Počet záznamů: 1  

Data pro článek. Reliability of fire danger forecasts for Czech agricultural and forestry landscapes

  1. 1.
    Kudláčková, Lucie

    Data pro článek. Reliability of fire danger forecasts for Czech agricultural and forestry landscapes.
    [Data for the article. Reliability of fire danger forecasts for Czech agricultural and forestry landscapes.]

    Popis: This dataset encompasses analytical outputs evaluating the reliability of fire danger forecasts in the Czech Republic using the Canadian Fire Weather Index (FWI) and the Australian Forest Fire Danger Index (FFDI). The dataset includes seasonal distributions of wildfire occurrences from 2018 to 2022, highlighting the bimodal nature of fire seasons with peaks in spring and summer. It provides comparative analyses of FWI and FFDI values. Linear regression models estimating fire occurrences based on individual and combined index values are presented. Inclusion of random effects to account for regional variability (NUTS 3 level) further enhances prediction accuracy. Additionally, the dataset assesses the performance of five numerical weather prediction models in forecasting fire danger, identifying the IFS model as the most suitable for Czech conditions and dataset provides information about fire occurrence stratified by land cover type, distinguishing agricultural areas and forested landscapes.
    [This dataset encompasses analytical outputs evaluating the reliability of fire danger forecasts in the Czech Republic using the Canadian Fire Weather Index (FWI) and the Australian Forest Fire Danger Index (FFDI). The dataset includes seasonal distributions of wildfire occurrences from 2018 to 2022, highlighting the bimodal nature of fire seasons with peaks in spring and summer. It provides comparative analyses of FWI and FFDI values. Linear regression models estimating fire occurrences based on individual and combined index values are presented. Inclusion of random effects to account for regional variability (NUTS 3 level) further enhances prediction accuracy. Additionally, the dataset assesses the performance of five numerical weather prediction models in forecasting fire danger, identifying the IFS model as the most suitable for Czech conditions and dataset provides information about fire occurrence stratified by land cover type, distinguishing agricultural areas and forested landscapes.]

    Institucionální podpora: RVO:86652079
    Obor OECD: Climatic research
    DOI: https://doi.org/10.57680/asep.0619176
    https://hdl.handle.net/11104/0366076
Počet záznamů: 1  

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