In r-tidy-remote-sensing/tidyrgee: 'tidyverse' Methods for 'Earth Engine'

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(rgee)
library(tidyrgee)

ee_Initialize()

Filter

Have adopted have made an s3 method for filter so it now works in a dplyresque fashion

l8 = ee$ImageCollection('LANDSAT/LC08/C01/T1_SR')

l8 |> 
  filter(date>"2016-01-01",date<"2016-03-04")

group_by and summarise

group_by

modis_ic <- ee$ImageCollection("MODIS/006/MOD13Q1")

modis_ic$select("NDVI") %>%
   filter(date>="2016-01-01",date<="2019-12-31") %>%
   group_by(year)

group_by + summarise

# debugonce(summarise)
modis_ndvi_yearly <- modis_ic$select("NDVI") %>%
   filter(date>="2016-01-01",date<="2019-12-31") %>%
   group_by(year) %>%
   summarise(stat=list("sum","sd"))


# showing difference in year_filter vs year_composite here... 
# modis_ic |> tidyrgee::ee_year_filter("2002-01-01","2004-01-01") |> ee_print()
# modis_ic |> tidyrgee::ee_year_composite(start_date = "2002-01-01",end_date = "2004-01-01",stat="max") |> ee_print()


# cool dplyr::group_by still working
# library(tidyverse)

# dat |> group_by(survey_date)

low level filters ee_year,ee_month, ee_year_month - this will be wrapped conditionally into filter methods

modis_ic |> 
  ee_month_filter(month=c(3,6,9)) |>
  ee_get_date_ic()



modis_ic |> 
  ee_year_month_filter(
    year = c(2005,2007),
    month=c(3,4)
    ) |> 
  ee_get_date_ic()