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meteo (version 2.0-3)

RFSI & STRK Interpolation for Meteo and Environmental Variables

Description

Random Forest Spatial Interpolation (RFSI, Sekulić et al. (2020) ) and spatio-temporal geostatistical (spatio-temporal regression Kriging (STRK)) interpolation for meteorological (Kilibarda et al. (2014) , Sekulić et al. (2020) ) and other environmental variables. Contains global spatio-temporal models calculated using publicly available data.

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Install

install.packages('meteo')

Monthly Downloads

355

Version

2.0-3

License

GPL (>= 2.0) | file LICENCE

Issues

4

Pull Requests

0

Stars

15

Forks

7

Maintainer

Aleksandar Sekulić

Last Published

April 18th, 2024

Functions in meteo (2.0-3)

dtempc_ogimet

Mean daily temperature in degrees Celsius for the year 2019 for Serbia
near.obs.soil

Finds n nearest observations from given locations for soil mapping.
meteo2STFDF

Create an object of STFDF-class class from two data frames (observation and stations)
dtempc

Mean daily temperature in degrees Celsius for July 2011
nlmodis20110704

MODIS LST 8 day images image for the Netherlands ('2011-07-04')
dtemp_minc

Minimum daily temperature in degrees Celsius for July 2011
get_meteo

Get daily, monthly, or annual; aggregated or long-term means meteorological data for specific location(s) and date(s).
get_coordinates

Get lon/lat coordinates for a specific location name.
near.obs

Finds n nearest observations from given locations.
dwdsp

Daily mean wind speed in m/s for July 2011
pred.strk

Spatio-temporal regression kriging prediction
nlmodis20110712

MODIS LST 8 day images image for the Netherlands ('2011-07-12')
pred.rfsi

Random Forest Spatial Interpolation (RFSI) prediction
rm.dupl

Find point pairs with equal spatial coordinates from STFDF-class object.
rfillspgaps

Close gaps of a grid or raster Layer data
rfsi

Random Forest Spatial Interpolation (RFSI) model
stations_ogimet

Data frame containing stations' information from the OGIMET service for Serbian territory
stations

Data frame containing stations' information
regdata

Dynamic and static covariates for spatio-temporal regression kriging
rfilltimegaps

Disaggregation in the time dimension through the use of splines for each pixel
tvgms

Spatio-temporal variogram models for global and local daily air temperatures
tune.rfsi

Tuning of Random Forest Spatial Interpolation (RFSI) model
tgeom2STFDF

Calculate geometrical temperature trend
temp_geom

Calculate geometrical temperature trend
tiling

Tiling raster or Spatial-class Grid or Pixels object
tregcoef

Multiple linear regression coefficients for global and local daily air temperatures
dsndp

Daily snow depth in cm for July 2011
cv.strk

k-fold cross-validation for spatio-temporal regression kriging
data.prepare

Prepare data
cv.rfsi

Nested k-fold cross-validation for Random Forest Spatial Interpolation (RFSI)
dem_twi_srb

Digital Elevation Model (DEM) and Topographic Wetness Index (TWI) for Serbia
dtemp_maxc

Maximum daily temperature in degrees Celsius for July 2011
dprec

Daily precipitation amount in mm for July 2011
dslp

Mean sea level pressure in hPa for July 2011
acc.metric.fun

Accuracy metrics calculation
NLpol

The Netherlands border polygon from WCAB