updated RStoolbox version

updated RStoolbox version

January 29, 2016

The RStoolbox R package has been updated after some testing in courses and by colleagues. Please update your package using update.packages() or install the RStoolbox again.

New functions are:

  • new function `validateMap()` for assessing map accuracy separately from model fitting, e.g. after majority or MMU filtering
  • new function `getValidation()` to extract specific validation results of superClass objects (proposed by James Duffy)
  • new spectral index NDVIc (proposed by Jeff Evans)
  • new argument scaleFactor for `spectralIndices()` for calculation of EVI/EVI2 based on scaled reflectance values
  • implemented dark object subtraction radCor(..,method=’sdos’) for Landsat 8 data (@BayAludra, #4)

various changes were applied:

  • superClass() based on polygons now considers only pixels which have their center coordinate within a polygon
  • rasterCVA() now returns angles from 0 to 360° instead of 0:45 by quadrant (reported by Martin Wegmann and explained here)
  • improved dark object DN estimation based on maximum slope of the histogram in `estimateHaze` (@BayAludra, #4)

And some bugs fixed:

  • superClass() failed when neither valData or trainPartition was specified. regression introduced in 0.1.3 (reported by Anna Stephani)
  • spectralIndices() valid value range of EVI/EVI2 now [-1,1]
  • radCor() returned smallest integer instead of NA for some NA pixels
  • fix ‘sdos’ for non-contiguous bands in radCor (@BayAludra, #4)

you may also like:

Visit at the Institute for Geoinformatics (IFGI) at University of Münster

Visit at the Institute for Geoinformatics (IFGI) at University of Münster

Two days ago, our PostDoc Dr. Jakob Schwalb-Willmann visited the Institute for Geoinformatics at University of Münster to give a talk at IFGI’s GI Forum titled “Can animals be used to classify land use? Employing movement-tracked animals as environmental informants using deep learning”.

EOCap4Africa training in Ruhengeri

EOCap4Africa training in Ruhengeri

This week, over 25 students are attending a training session at the Institute of Applied Sciences (INES) in Ruhengeri, Rwanda, using the MSc module on Remote Sensing for Biodiversity Conservation that we developed. This module is part of the EOCap4Africa project...