meteo

Random Forest Spatial Interpolation (RFSI, Sekulić et al. (2020) doi:10.3390/rs12101687 ) and spatio-temporal geostatistical (spatio-temporal regression Kriging (STRK)) interpolation for meteorological (Kilibarda et al. (2014) doi:10.1002/2013JD020803, Sekulić et al. (2020) doi:10.1007/s00704-019-03077-3) and other environmental variables. Contains global spatio-temporal models calculated using publicly available data.

Last 30 days

This package has been downloaded 331 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 13 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 4,093 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Apr 26, 2024 with 43 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.