Export data

In [1]:

# !pip install geemap

# !pip install geemap

In [2]:

import os
import ee
import geemap

import os import ee import geemap

In [3]:

from geemap.datasets import DATA

from geemap.datasets import DATA

In [4]:

Map = geemap.Map()

Map = geemap.Map()

Set an output directory¶

In [5]:

out_dir = os.path.expanduser("~/Downloads")

if not os.path.exists(out_dir):
    os.makedirs(out_dir)

out_dir = os.path.expanduser("~/Downloads") if not os.path.exists(out_dir): os.makedirs(out_dir)

Export an ee.FeatureCollection¶

In [6]:

fc = ee.FeatureCollection('users/giswqs/public/countries')

fc = ee.FeatureCollection('users/giswqs/public/countries')

In [7]:

Map.addLayer(fc, {}, "Countries")
Map.centerObject(fc)
Map

Map.addLayer(fc, {}, "Countries") Map.centerObject(fc) Map

Out[7]:

Make this Notebook Trusted to load map: File -> Trust Notebook

Export data to a local computer

In [8]:

out_shp = os.path.join(out_dir, "countries.shp")
geemap.ee_export_vector(fc, out_shp, verbose=True)

out_shp = os.path.join(out_dir, "countries.shp") geemap.ee_export_vector(fc, out_shp, verbose=True)

Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/tables/af2cd31629bab2fcc5007bd374c36321-5d0bf8b3b18d8530e2fb24de043eb545:getFeatures
Please wait ...
Data downloaded to /home/runner/Downloads/countries.shp

Export data to Google Drive

In [9]:

geemap.ee_export_vector_to_drive(fc, description="countries", folder="export")

geemap.ee_export_vector_to_drive(fc, description="countries", folder="export")

Exporting countries...

Export an ee.Image¶

In [10]:

image = ee.Image('LE7_TOA_5YEAR/1999_2003')

landsat_vis = {'bands': ['B4', 'B3', 'B2'], 'gamma': 1.7}
Map.addLayer(image, landsat_vis, "LE7_TOA_5YEAR/1999_2003", True, 1)
Map

image = ee.Image('LE7_TOA_5YEAR/1999_2003') landsat_vis = {'bands': ['B4', 'B3', 'B2'], 'gamma': 1.7} Map.addLayer(image, landsat_vis, "LE7_TOA_5YEAR/1999_2003", True, 1) Map

Out[10]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [11]:

out_dir = os.path.join(os.path.expanduser('~'), 'Downloads')
filename = os.path.join(out_dir, 'landsat.tif')

out_dir = os.path.join(os.path.expanduser('~'), 'Downloads') filename = os.path.join(out_dir, 'landsat.tif')

Exporting all bands as one single image¶

In [12]:

# set a default ROI
roi = ee.Geometry.Polygon(
    [
        [
            [-482.643127, 37.547027],
            [-482.643127, 37.996433],
            [-481.908417, 37.996433],
            [-481.908417, 37.547027],
            [-482.643127, 37.547027],
        ]
    ]
)

# set a default ROI roi = ee.Geometry.Polygon( [ [ [-482.643127, 37.547027], [-482.643127, 37.996433], [-481.908417, 37.996433], [-481.908417, 37.547027], [-482.643127, 37.547027], ] ] )

In [13]:

# Draw any shapes on the map using the Drawing tools before executing this code block
if Map.user_roi is not None:
    roi = Map.user_roi

# Draw any shapes on the map using the Drawing tools before executing this code block if Map.user_roi is not None: roi = Map.user_roi

In [14]:

roi.getInfo()

roi.getInfo()

Out[14]:

{'type': 'Polygon',
 'coordinates': [[[-482.643127, 37.547027],
   [-481.908417, 37.547027],
   [-481.908417, 37.996433],
   [-482.643127, 37.996433],
   [-482.643127, 37.547027]]]}

In [15]:

image_clip = image.clip(roi)

image_clip = image.clip(roi)

In [16]:

Map.addLayer(image_clip, landsat_vis, "image")

Map.addLayer(image_clip, landsat_vis, "image")

In [17]:

geemap.ee_export_image(
    image_clip, filename=filename, scale=90, region=roi, file_per_band=False
)

geemap.ee_export_image( image_clip, filename=filename, scale=90, region=roi, file_per_band=False )

Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/83a4ec0d21102c6b0b0fc3fcd9ab8d86-0dd8f1c19c81c94c9c8dc12c93ea1ed5:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/landsat.tif

Exporting each band as one image¶

In [18]:

geemap.ee_export_image(
    image, filename=filename, scale=90, region=roi, file_per_band=True
)

geemap.ee_export_image( image, filename=filename, scale=90, region=roi, file_per_band=True )

Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/a39da6f090dceafbb1b3469419e5eee0-65c0234332f338368a7fdeda1d7fba41:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads

Export an image to Google Drive¶

In [19]:

geemap.ee_export_image_to_drive(
    image, description='landsat', folder='export', region=roi, scale=30
)

geemap.ee_export_image_to_drive( image, description='landsat', folder='export', region=roi, scale=30 )

Exporting landsat ...

Download an ee.ImageCollection¶

In [20]:

loc = ee.Geometry.Point(-99.2222, 46.7816)
collection = (
    ee.ImageCollection('USDA/NAIP/DOQQ')
    .filterBounds(loc)
    .filterDate('2008-01-01', '2020-01-01')
    .filter(ee.Filter.listContains("system:band_names", "N"))
)

loc = ee.Geometry.Point(-99.2222, 46.7816) collection = ( ee.ImageCollection('USDA/NAIP/DOQQ') .filterBounds(loc) .filterDate('2008-01-01', '2020-01-01') .filter(ee.Filter.listContains("system:band_names", "N")) )

In [21]:

out_dir = os.path.expanduser('~/Downloads')

out_dir = os.path.expanduser('~/Downloads')

In [22]:

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

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

Out[22]:

['m_4609915_sw_14_060_20180902_20181213',
 'm_4609915_sw_14_060_20190626',
 'm_4609915_sw_14_1_20090818',
 'm_4609915_sw_14_1_20100629',
 'm_4609915_sw_14_1_20120714',
 'm_4609915_sw_14_1_20140901',
 'm_4609915_sw_14_1_20150926',
 'm_4609915_sw_14_h_20160704',
 'm_4609915_sw_14_h_20170703']

In [23]:

geemap.ee_export_image_collection(collection, out_dir=out_dir)

geemap.ee_export_image_collection(collection, out_dir=out_dir)

Total number of images: 9

Exporting 1/9: m_4609915_sw_14_060_20180902_20181213.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/12dba27394c3260fc731c0d6229e43a5-b7aecc663d9d6fc76ee1d863a7656ff2:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_060_20180902_20181213.tif


Exporting 2/9: m_4609915_sw_14_060_20190626.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/a05dd6d80c920403e8f1f943da8c4174-cdc561f26fd67f3de0dd0d22ef1b6679:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_060_20190626.tif


Exporting 3/9: m_4609915_sw_14_1_20090818.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/e0218e3dbca864608a201086538782b5-42176983ae44cc6f2b7ac5a9a2f0d43e:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_1_20090818.tif


Exporting 4/9: m_4609915_sw_14_1_20100629.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/e8b801d6cba914811034b6a836fa64e8-a64734817cb9f6bfed51409ae9620a6a:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_1_20100629.tif


Exporting 5/9: m_4609915_sw_14_1_20120714.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/a2835ac668b547edc38f2c74320168d8-d90a4c6d198fb2699afe894288993380:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_1_20120714.tif


Exporting 6/9: m_4609915_sw_14_1_20140901.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/dfc26d0ec2aa00709a488938a348c954-a48c1ac45fff1d6a0e3e8a3403623ab0:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_1_20140901.tif


Exporting 7/9: m_4609915_sw_14_1_20150926.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/a3f09592597bb46998d6ca0905a1b1e2-0812b3171b22ef953320887c8625cb4b:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_1_20150926.tif


Exporting 8/9: m_4609915_sw_14_h_20160704.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/0df29ebae58261ebc7edbe5743f785f7-7c01961fb6c682fae07b7055ac6b7875:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_h_20160704.tif


Exporting 9/9: m_4609915_sw_14_h_20170703.tif
Generating URL ...
Downloading data from https://earthengine.googleapis.com/v1alpha/projects/earthengine-legacy/thumbnails/b8e7221f77039b3b23cd347962c1a654-cef83aa3c63a1af1e11e4c47de28c28f:getPixels
Please wait ...
Data downloaded to /home/runner/Downloads/m_4609915_sw_14_h_20170703.tif

In [24]:

geemap.ee_export_image_collection_to_drive(collection, folder='export', scale=10)

geemap.ee_export_image_collection_to_drive(collection, folder='export', scale=10)

Total number of images: 9

Extract pixels as a Numpy array¶

In [25]:

import ee
import geemap
import numpy as np
import matplotlib.pyplot as plt

img = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_038029_20180810').select(['B4', 'B5', 'B6'])

aoi = ee.Geometry.Polygon(
    [[[-110.8, 44.7], [-110.8, 44.6], [-110.6, 44.6], [-110.6, 44.7]]], None, False
)

rgb_img = geemap.ee_to_numpy(img, region=aoi)
print(rgb_img.shape)

import ee import geemap import numpy as np import matplotlib.pyplot as plt img = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_038029_20180810').select(['B4', 'B5', 'B6']) aoi = ee.Geometry.Polygon( [[[-110.8, 44.7], [-110.8, 44.6], [-110.6, 44.6], [-110.6, 44.7]]], None, False ) rgb_img = geemap.ee_to_numpy(img, region=aoi) print(rgb_img.shape)

(373, 531, 3)

In [26]:

# Scale the data to [0, 255] to show as an RGB image.
# Adapted from https://bit.ly/2XlmQY8. Credits to Justin Braaten
rgb_img_test = (255 * ((rgb_img[:, :, 0:3] - 100) / 3500)).astype('uint8')
plt.imshow(rgb_img_test)
plt.show()

# Scale the data to [0, 255] to show as an RGB image. # Adapted from https://bit.ly/2XlmQY8. Credits to Justin Braaten rgb_img_test = (255 * ((rgb_img[:, :, 0:3] - 100) / 3500)).astype('uint8') plt.imshow(rgb_img_test) plt.show()

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Last update: 2022-03-25