start_annotation_simple | R Documentation |
Submit a dataframe for on-the-fly annotation. Does not require login - for use for small numbers of records and pilot jobs.
You can annotate using layers that are on earthengine! Layer parameters: Used by all:
spatial: The spatial buffer in meters.
temporal: The temporal buffer in days.
For STOAT layers:
product: The product e.g "srtm", or "landsat8".
variable; The vairable, e.g "elevation", or "evi".
For non STOAT layers, ie those in Google Earth Engine:
id: The id of the image in Google Earth Engine, mapped to "product" in the output.
static: Whether to load the imagery as an ImageCollection or as an Image.
bands: A list, wiht one element, which is used to specify which band of the imagery to use for the annotation, mapped to "variable" in the output.
reducers: A list containing one or more of the following:
mean
lcv_count
mode
median
stdev
min
max
stdev
If only one is provided the output will be assigned to "value", else the output will be named the same as the reducer.
start_annotation_simple( events, layers, coords = c("lng", "lat"), date = "date" )
events |
A data.frame for on the fly annotation |
layers |
A list of parameters or vector of codes, of the layers, see the examples below. |
coords |
A vector of length 2 containing column names for record longitudes, and latitudes. |
date |
Column name for record dates, dates must take the format YYYY-MM-DD |
Input data.frame with values from the annotation appended, in addition to unique identifier field event_id.
event_id: A unique identifier for each occurrence
product: Product used for annotation
variable: Variable used for annotation
s_buff: Spatial buffer in meters applied to occurrence
t_buff: Temporal buffer in days applied to occurrence
value: Annotated value of occurrence from requested layer (mean within buffer), if there is only one reducer (default), then this value will be here.
stdev: Standard deviation of values within buffer
valid_pixel_count: Number of pixels within buffered area'
## Not run: events <- data.frame( event_id = as.character(1:2), lng = c(-4, 24), lat = c(10, 10), date = '2015-01-01' ) # simple layer string format: PRODUCT-VARIABLE-S_BUFF-T_BUFF layers <- 'landsat8-evi-100-16' start_annotation_simple(events, layers) start_annotation_simple(events, layers) # For lcv_count (Count of landcover value), 'value' returned is a string of # landcover counts within the AOI. # The output format is: # <LANDCOVER_CLASS>:<COUNT_OF_PIXELS_WITH_THAT_CLASS> # classes are seperated by commas. start_annotation_simple(events, list( list( id="COPERNICUS/Landcover/100m/Proba-V-C3/Global", s_buff=1000, reducers=list("lcv_count", "mode"), static=FALSE, t_buff=365, bands=list("discrete_classification") ) )) # Annotating with two worldclim layers: # bio01 is annual mean temperature # bio12 is annual precipitation start_annotation_simple(events, list( list( "id"= "WORLDCLIM/V1/BIO", "s_buff"=1000, "reducers"=list("mean"), "static"= TRUE, "t_buff"= 1, "bands"=list("bio01") ), list( "id"= "WORLDCLIM/V1/BIO", "s_buff"=1000, "reducers"=list("mean"), "static"= TRUE, "t_buff"= 1, "bands"=list("bio12") ) )) ## End(Not run)
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