Package: mapspam2globiom 0.0.1

Michiel van Dijk

mapspam2globiom: An R package to create crop distribution maps as input for GLOBIOM

The aim of the mapspam2globiom R package is to facilitate the creation of country level crop distribution maps, which can be used as input by the IIASA's Global Biosphere Management Model (GLOBIOM) for a selected country. mapspam2globiom includes several functions to aggregate crop distribution maps that were created with the mapspamc package (Van Dijk et al. 2022) to the GLOBIOM input format. mapspamc was specifically developed to create national crop distribution maps using the Spatial Production Allocation Model (SPAM) (You and Wood 2006; You, Wood, and Wood-Sichra 2009; You et al. 2014; Yu et al. 2020).

Authors:Michiel van Dijk

mapspam2globiom_0.0.1.tar.gz
mapspam2globiom_0.0.1.zip(r-4.7-any)mapspam2globiom_0.0.1.zip(r-4.6-any)mapspam2globiom_0.0.1.zip(r-4.5-any)
mapspam2globiom_0.0.1.tgz(r-4.6-any)mapspam2globiom_0.0.1.tgz(r-4.5-any)
mapspam2globiom_0.0.1.tar.gz(r-4.7-any)mapspam2globiom_0.0.1.tar.gz(r-4.6-any)
mapspam2globiom_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mapspam2globiom/json (API)

# Install 'mapspam2globiom' in R:
install.packages('mapspam2globiom', repos = c('https://iiasa.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/iiasa/mapspam2globiom/issues

On CRAN:

Conda:

3.78 score 3 stars 1 scripts 1 exports 32 dependencies

Last updated from:041615e6a6. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR145
source / vignettesOK184
linux-release-x86_64ERROR124
macos-release-arm64ERROR121
macos-oldrel-arm64ERROR91
windows-develERROR69
windows-releaseERROR77
windows-oldrelERROR63
wasm-releaseOK163

Exports:create_globiom_input

Dependencies:classclassIntcliDBIdplyre1071exactextractrgenericsglueKernSmoothlatticelifecyclemagrittrMASSpillarpkgconfigproxyR6rasterRcpprlangs2sfspterratibbletidyselectunitsutf8vctrswithrwk

Adding a new crop to GLOBIOM
Assigning the new crop in sets | Supply | Demand | Adding demand in base year | Shifting demand for a new crop | Trade
Rendered fromadd_new_crop_to_globiom.Rmdusingknitr::rmarkdown

Last update: 2024-05-19
Started: 2020-05-18

Create updated GLOBIOM land cover and crop distribution data
Create updated land cover and crop distribution information
Rendered fromcreate_updated_globiom_input_data.Rmdusingknitr::rmarkdown

Last update: 2024-05-19
Started: 2024-05-19

Installation
Essential R packages | GAMS | References
Rendered frominstallation.Rmdusingknitr::rmarkdown

Last update: 2024-05-19
Started: 2020-04-17

Replace land cover and land use information in GLOBIOM
Step 1: Download the GLOBIOM model and GLOBIOM data branches | GLOBIOM_FABLE | Getting Started | Pre compilation | Graphical User Interface | Documentation | Platforms | Terms of Use | GLOBIOM_FABLE_Data | Requirements | Step 2: Set the regional definitions and the spatial resolution run the data compliation of the data branch | Spatial resolution | Step 3: start a GAMS script (.gms) to load the set and regional definitions and other data from the finaldata subfolder of the model folder | Load national level crop production and price statistics | Example code for including GAMS (.gms) files | Step 4: Loading and replacing the cropland use maps in the appropriate parameters within GLOBIOM | Load the existing cropland use maps | Load the existing land cover maps | Load the new cropland use map and land cover maps from mapspam2globiom | Example code for including gdx files | Step 5: Replace existing crop land use in CROP_DATA and replace the existing land cover data in LANDCOVER_INIT_CrpGrsForOagADJ | Troubleshooting: reorder or drop dimenstions | Step 6: Udpate the crop yields for new crop areas and identify and fill missing data with averages values | Calculate the crop yield average using FAO Statistics | Calculate the crop yield average using the average of each management system (based on EPIC Data) | Calculate the average crop input requirement using the average of each management system (based on EPIC Data) | Identify the grid cells with missing data and replace with average crop yields | Step 7: Update production costs by crop and management system | Table 2 | Example code for updating the crop/management system production costs | Step 8: Harmonize the cropland area with national level statistics and the land cover with the national level statistics | Step 9: Calibrate and rescale the crop yields using the national level statistics | Step 10: Send the updated parameters to the finaldata subfolder in the model branch
Rendered fromreplace_globiom_land_cover_land_use.Rmdusingknitr::rmarkdown

Last update: 2024-05-19
Started: 2020-05-20