library(rgee) ee_Initialize(drive = TRUE) library(sf) library(dplyr) library(Ipaper) library(tidymet) devtools::load_all() ## 1. read tested points sp <- st_met2481[, .(site, lon, lat)] %>% df2sf() inds = chunk(1:nrow(sp), 10) sp_sm = sp[inds[[1]], ]
bands = c( "surface_net_solar_radiation_sum", "surface_net_thermal_radiation_sum", "surface_solar_radiation_downwards_sum", "surface_thermal_radiation_downwards_sum" ) bands_new <- c("Rns", "Rnl", "Rs", "Rl") col <- ee$ImageCollection("ECMWF/ERA5_LAND/DAILY_RAW")$ select(bands, bands_new)$ filter(ee$filter$Filter$calendarRange(2000, 2021, "year")) # filter(ee$filter$Filter$calendarRange(month, month, "month"))$ # filter(ee$filter$Filter$calendarRange(day, day, "day_of_month"))
main <- function(sp) { # years = rev(2001:2019) years <- rev(2000:2021) temp <- foreach(year = years, i = icount()) %do% { runningId(i) col <- ee$ImageCollection("ECMWF/ERA5_LAND/DAILY_RAW")$ filter(ee$filter$Filter$calendarRange(year, year, "year"))$ select(bands) tmp <- ee_extract2(col, sp, via = "drive", lazy = TRUE, scale = 10e3, # 10km # sp, via = "getInfo", lazy = FALSE, scale = 10e3,#10km outfile = glue("st2481_ERA5L_Radiation_{year}.csv") ) } } main(sp)
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