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A new version of MODIStsp (1.3.9) is on CRAN as of today !

This version:

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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!

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We are sorry to report that we recently discovered a nasty bug (or rather, a stupid mistake…) in the MODIStsp package. The bug led to improper computation of custom spectral indices in the case that their formula included addition or subtraction operations on reflectance values (e.g., something like \(\frac{(\rho_{NIR}+0.1)}{\rho_{Red}}\), with \(\rho\) indicating a reflectance). What is affected Values of the following Additional Spectral Indices selectable using the MODIStsp GUI:

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We are happy to report that our MODIStsp package for automatic preprocessing of MODIS time series has been recently approved for being included in the rOpenSci ecosystem of R packages for reproducible science! We wish to thank reviewers Leah Wasser and Jeffrey Hanson for providing really valuable insights during the onboarding review process. We think their contribution really helped in improving the package! Please also note that MODIStsp website was also migrated, and is now available at http://ropensci.

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Selected Publications

(2018). Analysing spatial–temporal changes in rice cultivation practices in the Senegal River Valley using MODIS time-series and the PhenoRice algorithm. International Journal of Applied Earth Observation and Geoinformation, (75), pp. 15-28, https://doi.org/10.1016/j.jag.2018.09.016.

(2017). Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (10), 12, pp. 5423-5441, https://doi.org/10.1109/JSTARS.2017.2679159.

(2017). PhenoRice: A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series. Remote Sensing of Environment, (194), pp. 347-365, https://doi.org/10.1016/j.rse.2017.03.029.

Recent Publications

More Publications

. A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUMETSAT Polar System. Remote Sensing, (10), 5, https://doi.org/10.3390/rs10020293, 2018.

. A high-resolution, integrated system for rice yield forecasting at district level. Remote Sensing, (10), 5, https://doi.org/10.1016/j.agsy.2018.05.007, 2018.

. Analysing spatial–temporal changes in rice cultivation practices in the Senegal River Valley using MODIS time-series and the PhenoRice algorithm. International Journal of Applied Earth Observation and Geoinformation, (75), pp. 15-28, https://doi.org/10.1016/j.jag.2018.09.016, 2018.

. Early season weed mapping in rice crops using multi-spectral UAV data. International Journal of Remote Sensing, pp. 1-21, https://doi.org/10.1080/01431161.2018.1441569, 2018.

Projects

MODIStsp

An R package for automatic download and preprocessing of MODIS Land Products Time Series

SPRAWL

sprawl - Spatial Processing (in) R: Amorphous Wrappers Library