Checking the Consistency of Volunteered Phenological Observations While Analysing Their Synchrony

Abstract

The increasing availability of volunteered geographic information (VGI) enables novel studies in many scientific domains. However, inconsistent VGI can negatively affect these studies. This paper describes a workflow that checks the consistency of Volunteered Phenological Observations (VPOs) while considering the synchrony of observations (i.e., the temporal dispersion of a phenological event). The geographic coordinates, day of the year (DOY) of the observed event, and the accumulation of daily temperature until that DOY were used to: (1) spatially group VPOs by connecting observations that are near to each other, (2) define consistency constraints, (3) check the consistency of VPOs by evaluating the defined constraints, and (4) optimize the constraints by analysing the effect of inconsistent VPOs on the synchrony models derived from the observations. This workflow was tested using VPOs collected in the Netherlands during the period 2003⁻2015. We found that the average percentage of inconsistent observations was low to moderate (ranging from 1% for wood anemone and pedunculate oak to 15% for cow parsley species). This indicates that volunteers provide reliable phenological information. We also found a significant correlation between the standard deviation of DOY of the observed events and the accumulation of daily temperature (with correlation coefficients ranging from 0.78 for lesser celandine, and 0.60 for pedunculate oak). This confirmed that colder days in late winter and early spring lead to synchronous flowering and leafing onsets. Our results highlighted the potential of synchrony information and geographical context for checking the consistency of phenological VGI. Other domains using VGI can adapt this geocomputational workflow to check the consistency of their data, and hence the robustness of their analyses.

Keywords

• volunteered geographical information
• citizen science
• climate change
• phenology
• synchrony
• geocomputation
• data quality
• constraint satisfaction