Man pages for environmentalinformatics-marburg/Rainfall
Functions for training, predictiion and validation of an MSG based optical rainfall retrieval

aggRasterTemporal aggregation of raster data
borgIndicesCalculate shape indices listed in Borg 1998
calcScalingStatsReturns mean and sd values of the predictors which can be...
calculatePredictorsCalculate predictors from MSG cloud masked data
cr2llGet geocoordinates from MSG column and rows
createSubsetCreate a training subset from data
ffs4rainfallPerforms forward feature selection
filterStatsCalculate statistics of spatial filters of MSG bands
fourStatsnnet with cutoff as additional tuning parameter
generateFileNameGenerate msg file names
geometryVariablesCalculate selected geometry variables for clouds
getChannelsGet channels from a msg scene's inputpath
getDateGet the date from a msg scene's inputpath
getDaytimeClassify a scene into day, twilight, night according to its...
getSunzenithGet sunzenith raster from a msg scene's inputpath
glcmPerPatchCalculate selected Texture parameters for overall cloud...
ll2crGet MSG pixel coordinates (column/rows) from geocordiantes
msgstatmatchMatch temporally aggregated (1h) MSG data with station data
plotPredCorrPlot correlation of predictors
ppStatCalculate zonal statistics for cloud patches
predictRainfallPredicts the rainfall rate based on a trained model and MSG...
projectMSGQuick&Dirty Method to project MSG data
rainfall-packageFunctions for training and prediction of an MSG based...
randomScenesRandomly Select a percentage of scenes
rfe4rainfallPerforms recursive feature selction
scaleByValueScales Predictors using mean and sd from lookup table
spectralDerivateCalculation of derivated spectral channels
tempAggregateAggregates MSG images and sunzenith to one hour (mean...
textureVariablesCalculate selected Texture parameters from clouds based on...
train4rainfallPerforms model training
validateValidation of model results
varFromRfeExtract variables from rfe model
writeToFileWrites a stack of MSG channels to a new file with respect to...
environmentalinformatics-marburg/Rainfall documentation built on May 16, 2019, 7:49 a.m.