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Query: "author" (Oblišar Gal) .

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Repository of drought event impacts across the danube catchment countries between 1981 and 2016 using publicly available sources
Jiří Jakubínský, Monika Bláhová, Lenka Bartošová, Klára Steinerová, Jan Balek, Petra Dížková, Daniela Semerádová, Daniel Alexandru, Galia Bardarska, Sabina Bokal, Gregor Gregorič, Gal Oblišar, Andreja Sušnik, 2019, original scientific article

Abstract: Drought directly and indirectly affects human society in a number of ways. In many regions of the world climate change will exasperate the effects of droughts, affect national economies more intensely. The main aim of this article was to catalogue and analyze the drought impacts in the 11 Central and South Eastern European states located in the Danube river basin. The identification of dry episodes was based on information from publicly available sources, namely, newspaper and journal articles that reported drought impacts. Information on drought impact occurrences was classified into one of five defined categories in which the drought impact report was most clearly manifested (i.e., agriculture, forestry, soil systems, wildfires and hydrology). In terms of the spatial distribution of drought impacts, individual recorded events were analyzed at the level of EU NUTS regions (or their equivalent in non-EU countries). The analysis highlights country-specific vulnerability to drought. Furthermore, gradual increases in drought events and the number of reported impacts were identified, which was particularly evident in the agricultural sector.
Keywords: drought impact, Danube basin, agriculture, climate change, water stress
Published in DiRROS: 21.04.2022; Views: 790; Downloads: 355
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3.
Empirical approach for modelling tree phenology in mixed forests using remote sensing
Koffi Dodji Noumonvi, Gal Oblišar, Ana Žust, Urša Vilhar, 2021, original scientific article

Abstract: : 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.
Keywords: phenology modelling, start of season, end of season, remote sensing, MODIS GPP, vegetation indices, threshold methods
Published in DiRROS: 23.08.2021; Views: 889; Downloads: 667
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