All functions

GDALcrop()

Crop on disk using gdalUtilities::ogr2ogr

GDALintersect()

Crop on disk using gdalUtilities::ogr2ogr

ModelDir()

Function for quickly calculating model direction/agreement

addVars()

Add extra climate variables

bccciss-data BGCRegions E1 F1 footnotes models_info N1 R1 S1 SIBEC silvics_mature silvics_regen silvics_resist silvics_tol stocking_height stocking_info stocking_standards subzones_colours_ref T1 TreeCols V1 zones_colours_ref E1_Phase covMat

Data to be included in bccciss package

ccissOutput()

ccissOutput

cleanData()

Clean Portfolio Data

dbBbox()

Buffered bounding box

dbGetBGC()

Get sitenos for preselected points in BGC/district

dbGetBGCPred()

Return raw predictions for given sitenos

dbGetCCISS()

Pull CCISS from a vector of SiteNo

dbGetCCISSRaw()

Pull individual predictions by district

dbGetClimSum()

Get Climate Summary Data

dbGetSppLimits()

Species Limits

dbPointInfo()

Pull points info from lat long inputs

setup_docklet() remote_shp_tiles() tippecanoe_usage() tileserver_doc() styling_doc() reset_ssh_sessions() launch_tileserver()

Setup droplet

.gc()

Garbage collect a few times

.getClimVars()

Wrapper for climr::downscale that keeps extra columns in table of point coordinates.

dwnldFromObjSto()

Download a file from Object Storage

edatopicOverlap()

EDA Topic Overlap

edatopicSubset()

Portfolio Subset

ef_plot()

Plot Efficient Frontier

getClimate()

Prepares coordinates and obtains climate normals using climr::downscale

logVars()

Log-transform climate variables

makeGapExtents()

Make generate extents for gaps used in hold-out samples for model cross-validation.

makePointCoords()

Create a set of training points with associated elevation and BGC values.

optimise_portfolio()

Optimise Portfolio

removeOutlier()

Remove outliers from data

rmLowSampleBGCs()

Remove BGCs with low sample sizes

run_portfolio()

Run species Portfolio

simulateClimate()

Simulate Climate for Portfolio

subsetByExtent()

Subset a group of points by spatial extent

trainModel()

mlr3 model training wrapper