ImageCollection Overview

    An ImageCollection is a stack or sequence of images.

    Construct from a collection ID

    An ImageCollection can be loaded by pasting an Earth Engine asset ID into the ImageCollection constructor. You can find ImageCollection IDs in the data catalog . For example, to load the Sentinel-2 surface reflectance collection :

    Code Editor (JavaScript) 

     var 
  
 sentinelCollection 
  
 = 
  
 ee 
 . 
 ImageCollection 
 ( 
 'COPERNICUS/S2_SR' 
 );

    Python setup

    See the Python Environment page for information on the Python API and using geemap for interactive development.

     import 
  
 ee 
 import 
  
 geemap.core 
  
 as 
  
 geemap

    Colab (Python) 

     sentinel_collection 
 = 
 ee 
 . 
 ImageCollection 
 ( 
 'COPERNICUS/S2_SR' 
 )

    This collection contains every Sentinel-2 image in the public catalog. There are a lot. Usually you want to filter the collection as shown here or here .

    Construct from an image list

    The constructor ee.ImageCollection() or the convenience method ee.ImageCollection.fromImages() create image collections from lists of images. You can also create new image collections by merging existing collections. For example:

    Code Editor (JavaScript) 

     // Create arbitrary constant images. 
 var 
  
 constant1 
  
 = 
  
 ee 
 . 
 Image 
 ( 
 1 
 ); 
 var 
  
 constant2 
  
 = 
  
 ee 
 . 
 Image 
 ( 
 2 
 ); 
 // Create a collection by giving a list to the constructor. 
 var 
  
 collectionFromConstructor 
  
 = 
  
 ee 
 . 
 ImageCollection 
 ([ 
 constant1 
 , 
  
 constant2 
 ]); 
 print 
 ( 
 'collectionFromConstructor: ' 
 , 
  
 collectionFromConstructor 
 ); 
 // Create a collection with fromImages(). 
 var 
  
 collectionFromImages 
  
 = 
  
 ee 
 . 
 ImageCollection 
 . 
 fromImages 
 ( 
  
 [ 
 ee 
 . 
 Image 
 ( 
 3 
 ), 
  
 ee 
 . 
 Image 
 ( 
 4 
 )]); 
 print 
 ( 
 'collectionFromImages: ' 
 , 
  
 collectionFromImages 
 ); 
 // Merge two collections. 
 var 
  
 mergedCollection 
  
 = 
  
 collectionFromConstructor 
 . 
 merge 
 ( 
 collectionFromImages 
 ); 
 print 
 ( 
 'mergedCollection: ' 
 , 
  
 mergedCollection 
 ); 
 // Create a toy FeatureCollection 
 var 
  
 features 
  
 = 
  
 ee 
 . 
 FeatureCollection 
 ( 
  
 [ 
 ee 
 . 
 Feature 
 ( 
 null 
 , 
  
 { 
 foo 
 : 
  
 1 
 }), 
  
 ee 
 . 
 Feature 
 ( 
 null 
 , 
  
 { 
 foo 
 : 
  
 2 
 })]); 
 // Create an ImageCollection from the FeatureCollection 
 // by mapping a function over the FeatureCollection. 
 var 
  
 images 
  
 = 
  
 features 
 . 
 map 
 ( 
 function 
 ( 
 feature 
 ) 
  
 { 
  
 return 
  
 ee 
 . 
 Image 
 ( 
 ee 
 . 
 Number 
 ( 
 feature 
 . 
 get 
 ( 
 'foo' 
 ))); 
 }); 
 // Print the resultant collection. 
 print 
 ( 
 'Image collection: ' 
 , 
  
 images 
 );

    Python setup

    See the Python Environment page for information on the Python API and using geemap for interactive development.

     import 
  
 ee 
 import 
  
 geemap.core 
  
 as 
  
 geemap

    Colab (Python) 

     # Create arbitrary constant images. 
 constant_1 
 = 
 ee 
 . 
 Image 
 ( 
 1 
 ) 
 constant_2 
 = 
 ee 
 . 
 Image 
 ( 
 2 
 ) 
 # Create a collection by giving a list to the constructor. 
 collection_from_constructor 
 = 
 ee 
 . 
 ImageCollection 
 ([ 
 constant_1 
 , 
 constant_2 
 ]) 
 display 
 ( 
 'Collection from constructor:' 
 , 
 collection_from_constructor 
 ) 
 # Create a collection with fromImages(). 
 collection_from_images 
 = 
 ee 
 . 
 ImageCollection 
 . 
 fromImages 
 ( 
 [ 
 ee 
 . 
 Image 
 ( 
 3 
 ), 
 ee 
 . 
 Image 
 ( 
 4 
 )] 
 ) 
 display 
 ( 
 'Collection from images:' 
 , 
 collection_from_images 
 ) 
 # Merge two collections. 
 merged_collection 
 = 
 collection_from_constructor 
 . 
 merge 
 ( 
 collection_from_images 
 ) 
 display 
 ( 
 'Merged collection:' 
 , 
 merged_collection 
 ) 
 # Create a toy FeatureCollection 
 features 
 = 
 ee 
 . 
 FeatureCollection 
 ( 
 [ 
 ee 
 . 
 Feature 
 ( 
 None 
 , 
 { 
 'foo' 
 : 
 1 
 }), 
 ee 
 . 
 Feature 
 ( 
 None 
 , 
 { 
 'foo' 
 : 
 2 
 })] 
 ) 
 # Create an ImageCollection from the FeatureCollection 
 # by mapping a function over the FeatureCollection. 
 images 
 = 
 features 
 . 
 map 
 ( 
 lambda 
 feature 
 : 
 ee 
 . 
 Image 
 ( 
 ee 
 . 
 Number 
 ( 
 feature 
 . 
 get 
 ( 
 'foo' 
 )))) 
 # Display the resultant collection. 
 display 
 ( 
 'Image collection:' 
 , 
 images 
 )

    Note that in this example an ImageCollection is created by mapping a function that returns an Image over a FeatureCollection . Learn more about mapping in the Mapping over an ImageCollection section . Learn more about feature collections from the FeatureCollection section .

    Construct from a COG list

    Create an ImageCollection from GeoTiffs in Cloud Storage. For example:

    Code Editor (JavaScript) 

     // All the GeoTiffs are in this folder. 
 var 
  
 uriBase 
  
 = 
  
 'gs://gcp-public-data-landsat/LC08/01/001/002/' 
  
 + 
  
 'LC08_L1GT_001002_20160817_20170322_01_T2/' 
 ; 
 // List of URIs, one for each band. 
 var 
  
 uris 
  
 = 
  
 ee 
 . 
 List 
 ([ 
  
 uriBase 
  
 + 
  
 'LC08_L1GT_001002_20160817_20170322_01_T2_B2.TIF' 
 , 
  
 uriBase 
  
 + 
  
 'LC08_L1GT_001002_20160817_20170322_01_T2_B3.TIF' 
 , 
  
 uriBase 
  
 + 
  
 'LC08_L1GT_001002_20160817_20170322_01_T2_B4.TIF' 
 , 
  
 uriBase 
  
 + 
  
 'LC08_L1GT_001002_20160817_20170322_01_T2_B5.TIF' 
 , 
 ]); 
 // Make a collection from the list of images. 
 var 
  
 images 
  
 = 
  
 uris 
 . 
 map 
 ( 
 ee 
 . 
 Image 
 . 
 loadGeoTIFF 
 ); 
 var 
  
 collection 
  
 = 
  
 ee 
 . 
 ImageCollection 
 ( 
 images 
 ); 
 // Get an RGB image from the collection of bands. 
 var 
  
 rgb 
  
 = 
  
 collection 
 . 
 toBands 
 (). 
 rename 
 ([ 
 'B2' 
 , 
  
 'B3' 
 , 
  
 'B4' 
 , 
  
 'B5' 
 ]); 
 Map 
 . 
 centerObject 
 ( 
 rgb 
 ); 
 Map 
 . 
 addLayer 
 ( 
 rgb 
 , 
  
 { 
 bands 
 : 
  
 [ 
 'B4' 
 , 
  
 'B3' 
 , 
  
 'B2' 
 ], 
  
 min 
 : 
  
 0 
 , 
  
 max 
 : 
  
 20000 
 }, 
  
 'rgb' 
 );

    Python setup

    See the Python Environment page for information on the Python API and using geemap for interactive development.

     import 
  
 ee 
 import 
  
 geemap.core 
  
 as 
  
 geemap

    Colab (Python) 

     # All the GeoTiffs are in this folder. 
 uri_base 
 = 
 ( 
 'gs://gcp-public-data-landsat/LC08/01/001/002/' 
 + 
 'LC08_L1GT_001002_20160817_20170322_01_T2/' 
 ) 
 # List of URIs, one for each band. 
 uris 
 = 
 ee 
 . 
 List 
 ([ 
 uri_base 
 + 
 'LC08_L1GT_001002_20160817_20170322_01_T2_B2.TIF' 
 , 
 uri_base 
 + 
 'LC08_L1GT_001002_20160817_20170322_01_T2_B3.TIF' 
 , 
 uri_base 
 + 
 'LC08_L1GT_001002_20160817_20170322_01_T2_B4.TIF' 
 , 
 uri_base 
 + 
 'LC08_L1GT_001002_20160817_20170322_01_T2_B5.TIF' 
 , 
 ]) 
 # Make a collection from the list of images. 
 images 
 = 
 uris 
 . 
 map 
 ( 
 lambda 
 uri 
 : 
 ee 
 . 
 Image 
 . 
 loadGeoTIFF 
 ( 
 uri 
 )) 
 collection 
 = 
 ee 
 . 
 ImageCollection 
 ( 
 images 
 ) 
 # Get an RGB image from the collection of bands. 
 rgb 
 = 
 collection 
 . 
 toBands 
 () 
 . 
 rename 
 ([ 
 'B2' 
 , 
 'B3' 
 , 
 'B4' 
 , 
 'B5' 
 ]) 
 m 
 = 
 geemap 
 . 
 Map 
 () 
 m 
 . 
 center_object 
 ( 
 rgb 
 ) 
 m 
 . 
 add_layer 
 ( 
 rgb 
 , 
 { 
 'bands' 
 : 
 [ 
 'B4' 
 , 
 'B3' 
 , 
 'B2' 
 ], 
 'min' 
 : 
 0 
 , 
 'max' 
 : 
 20000 
 }, 
 'rgb' 
 ) 
 m

    Learn more about loading images from Cloud GeoTiffs .

    Construct from a Zarr v2 array

    Create an ImageCollection from a Zarr v2 array in Cloud Storage by taking image slices along a higher dimension. For example:

    Code Editor (JavaScript) 

     var 
  
 timeStart 
  
 = 
  
 1000000 
 ; 
 var 
  
 timeEnd 
  
 = 
  
 1000048 
 ; 
 var 
  
 zarrV2ArrayImages 
  
 = 
  
 ee 
 . 
 ImageCollection 
 . 
 loadZarrV2Array 
 ({ 
  
 uri 
 : 
  
 'gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3/evaporation/.zarray' 
 , 
  
 proj 
 : 
  
 'EPSG:4326' 
 , 
  
 axis 
 : 
  
 0 
 , 
  
 starts 
 : 
  
 [ 
 timeStart 
 ], 
  
 ends 
 : 
  
 [ 
 timeEnd 
 ] 
 }); 
 print 
 ( 
 zarrV2ArrayImages 
 ); 
 Map 
 . 
 addLayer 
 ( 
 zarrV2ArrayImages 
 , 
  
 { 
 min 
 : 
  
 - 
 0.0001 
 , 
  
 max 
 : 
  
 0.00005 
 }, 
  
 'Evaporation' 
 );

    Python setup

    See the Python Environment page for information on the Python API and using geemap for interactive development.

     import 
  
 ee 
 import 
  
 geemap.core 
  
 as 
  
 geemap

    Colab (Python) 

     time_start 
 = 
 1000000 
 time_end 
 = 
 1000048 
 zarr_v2_array_images 
 = 
 ee 
 . 
 ImageCollection 
 . 
 loadZarrV2Array 
 ( 
 uri 
 = 
 'gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3/evaporation/.zarray' 
 , 
 proj 
 = 
 'EPSG:4326' 
 , 
 axis 
 = 
 0 
 , 
 starts 
 = 
 [ 
 time_start 
 ], 
 ends 
 = 
 [ 
 time_end 
 ], 
 ) 
 display 
 ( 
 zarr_v2_array_images 
 ) 
 m 
 = 
 geemap 
 . 
 Map 
 () 
 m 
 . 
 add_layer 
 ( 
 zarr_v2_array_images 
 , 
 { 
 'min' 
 : 
 - 
 0.0001 
 , 
 'max' 
 : 
 0.00005 
 }, 
 'Evaporation' 
 ) 
 m
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