Abstract
A new approach for the analysis of empirical phenological data is presented which supports oligofactorial seasonality modelling. The temporal resolution of this approach is only limited by the temporal aggregation or sampling frequency (1 day, typically, in the case of weather elements) of the available primary data on the relevant environmental factors. The phenological periods of interest may be “phenologically opaque” in the sense that they do not contain any phenologically observable events except their onset and end. In traditional approaches, the available primary data are aggregated over the duration of the respective phenological period (weeks or even months, typically, in plant phenology). The new approach is supported by modern mathematical methods, which allow for data analysis under unfavourable conditions of irregular oligofactorial data design, and could thus also upgrade traditional approaches of phenological data analysis.
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Klein, G.H. Time-resolved empirical modelling of seasonal development during phenologically opaque periods. Int J Biometeorol 38, 70–77 (1995). https://doi.org/10.1007/BF01270662
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DOI: https://doi.org/10.1007/BF01270662