# 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")
)
))
# }
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