Image collection overview

Getting Started with Earth Engine ImageCollection

As illustrated in the Get Started section and the ImageCollection Information section, Earth Engine provides a variety of convenience methods for filtering image collections. Specifically, many common use cases are handled by imageCollection.filterDate(), and imageCollection.filterBounds(). For general purpose filtering, use imageCollection.filter() with an ee.Filter as an argument. The following example demonstrates both convenience methods and filter() to identify and remove images with bad registration from an ImageCollection:

In [1]:

import ee
import geemap

import ee import geemap

In [2]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

Out[2]:

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Get collection size¶

In [3]:

collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')

collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')

In [4]:

print(collection.size().getInfo())

print(collection.size().getInfo())

1233209

Get the first image¶

In [5]:

image = collection.first()
geemap.image_props(image).getInfo()

image = collection.first() geemap.image_props(image).getInfo()

Out[5]:

{'CLOUD_COVER': 88.55,
 'CLOUD_COVER_LAND': 38.2,
 'EARTH_SUN_DISTANCE': 1.012707,
 'ESPA_VERSION': '2_23_0_1a',
 'GEOMETRIC_RMSE_MODEL': 7.666,
 'GEOMETRIC_RMSE_MODEL_X': 5.483,
 'GEOMETRIC_RMSE_MODEL_Y': 5.358,
 'IMAGE_DATE': '2014-05-24',
 'IMAGE_QUALITY_OLI': 9,
 'IMAGE_QUALITY_TIRS': 9,
 'LANDSAT_ID': 'LC08_L1TP_001004_20140524_20170422_01_T1',
 'LEVEL1_PRODUCTION_DATE': 1492857311000,
 'NOMINAL_SCALE': 30,
 'PIXEL_QA_VERSION': 'generate_pixel_qa_1.6.0',
 'SATELLITE': 'LANDSAT_8',
 'SENSING_TIME': '2014-05-24T14:07:53.5175160Z',
 'SOLAR_AZIMUTH_ANGLE': -161.343674,
 'SOLAR_ZENITH_ANGLE': 57.854137,
 'SR_APP_VERSION': 'LaSRC_1.3.0',
 'WRS_PATH': 1,
 'WRS_ROW': 4,
 'system:asset_size': '633.527205 MB',
 'system:band_names': ['B1',
  'B2',
  'B3',
  'B4',
  'B5',
  'B6',
  'B7',
  'B10',
  'B11',
  'sr_aerosol',
  'pixel_qa',
  'radsat_qa'],
 'system:id': 'LANDSAT/LC08/C01/T1_SR/LC08_001004_20140524',
 'system:index': 'LC08_001004_20140524',
 'system:time_end': '2014-05-24 14:07:53',
 'system:time_start': '2014-05-24 14:07:53',
 'system:version': 1522727451594601}

In [6]:

Map.addLayer(image, {}, "First image")
Map.centerObject(image, 6)
Map

Map.addLayer(image, {}, "First image") Map.centerObject(image, 6) Map

Out[6]:

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Filter by dates¶

https://developers.google.com/earth-engine/apidocs/ee-imagecollection-filterdate

In [7]:

collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterDate(
    '2020-01-01', '2020-12-31'
)

collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterDate( '2020-01-01', '2020-12-31' )

In [8]:

print(collection.size().getInfo())

print(collection.size().getInfo())

140225

In [9]:

image2 = collection.first()
Map.addLayer(image2, {}, "Another image")
Map.centerObject(image2, 6)
Map

image2 = collection.first() Map.addLayer(image2, {}, "Another image") Map.centerObject(image2, 6) Map

Out[9]:

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Filter by location¶

https://developers.google.com/earth-engine/apidocs/ee-imagecollection-filterbounds

In [10]:

roi = ee.Geometry.Point(-122.4488, 37.7589)

roi = ee.Geometry.Point(-122.4488, 37.7589)

In [11]:

collection = (
    ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
    .filterDate('2020-01-01', '2020-12-31')
    .filterBounds(roi)
)

collection = ( ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') .filterDate('2020-01-01', '2020-12-31') .filterBounds(roi) )

In [12]:

print(collection.size().getInfo())

print(collection.size().getInfo())

21

In [13]:

Map = geemap.Map()
image = collection.first()

vis_param = {'min': 0, 'max': 2000, 'bands': ['B5', 'B4', 'B3'], 'gamma': 1.5}

Map.addLayer(image, vis_param, "First mage")
Map.centerObject(image, 8)

Map

Map = geemap.Map() image = collection.first() vis_param = {'min': 0, 'max': 2000, 'bands': ['B5', 'B4', 'B3'], 'gamma': 1.5} Map.addLayer(image, vis_param, "First mage") Map.centerObject(image, 8) Map

Out[13]:

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Filter by metadata¶

https://developers.google.com/earth-engine/apidocs/ee-imagecollection-filtermetadata

In [14]:

collection = (
    ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
    .filterDate('2020-01-01', '2020-12-31')
    .filterBounds(ee.Geometry.Point(-122.4488, 37.7589))
    .filterMetadata('CLOUD_COVER', 'less_than', 10)
    .sort("CLOUD_COVER")
)

collection = ( ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') .filterDate('2020-01-01', '2020-12-31') .filterBounds(ee.Geometry.Point(-122.4488, 37.7589)) .filterMetadata('CLOUD_COVER', 'less_than', 10) .sort("CLOUD_COVER") )

In [15]:

Map = geemap.Map()
image = collection.first()

vis_param = {'min': 0, 'max': 2000, 'bands': ['B5', 'B4', 'B3'], 'gamma': 1.5}

Map.addLayer(image, vis_param, "First mage")
Map.centerObject(image, 8)

Map

Map = geemap.Map() image = collection.first() vis_param = {'min': 0, 'max': 2000, 'bands': ['B5', 'B4', 'B3'], 'gamma': 1.5} Map.addLayer(image, vis_param, "First mage") Map.centerObject(image, 8) Map

Out[15]:

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In [16]:

geemap.image_props(image).getInfo()

geemap.image_props(image).getInfo()

Out[16]:

{'CLOUD_COVER': 0.07,
 'CLOUD_COVER_LAND': 0.1,
 'EARTH_SUN_DISTANCE': 0.997823,
 'ESPA_VERSION': '2_23_0_1b',
 'GEOMETRIC_RMSE_MODEL': 6.867,
 'GEOMETRIC_RMSE_MODEL_X': 4.673,
 'GEOMETRIC_RMSE_MODEL_Y': 5.031,
 'IMAGE_DATE': '2020-10-12',
 'IMAGE_QUALITY_OLI': 9,
 'IMAGE_QUALITY_TIRS': 9,
 'LANDSAT_ID': 'LC08_L1TP_044034_20201012_20201104_01_T1',
 'LEVEL1_PRODUCTION_DATE': 1604502607000,
 'NOMINAL_SCALE': 30,
 'PIXEL_QA_VERSION': 'generate_pixel_qa_1.6.0',
 'SATELLITE': 'LANDSAT_8',
 'SENSING_TIME': '2020-10-12T18:46:24.8043990Z',
 'SOLAR_AZIMUTH_ANGLE': 156.943848,
 'SOLAR_ZENITH_ANGLE': 47.988567,
 'SR_APP_VERSION': 'LaSRC_1.3.0',
 'WRS_PATH': 44,
 'WRS_ROW': 34,
 'system:asset_size': '556.916351 MB',
 'system:band_names': ['B1',
  'B2',
  'B3',
  'B4',
  'B5',
  'B6',
  'B7',
  'B10',
  'B11',
  'sr_aerosol',
  'pixel_qa',
  'radsat_qa'],
 'system:id': 'LANDSAT/LC08/C01/T1_SR/LC08_044034_20201012',
 'system:index': 'LC08_044034_20201012',
 'system:time_end': '2020-10-12 18:46:24',
 'system:time_start': '2020-10-12 18:46:24',
 'system:version': 1604744200215236}

Get image collection properties¶

In [17]:

collection = (
    ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
    .filterDate('2020-01-01', '2020-12-31')
    .filterBounds(ee.Geometry.Point(-122.4488, 37.7589))
    .filterMetadata('CLOUD_COVER', 'less_than', 10)
)

collection = ( ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') .filterDate('2020-01-01', '2020-12-31') .filterBounds(ee.Geometry.Point(-122.4488, 37.7589)) .filterMetadata('CLOUD_COVER', 'less_than', 10) )

In [18]:

collection.aggregate_array('CLOUD_COVER').getInfo()

collection.aggregate_array('CLOUD_COVER').getInfo()

Out[18]:

[0.55, 0.46, 6.53, 0.07, 2.96, 0.55]

In [19]:

collection.aggregate_array('system:id').getInfo()

collection.aggregate_array('system:id').getInfo()

Out[19]:

['LANDSAT/LC08/C01/T1_SR/LC08_044034_20200302',
 'LANDSAT/LC08/C01/T1_SR/LC08_044034_20200403',
 'LANDSAT/LC08/C01/T1_SR/LC08_044034_20200606',
 'LANDSAT/LC08/C01/T1_SR/LC08_044034_20201012',
 'LANDSAT/LC08/C01/T1_SR/LC08_044034_20201028',
 'LANDSAT/LC08/C01/T1_SR/LC08_044034_20201129']

In [20]:

collection.aggregate_mean('CLOUD_COVER').getInfo()

collection.aggregate_mean('CLOUD_COVER').getInfo()

Out[20]:

1.8533333333333335

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Last update: 2022-03-25