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Handling large geo data with Julia

Authors: Felix Cremer;

Handling large geo data with Julia

Abstract

This talk is part of the Pangeo Show & Tell series and was given on September 1st 2022 by Felix Cremer. Bio Felix Cremer received his diploma in mathematics from the University of Leipzig in 2014. In 2016 he started his PhD study on time series analysis of hypertemporal Sentinel-1 radar data. He currently works at the Max-Planck-Institute for Biogeochemistry on the development of the JuliaDataCubes ecosystem in the scope of the NFDI4Earth 5 project. Abstract The Earth Data Lab (EDL) is a data cube framework in Julia for the efficient handling of raster data. It is based on the YAXArrays.jl package. YAXArrays.jl provides functionality to deal with labelled arrays, similar to the xarray python package and it also provides efficient and easy multithreading and distributed computation of user defined functions along arbitrary slices of the data. EarthDataLab.jl uses DiskArrays.jl in the backend to deal with out of memory datasets. In this Show-and-Tell Felix is going to give a short introduction into the EarthDataLab.jl package for raster data handling in Julia.

Keywords

Earth sciences, Applied sciences

EOSC Subjects

RO-crate, Jupyter Notebook

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average