Thursday, 09 April 2020 08:20

Processing Sentinel-2 data in R using sen2r: the paper published by "Computers & Geosciences"

computers geosciencessen2r is an R package developed by the Institute of Remote Sensing of Environment (IREA) of the Italian National Research Council, with the aim to simplify and speed up several steps commonly needed to process Sentinel-2 data. Recently, an important recognition to the worth and usefulness of this tool came from the ISI journal Computers & Geosciences, publishing the scientific paper “sen2r”: An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data.

Up to the 14th of May 2020, it is possible to get free access to the manuscript at this link:

sen2r gui2The paper provides an overview of the functionalities of the package: the steps performed by a standard processing chain are described, from the search and download of the available Sentinel-2 products over an area of interest and in a specific time window, to the actual preprocessing operations (clipping, reshaping and reprojecting, masking clouds, computing spectral indices and RGB images), to the description of the package operation through graphical user interface or command line instructions. Further details can be found at this link.

Last section of the manuscript shows a real sen2r use case as Service-Oriented Architecture backend, implemented in the framework of the SATURNO project, devoted to demonstrate a precision farming service infrastructure. This example illustrates how the package can be used, by defining and scheduling a custom processing chain, to provide added value information to end-users on the project geoportal

sen2r is released with license GNU GPL-3, so it can be freely accessed and modified by users. The complete reference to the article, here reported, is to be used in scientific works that exploit the package:

L. Ranghetti, M. Boschetti, F. Nutini, L. Busetto (2020). “sen2r: An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data”. Computers & Geosciences, 139, 104473. DOI: 10.1016/j.cageo.2020. 104473, URL:


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