blockCV 2.1.4-foss-2021a-R-4.1.0

Creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments; Investigating and visualising the effective range of spatial autocorrelation in continuous raster covariates to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019) .

Accessing blockCV 2.1.4-foss-2021a-R-4.1.0

To load the module for blockCV 2.1.4-foss-2021a-R-4.1.0 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):

module load blockCV/2.1.4-foss-2021a-R-4.1.0

BEAR Apps Version




The listed architectures consist of two part: OS-CPU.

  • BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
  • BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.


  • automap-1.0-16
  • blockCV 2.1.4
  • geosphere-1.5-14
  • googleVis 0.6.12
  • gstat-2.0-9
  • intervals 0.15.2
  • rgeos-0.5-9
  • sp-1.4-6
  • spacetime-1.2-6

More Information

For more information visit the blockCV website.


This version of blockCV has a direct dependency on: foss/2021a R/4.1.0-foss-2021a rgdal/1.5-23-foss-2021a-R-4.1.0

Last modified on 13th April 2022