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Shiny GUI for Spatial Interpolation


Find, Download and Process Sentinel-2 Data

Recent Publications

(2019). Scaricare e processare automaticamente i dati Sentinel-2 in R: il nuovo pacchetto "sen2r". XX Meeting degli utenti italiani di GRASS e GFOSS (Foss4G-IT 2019), Padova, 21-22/02/2019.

Recent & Upcoming Talks

sen2r ( è un pacchetto R sviluppato nell’ottica di facilitare, velocizzare ed eventualmente …

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Do you need to perform a spatial interpolation on point data using an interactive graphical interface? You can exploit GUInterp: try it at; install the {guinterp} package with the command remotes::install_github("ranghetti/guinterp"); launch guinterp::guinterp(); enjoy. A typical spatial interpolation workflow includes common steps: loading point data; filtering them to exclude undesired outlier values; setting the interpolation method and parameters; defining an output raster grid; processing data.


sen2r 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.


Until August 2019, all Sentinel-2 satellite data could be directly downloaded from the ESA Data Hub, both through the interactive Open Hub or using an API interface. Recently this policy was changed: typically, only the most recent products are available for direct download, while the oldest ones (level 2A archives older than 18 months and level 1C older than one year) are stored in the so called Long Term Archive, and must be ordered by the user; then, they are made available for download after a while (no messages are sent to the user).


The availability of Sentinel-2 satellite data has been a turning point for a widespread kind of users, which can now take advantage from a dataset sufficiently dense (revisiting time of 5 days) to perform time series analysis, and which is characterised by a decametric resolution that allows to discriminate many natural and agronomic targets. Data access is free (upon registration to ESA data hub). Although many solutions are available to obtain images (a detailed list is available here), R users should download them manually (or using ESA API Hub) and then perform some preprocessing operations before being able to use them (e.



  • CNR-IREA, Via Corti 12, 20133 Milano, Italy
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