UVA_VPTS - Vertical profiles of biological targets derived from weather radars in Belgium, Germany and the Netherlands (Q6338)
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Dataset published at Zenodo repository.
Language | Label | Description | Also known as |
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English | UVA_VPTS - Vertical profiles of biological targets derived from weather radars in Belgium, Germany and the Netherlands |
Dataset published at Zenodo repository. |
Statements
UVA_VPTS - Vertical profiles of biological targets derived from weather radars in Belgium, Germany and the Netherlands is a vertical profile time series dataset published by the Research Institute for Nature and Forest (INBO). It contains animal movement data derived from 24 weather radars in Belgium, Germany and the Netherlands, with varying coverage from 2008 to 2023. These data were created by processing weather radar data - provided by the Royal Meteorological Institute of Belgium (RMI), German Meteorological Service (DWD) and Royal Netherlands Meteorological Institute (KMNI) - with methods optimized for extracting bird targets. The resulting data are vertical profile time series (VPTS), containing the density, speed and direction of biological targets within a weather radar (radar) volume, grouped into altitude bins (height) and measured over time (datetime). The data are also available in the Aloft bucket. Files VPTS data in this deposit are organized per country (.tgz file), radar (directory), year (directory) and month (.csv.gz file). Fields in the data follow the VPTS CSV format and are described in vpts-csv-table-schema.json. An overview of what data are available is provided in coverage.csv. Radar metadata can be found athttps://aloftdata.eu/radars/. coverage.csv: coverage of the VPTS data, representing the number of unique hours, heights, source files and records for each radar and date combination. vpts-csv-table-schema.json: technical description of the fields in the VPTS data. be.tgz: VPTS data from 3 radars in Belgium. de.gz: VPTS data from 18 radars in Germany. nl.gz: VPTS data from 3 radars in the Netherlands. Acknowledgements This dataset was processed using infrastructure provided by the University of Amsterdam, SURF Cooperative, Ghent University and the Research Institute for Nature and Forest (INBO). It was mainly supported by the GloBAM project, funded through the 2017-18 Belmont Forum and BiodivERsA joint call for research proposals under the BiodivScen ERA-Net COFUND programme.
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25 January 2025
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