Feature Layers

Layer Info and Table

Command	Description
fc.size().getInfo()	Number of features
fc.getInfo().get('features')[n].get('properties')	Properties (dictionary) of feature n
fc.getInfo().get('features')[n].get('properties').keys()	List of field names
fc.getInfo().get('features')[n].toDictionary().get('MYFIELD')	Value of the field

Common Functions

Command	Description
fc.reduceColumns(reducer=ee.Reducer.mean(), selectors=['field'])	Statistics (mean) of column ‘field’
fc1.merge(fc2)	Merge two layers
fc.map(lambda feature: feature.set('Area_HA', feature.geometry().area().divide(100 * 100)))	Area in hectares for every feature
fc.map(lambda feature: feature.buffer(300))	Buffer of 300m on every polygon
fc.reduceToImage(properties=['field'], reducer=ee.Reducer.first())	Convert feature collection to image

img = ee.Image('UMD/hansen/global_forest_change_2018_v1_6').select(['lossyear'])
AOI = ee.FeatureCollection('users/user/DVC_for_hab')

def getHist(feature):
    hist = img.reduceRegion(reducer=ee.Reducer.frequencyHistogram(), geometry=feature.geometry())
    return feature.set(hist)

AOI = AOI.map(lambda feature: getHist(feature))

Selecting

Command	Description
fc.filter(ee.Filter.eq('Field', 'Value'))	Select by property
fc.filterMetadata('Field', 'Operator', 'Value')	Select by property. Operators: 'equals', 'less_than', 'greater_than', 'not_equals', 'not_less_than', 'not_greater_than', 'starts_with', 'ends_with', 'not_starts_with', 'not_ends_with', 'contains', 'not_contains'
fc1.filterBounds(fc2)	Select by geometry, features that intersect fc2

Vector to Raster

sheds = ee.FeatureCollection('ft:1IXfrLpTHX4dtdj1LcNXjJADBB-d93rkdJ9acSEWK')

# Version 1
empty = ee.Image().byte().clip(sheds)
sheds_Layer = empty.paint(ee.FeatureCollection(sheds))

# Version 2
sheds_Layer = sheds.reduceToImage(['Area'], ee.Reducer.first())