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dc.contributor.authorKEMPENEERS PIETERen_GB
dc.contributor.authorPESEK ONDREJen_GB
dc.contributor.authorDE MARCHI DAVIDEen_GB
dc.contributor.authorSOILLE PIERREen_GB
dc.date.accessioned2019-11-29T01:19:12Z-
dc.date.available2019-11-28en_GB
dc.date.available2019-11-29T01:19:12Z-
dc.date.created2019-11-25en_GB
dc.date.issued2019en_GB
dc.date.submitted2019-10-11en_GB
dc.identifier.citationISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION vol. 8 no. 10 p. 1-14en_GB
dc.identifier.issn2220-9964 (online)en_GB
dc.identifier.urihttps://www.mdpi.com/2220-9964/8/10/461en_GB
dc.identifier.urihttps://publications.jrc.ec.europa.eu/repository/handle/JRC118210-
dc.description.abstractA new Python package, pyjeo, that deals with the analysis of geospatial data has been created by the JRC. Adopting the principles of open science, the JRC strives at transparency and reproducibility of results. In this view, it has been decided to release pyjeo as free and open software. This paper describes the design of pyjeo and how its underlying C/C++ library was ported to Python. Strengths and limitations of the design choices are discussed. In particular the data model that allows the generation of on-the-fly data cubes is of importance. Two uses cases illustrate how pyjeo can contribute to open science. The first is an example of large scale processing, where pyjeo was used to create a global composite of Sentinel-2 data. The second shows how pyjeo can be imported within an interactive platform for image analysis and visualization. Using an innovative mechanism that interprets Python code within a C++ library on-the-fly, users can benefit from all functions in the pyjeo package. Images are processed in deferred mode, which is ideal for prototyping new algorithms on geospatial data and assess the suitability of the results created on the fly at any scale and location.en_GB
dc.description.sponsorshipJRC.I.3-Text and Data Miningen_GB
dc.format.mediumOnlineen_GB
dc.languageENGen_GB
dc.publisherMDPIen_GB
dc.relation.ispartofseriesJRC118210en_GB
dc.titlepyjeo: A Python Package For The Analysis Of Geospatial Dataen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.3390/ijgi8100461 (online)en_GB
JRC Directorate:Joint Research Centre Corporate Activities

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