Package: dissever 0.2-3.9000

dissever: Spatial Downscaling using the Dissever Algorithm

Spatial downscaling of coarse grid mapping to fine grid mapping using predictive covariates and a model fitted using the 'caret' package. The original dissever algorithm was published by Malone et al. (2012) <doi:10.1016/j.cageo.2011.08.021>, and extended by Roudier et al. (2017) <doi:10.1016/j.compag.2017.08.021>.

Authors:Pierre Roudier [cre, aut], Brendan Malone [ctb]

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dissever.pdf |dissever.html
dissever/json (API)

# Install 'dissever' in R:
install.packages('dissever', repos = c('https://pierreroudier.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/pierreroudier/dissever/issues

Datasets:
  • edgeroi - Subset of the 1-km resolution soil carbon map and selected subset of environmental covariates for the Edgeroi District, NSW

On CRAN:

4.70 score 10 stars 6 scripts 167 downloads 5 exports 81 dependencies

Last updated 4 years agofrom:37441ee1cc. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-winOKNov 04 2024
R-4.5-linuxOKNov 04 2024
R-4.4-winOKNov 04 2024
R-4.4-macOKNov 04 2024
R-4.3-winOKNov 04 2024
R-4.3-macOKNov 04 2024

Exports:dissevergenerate_ciplot.disseverprint.disseversummary.dissever

Dependencies:bootcaretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergridExtragtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6rasterRColorBrewerRcpprecipesreshape2rlangrpartscalesshapespSQUAREMstringistringrsurvivalterratibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisviridisLitewithr

Dissever Tutorial

Rendered fromdissever-demo.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2017-12-11
Started: 2015-09-29