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Preprints

Filtering by Subject: Software Engineering

theRmalUAV: an R package to clean and correct thermal UAV data for accurate land surface temperatures

Christophe Metsu, Wouter H. Maes, Sam Ottoy, et al.

Published: 2025-02-28
Subjects: Agricultural Science, Climate, Environmental Monitoring, Software Engineering

Thermal cameras mounted on unoccupied aerial vehicles (UAVs) are increasingly utilized across various environmental research fields, including hydrological modelling, wildfire detection, urban heat island studies, microclimate and precision agriculture. However, several steps are needed to convert the measured thermal signal to more relevant land surface temperature (LST). Since a number of users [...]

Ten Simple Rules to build a Model Life Cycle

Timothée Poisot, Daniel J Becker, Cole B Brookson, et al.

Published: 2024-02-09
Subjects: Bioinformatics, Ecology and Evolutionary Biology, Software Engineering

Just like data, models have their own life cycle. By recognizing how one’s model fits within the life cycle of the data (or at least, ensuring that the model life cycle is understood), we can identify opportunities to foster new collaborations, encourage better practices in data analysis, and ultimately accelerate research. In this manuscript, we introduce the Model Life Cycle and develop a [...]

Phyloreferences: Tree-Native, Reproducible, and Machine-Interpretable Taxon Concepts

Nico Cellinese, Stijn Conix, Hilmar Lapp

Published: 2021-03-05
Subjects: Biodiversity, Bioinformatics, Computer Sciences, Databases and Information Systems, Ecology and Evolutionary Biology, Engineering, Life Sciences, Other Ecology and Evolutionary Biology, Physical Sciences and Mathematics, Software Engineering

Evolutionary and organismal biology have become inundated with data. At the same rate, we are experiencing a surge in broader evolutionary and ecological syntheses for which tree-thinking is the staple for a variety of post-tree analyses. To fully take advantage of this wealth of data to discover and understand large-scale evolutionary and ecological patterns, computational data integration, i.e. [...]

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