"sen2r": An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data. (June 2020)
- Record Type:
- Journal Article
- Title:
- "sen2r": An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data. (June 2020)
- Main Title:
- "sen2r": An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data
- Authors:
- Ranghetti, Luigi
Boschetti, Mirco
Nutini, Francesco
Busetto, Lorenzo - Abstract:
- Abstract: sen2r is a scalable and flexible R package to enable downloading and preprocessing of Sentinel-2 satellite imagery via an accessible and easy to install interface. It allows the execution of several preprocessing steps which are commonly performed by Sentinel-2 users: searching the Sentinel-2 archive for datasets available over a spatial area of interest and in a defined time window, downloading them, applying the Sen2Cor atmospheric correction algorithm to compute surface reflectances, merging adjacent tiles, performing geometric transformations, applying a cloud mask, computing spectral indices and colour images. The package is designed to be accessible to a range of users, from beginners to skilled R users. It comes with a Graphical User Interface, which can be used to set the processing parameters and launch processing operations: this feature makes sen2r accessible also for novices with limited programming experience. High-level R functions, which enable customised image processing workflows and control over intermediate steps, can be useful to experienced remote sensing researchers. Thanks to those functions it is possible to easily schedule automatic processing chains, so to manage massive processing operations. This paper describes the main characteristics, functionalities and performance of the package and highlights its usefulness as the operational back-end of service-oriented architectures, as illustrated by the Saturno project. Highlights: We presentAbstract: sen2r is a scalable and flexible R package to enable downloading and preprocessing of Sentinel-2 satellite imagery via an accessible and easy to install interface. It allows the execution of several preprocessing steps which are commonly performed by Sentinel-2 users: searching the Sentinel-2 archive for datasets available over a spatial area of interest and in a defined time window, downloading them, applying the Sen2Cor atmospheric correction algorithm to compute surface reflectances, merging adjacent tiles, performing geometric transformations, applying a cloud mask, computing spectral indices and colour images. The package is designed to be accessible to a range of users, from beginners to skilled R users. It comes with a Graphical User Interface, which can be used to set the processing parameters and launch processing operations: this feature makes sen2r accessible also for novices with limited programming experience. High-level R functions, which enable customised image processing workflows and control over intermediate steps, can be useful to experienced remote sensing researchers. Thanks to those functions it is possible to easily schedule automatic processing chains, so to manage massive processing operations. This paper describes the main characteristics, functionalities and performance of the package and highlights its usefulness as the operational back-end of service-oriented architectures, as illustrated by the Saturno project. Highlights: We present sen2r, an R package devoted to download and preprocess Sentinel-2 data. A Graphical User Interface facilitates settings the processing parameters. sen2r can be used to automatically keep a Sentinel-2 archive updated. A case study for precision farming applications is described. … (more)
- Is Part Of:
- Computers & geosciences. Volume 139(2020)
- Journal:
- Computers & geosciences
- Issue:
- Volume 139(2020)
- Issue Display:
- Volume 139, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 139
- Issue:
- 2020
- Issue Sort Value:
- 2020-0139-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-06
- Subjects:
- Data processing -- Software engineering -- Parallel and high-performance computing -- Remote sensing
Environmental policy -- Periodicals
550.5 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00983004 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cageo.2020.104473 ↗
- Languages:
- English
- ISSNs:
- 0098-3004
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.695000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13414.xml