pyjeo: A Python Package for the Analysis of Geospatial Data
A new Python package, pyjeo, that deals with the analysis of geospatial data has been created by the Joint Research Centre (JRC). Adopting the principles of open science, the JRC strives for transparency and reproducibility of results. In this view, it has been decided to release pyjeo as free and o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-10-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/8/10/461 |
| _version_ | 1818944715556388864 |
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| author | Pieter Kempeneers Ondrej Pesek Davide De Marchi Pierre Soille |
| author_facet | Pieter Kempeneers Ondrej Pesek Davide De Marchi Pierre Soille |
| author_sort | Pieter Kempeneers |
| collection | DOAJ |
| description | A new Python package, pyjeo, that deals with the analysis of geospatial data has been created by the Joint Research Centre (JRC). Adopting the principles of open science, the JRC strives for 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. |
| first_indexed | 2024-12-20T07:47:38Z |
| format | Article |
| id | doaj.art-352223c398b04d87ade0a49b91244b53 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-20T07:47:38Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-352223c398b04d87ade0a49b91244b532022-12-21T19:47:55ZengMDPI AGISPRS International Journal of Geo-Information2220-99642019-10-0181046110.3390/ijgi8100461ijgi8100461pyjeo: A Python Package for the Analysis of Geospatial DataPieter Kempeneers0Ondrej Pesek1Davide De Marchi2Pierre Soille3Joint Research Centre of the European Commission, Via E. Fermi 2749, I-21027 Ispra, ItalyDepartment of Geomatics, Czech Faculty of Civil Engineering, Technical University in Prague, CZ-16629 Prague, Czech RepublicJoint Research Centre of the European Commission, Via E. Fermi 2749, I-21027 Ispra, ItalyJoint Research Centre of the European Commission, Via E. Fermi 2749, I-21027 Ispra, ItalyA new Python package, pyjeo, that deals with the analysis of geospatial data has been created by the Joint Research Centre (JRC). Adopting the principles of open science, the JRC strives for 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.https://www.mdpi.com/2220-9964/8/10/461open-source softwaregeospatial dataimage processing |
| spellingShingle | Pieter Kempeneers Ondrej Pesek Davide De Marchi Pierre Soille pyjeo: A Python Package for the Analysis of Geospatial Data ISPRS International Journal of Geo-Information open-source software geospatial data image processing |
| title | pyjeo: A Python Package for the Analysis of Geospatial Data |
| title_full | pyjeo: A Python Package for the Analysis of Geospatial Data |
| title_fullStr | pyjeo: A Python Package for the Analysis of Geospatial Data |
| title_full_unstemmed | pyjeo: A Python Package for the Analysis of Geospatial Data |
| title_short | pyjeo: A Python Package for the Analysis of Geospatial Data |
| title_sort | pyjeo a python package for the analysis of geospatial data |
| topic | open-source software geospatial data image processing |
| url | https://www.mdpi.com/2220-9964/8/10/461 |
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