatively easier to match vegetation indices with ground observations. In mixed forests, phenology modelling from remote sensing is often limited to land surface phenology, which consists of an overall phenology of all tree species present in a pixel. The potential of remote sensing for modelling the phenology of individual tree species in mixed forests remains underexplored. In this study, we applied the seasonal midpoint (SM) method with MODIS GPP to model the start of season (SOS) and the end of season (EOS) of six different tree species in Slovenian mixed forests. First, substitute locations were identified for each combination of observation station and plant species based on similar environmental conditions (aspect, slope, and altitude) and tree species of interest, and used to retrieve the remote sensing information used in the SM method after fitting the best of a Gaussian and two double logistic functions to each year of GPP time series. Then, the best thresholds were identified for SOS and EOS, and the results were validated using cross-validation. The results show clearly that the usual threshold of 0.5 is not best in most cases, especially for estimating the EOS. Despite the difficulty in modelling the phenology of different tree species in a mixed forest using remote sensing, it was possible to estimate SOS and EOS with moderate errors as low as <8 days (Fagus sylvatica and Tilia sp.) and <10 days (Fagus sylvatica and Populus tremula), respectively. phenology modelling start of season end of season remote sensing MODIS GPP vegetation indices threshold methods fenološko modeliranje daljinsko zaznavanje MODIS GPP vegetacijski indekki true false true Angleški jezik Ni določen Neznano 2021-08-23 12:45:55 2021-08-23 12:45:57 2022-08-20 03:34:38 0000-00-00 00:00:00 2021 0 0 Nasl. z nasl. zaslona; Opis vira z dne 19. 8. 2021; 15 str. iss. 15 Vol. 13 2021 0000-00-00 Zaloznikova Objavljeno apc 0000-00-00 0000-00-00 0000-00-00 630*18 2072-4292 10.3390/rs13153015 73513731 RAZ_Noumonvi_Koffi_Dodji_i2021.pdf RAZ_Noumonvi_Koffi_Dodji_i2021.pdf 1 D36692496B5256672038F0A54E28AC89 9b21a7c26fe1fe5f0e2de2df02b49700151a920bf557ce2bda284825aeb1b347 aa922717-17b6-11ed-b6b8-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=17937 https://www.mdpi.com/2072-4292/13/15/3015 1 https://dirros.openscience.si/Dokument.php?lang=slv&id=17936 Gozdarski inštitut Slovenije 0 0 0