MODIS

A new version of MODIStsp (1.3.8) is on CRAN as of today ! The new version fixes a nasty issue introduced by changes in gdal_buildvrt behaviour in GDAL > 2.3, (https://trac.osgeo.org/gdal/ticket/3221#comment:5) which caused problems in proper application of scales and offset on MODIS layers - see https://github.com/ropensci/MODIStsp/issues/163 If you are experiencing problems with MODIStsp and you have GDAL > 2.3 on your system, you are strongly encouraged to update the package!

We are happy to report that a new version of MODIStsp (1.3.4) is on CRAN as of today ! The new version introduces a strongly improved GUI (thanks mainly to @lwasser comments in her review for MODIStsp onboarding on ropensci). The new GUI facilitates the selection of layers to be processed, and allows interactive selection of the processing spatial extent over a map (thanks to @timsalabim and @timelyportfolio for implementing some changes on mapview to allow this!

A new version of MODIStsp (1.3.3) is on CRAN as of today ! Below, you can find a short description of the main improvements. Processing speed improvements Processing of MODIS layers after download (i.e., scale and offset calibration, computation of Spectral Indexes and Quality Indicators) is now much faster. As you can see in the figure, processing time was almost halved on my (not so fast) laptop. This was achieved by modifying all computation functions so to use raster::calc() and raster::overlay() (more on this in a later post).

The MODIStsp website, which lay abandoned since several months on github pages, recently underwent a major overhaul thanks to pkgdown. The new site is now available at http://ropensci.github.io/MODIStsp/ We hope that the revised website will allow to navigate MODIStsp-related material much more easily than either github or the standard CRAN documentation, and will therefore help users in better and more easily exploiting MODIStsp functionality. The restyling was possible thanks to the very nice “pkgdown” R package (http://hadley.

We are glad to report that MODIStsp is now also available on CRAN ! From now on, you can therefore install it by simply using: install.packages("MODIStsp") In v 1.3.2 we also added the functionality to automatically apply scale and offset coefficients on MODIS original values according with the specifications of single MODIS products. Setting the new “Scale output values” option to “Yes”, scale factors and offsets are applied (if existing).

MODIStsp is a R package allowing automatic download and preprocessing of MODIS Land Products time series, available at this https://github.com/ropensci/MODIStsp github page (See also here for additional information) v1.3.1 adds functionality for processing MODIS snow cover products, accelerated download, processing specified portions of years, plus various bug fixing and improvements. MODIStsp: the main processing GUI See here for a detailed description of introduced changes We hope you will find the new version useful and that we didn’t introduce too many bugs !

MODIStsp v1.3.0 has been finally released ! It adds the much-needed functionality for downloading and preprocessing MODIS Collection 006 datasets. Off-line preprocessing of already downloaded hdf images was also improved, and the GUI was a bit revamped to improve user-friendliness (A detailed changelog can be found here). More detailed usage instructions were also added to the main github page, and a FAQ section addressing common issues with the package (e.g., installation problems, etc) was added.

In this post, we are introducing MODIStsp a new “R” package allowing to automatize the creation of time series of rasters derived from Land Products data derived from MODIS satellite data (; www.sciencedirect.com/science/article/pii/S0098300416303107). Development of MODIStsp started from modifications of the ModisDownload “R” script by Thomas Hengl (spatial-analyst.net/wiki/index.php?title=Download_and_resampling_of_MODIS_images), and successive adaptations by Babak Naimi (r-gis.net/?q=ModisDownload). Their functionalities were gradually incremented with the aim of: Developing a standalone application allowing to perform several preprocessing steps (e.