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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Data from: Learning to predict spatio-temporal movement dynamics from weather radar networks

Authors: Lippert, Fiona; Kranstauber, Bart; Forré, Patrick; van Loon, E. Emiel;

Data from: Learning to predict spatio-temporal movement dynamics from weather radar networks

Abstract

This dataset contains the following: data: preprocessed: hourly European weather radar data (here: radar) and aggregated simulation outputs (here: abm), combined with ERA5 reanalysis data and Voronoi tessellation details shapes: geographical shapes used for plotting results: trained models and corresponding results for both simulated data (here: abm) and weather radar data (here: radar). figures: final figures presented in our paper "Learning to predict spatio-temporal movement dynamics from weather radar networks" to summarize the results The corresponding code used to train and evaluate models is archived here: 10.5281/zenodo.6921595.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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BIP!Impulse provided by BIP!
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