Extract values from a ee$Image
or ImageCollection
at the
locations of a geometry object. You can use ee$Geometry$*
,
ee$Feature
, ee$FeatureCollection
and sf objects. This function
mimicking how extract currently works.
ee_extract(x, y, fun = ee$Reducer$mean(), scale = 1000, sf = FALSE, ...)
x | ee$Image or ee$ImageCollection with a single band. |
---|---|
y | ee$Geometry$*, ee$Feature, ee$FeatureCollection or sf objects. |
fun | ee$Reducer object. Function to summarize the values. The function must take a single numeric value as an argument and return a single value. See details. |
scale | A nominal scale in meters of the Image projection to work in. By default 1000. |
sf | Logical. Should the extracted values be added to the data.frame of the sf object y? |
... | reduceRegions additional parameters. See
|
A data.frame or an sf object depending on the sf argument. The
columns receive their name from the image
metadata property RGEE_NAME
. If it is not defined ee_extract
use the band name (ee$Image$name
) if x
is an ee$Image
and the system:index
property if x
is an
ee$ImageCollection
.
The reducer functions that return one value are:
allNonZero: Returns a Reducer that returns 1 if all of its
inputs are non-zero, 0 otherwise.
anyNonZero: Returns a Reducer that returns 1 if any of its
inputs are non-zero, 0 otherwise.
bitwiseAnd: Returns a Reducer that computes the bitwise-and summation of its inputs.
bitwiseOr: Returns a Reducer that computes the bitwise-or summation of its inputs.
count: Returns a Reducer that computes the number of non-null inputs.
first: Returns a Reducer that returns the first of its inputs.
firstNonNull: Returns a Reducer that returns the first of its non-null inputs.
kurtosis: Returns a Reducer that Computes the kurtosis of its inputs.
last: Returns a Reducer that returns the last of its inputs.
lastNonNull: Returns a Reducer that returns the last of its non-null inputs.
max: Creates a reducer that outputs the maximum value of its (first) input. If numInputs is greater than one, also outputs the corresponding values of the additional inputs.
mean: Returns a Reducer that computes the (weighted) arithmetic mean of its inputs.
median: Create a reducer that will compute the median of the inputs. For small numbers of inputs (up to maxRaw) the median will be computed directly; for larger numbers of inputs the median will be derived from a histogram.
min: Creates a reducer that outputs the minimum value of its (first) input. If numInputs is greater than one, also outputs additional inputs.
mode: Create a reducer that will compute the mode of the inputs. For small numbers of inputs (up to maxRaw) the mode will be computed directly; for larger numbers of inputs the mode will be derived from a histogram.
product: Returns a Reducer that computes the product of its inputs.
sampleStdDev: Returns a Reducer that computes the sample standard deviation of its inputs.
sampleVariance: Returns a Reducer that computes the sample variance of its inputs.
stdDev: Returns a Reducer that computes the standard deviation of its inputs.
sum: Returns a Reducer that computes the (weighted) sum of its inputs.
variance: Returns a Reducer that computes the variance of its inputs.
if (FALSE) { library(rgee) library(sf) ee_Initialize() # Define a Image or ImageCollection: Terraclimate terraclimate <- ee$ImageCollection("IDAHO_EPSCOR/TERRACLIMATE")$ filterDate("2001-01-01", "2002-01-01")$ map(function(x){ date <- ee$Date(x$get("system:time_start"))$format('YYYY_MM_dd') name <- ee$String$cat("Terraclimate_pp_", date) x$select("pr")$reproject("EPSG:4326")$set("RGEE_NAME", name) }) # Define a geometry nc <- st_read( dsn = system.file("shape/nc.shp", package = "sf"), stringsAsFactors = FALSE, quiet = TRUE ) # Extract values ee_nc_rain <- ee_extract( x = terraclimate, y = nc, scale = 250, fun = ee$Reducer$mean(), sf = TRUE ) # Spatial plot plot( ee_nc_rain["Terraclimate_pp_2001_01_01"], main = "2001 Jan Precipitation - Terraclimate", reset = FALSE ) }