Example that shows how to extract image collection values for a feature collection, create a vegetaion index time series dataframe and apply a Savitzky-Golay filter over it.
A better version of this function was implemented in eemont as an extended method for the ee.ImageCollection object:
import ee, eemont
ee.Authenticate()
ee.Initialize()
f1 = ee.Feature(ee.Geometry.Point([3.984770,48.767221]).buffer(50),{'ID':'A'})
f2 = ee.Feature(ee.Geometry.Point([4.101367,48.748076]).buffer(50),{'ID':'B'})
fc = ee.FeatureCollection([f1,f2])
S2 = (ee.ImageCollection('COPERNICUS/S2_SR')
.filterBounds(fc)
.filterDate('2020-01-01','2021-01-01')
.maskClouds()
.scale()
.index(['EVI','NDVI']))
# By Region
ts = S2.getTimeSeriesByRegion(reducer = [ee.Reducer.mean(),ee.Reducer.median()],
geometry = fc,
bands = ['EVI','NDVI'],
scale = 10)
# By Regions
ts = S2.getTimeSeriesByRegions(reducer = [ee.Reducer.mean(),ee.Reducer.median()],
collection = fc,
bands = ['EVI','NDVI'],
scale = 10)