Uncomment the following line to install geemap if needed.

In [1]:

# !pip install geemap

# !pip install geemap

How to get image basic properties and descriptive statistics¶

In [2]:

import ee
import geemap

import ee import geemap

Create an interactive map¶

In [3]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

Out[3]:

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

Add images to the map¶

In [4]:

centroid = ee.Geometry.Point([-122.4439, 37.7538])

landsat = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterBounds(centroid).first()

landsat_vis = {'min': 0, 'max': 3000, 'bands': ['B5', 'B4', 'B3']}

Map.centerObject(centroid, 8)
Map.addLayer(landsat, landsat_vis, "Landsat-8")

centroid = ee.Geometry.Point([-122.4439, 37.7538]) landsat = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterBounds(centroid).first() landsat_vis = {'min': 0, 'max': 3000, 'bands': ['B5', 'B4', 'B3']} Map.centerObject(centroid, 8) Map.addLayer(landsat, landsat_vis, "Landsat-8")

In [5]:

naip = ee.ImageCollection('USDA/NAIP/DOQQ').filterBounds(centroid).first()

naip_vis = {'bands': ['N', 'R', 'G']}

Map.addLayer(naip, naip_vis, 'NAIP')

naip = ee.ImageCollection('USDA/NAIP/DOQQ').filterBounds(centroid).first() naip_vis = {'bands': ['N', 'R', 'G']} Map.addLayer(naip, naip_vis, 'NAIP')

Get image property names¶

In [6]:

landsat.propertyNames().getInfo()

landsat.propertyNames().getInfo()

Out[6]:

['IMAGE_QUALITY_TIRS',
 'CLOUD_COVER',
 'system:id',
 'EARTH_SUN_DISTANCE',
 'LANDSAT_ID',
 'system:footprint',
 'system:version',
 'CLOUD_COVER_LAND',
 'GEOMETRIC_RMSE_MODEL',
 'SR_APP_VERSION',
 'SATELLITE',
 'SOLAR_AZIMUTH_ANGLE',
 'IMAGE_QUALITY_OLI',
 'system:time_end',
 'WRS_PATH',
 'system:time_start',
 'SENSING_TIME',
 'ESPA_VERSION',
 'SOLAR_ZENITH_ANGLE',
 'WRS_ROW',
 'GEOMETRIC_RMSE_MODEL_Y',
 'LEVEL1_PRODUCTION_DATE',
 'GEOMETRIC_RMSE_MODEL_X',
 'system:asset_size',
 'PIXEL_QA_VERSION',
 'system:index',
 'system:bands',
 'system:band_names']

In [7]:

landsat.get('CLOUD_COVER').getInfo()

landsat.get('CLOUD_COVER').getInfo()

Out[7]:

0.05

In [8]:

# The number of milliseconds since 1970-01-01T00:00:00Z.
landsat.get('system:time_start').getInfo()

# The number of milliseconds since 1970-01-01T00:00:00Z. landsat.get('system:time_start').getInfo()

Out[8]:

1365533194757

In [9]:

ee.Date(landsat.get('system:time_start')).format('YYYY-MM-dd').getInfo()

ee.Date(landsat.get('system:time_start')).format('YYYY-MM-dd').getInfo()

Out[9]:

'2013-04-09'

Get image properties all at once¶

In [10]:

landsat_props = geemap.image_props(landsat)
landsat_props.getInfo()

landsat_props = geemap.image_props(landsat) landsat_props.getInfo()

Out[10]:

{'CLOUD_COVER': 0.05,
 'CLOUD_COVER_LAND': 0.06,
 'EARTH_SUN_DISTANCE': 1.001791,
 'ESPA_VERSION': '2_23_0_1b',
 'GEOMETRIC_RMSE_MODEL': 6.678,
 'GEOMETRIC_RMSE_MODEL_X': 4.663,
 'GEOMETRIC_RMSE_MODEL_Y': 4.78,
 'IMAGE_DATE': '2013-04-09',
 'IMAGE_QUALITY_OLI': 9,
 'IMAGE_QUALITY_TIRS': 9,
 'LANDSAT_ID': 'LC08_L1TP_044034_20130409_20170310_01_T1',
 'LEVEL1_PRODUCTION_DATE': 1489126619000,
 'NOMINAL_SCALE': 30,
 'PIXEL_QA_VERSION': 'generate_pixel_qa_1.6.0',
 'SATELLITE': 'LANDSAT_8',
 'SENSING_TIME': '2013-04-09T18:46:34.7579070Z',
 'SOLAR_AZIMUTH_ANGLE': 142.742508,
 'SOLAR_ZENITH_ANGLE': 34.973495,
 'SR_APP_VERSION': 'LaSRC_1.3.0',
 'WRS_PATH': 44,
 'WRS_ROW': 34,
 'system:asset_size': '558.682087 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_20130409',
 'system:index': 'LC08_044034_20130409',
 'system:time_end': '2013-04-09 18:46:34',
 'system:time_start': '2013-04-09 18:46:34',
 'system:version': 1581684730621653}

In [11]:

landsat_props.get('IMAGE_DATE').getInfo()

landsat_props.get('IMAGE_DATE').getInfo()

Out[11]:

'2013-04-09'

In [12]:

naip_props = geemap.image_props(naip)
naip_props.getInfo()

naip_props = geemap.image_props(naip) naip_props.getInfo()

Out[12]:

{'IMAGE_DATE': '2018-08-04',
 'NOMINAL_SCALE': 0.6,
 'system:asset_size': '507.744814 MB',
 'system:band_names': ['R', 'G', 'B', 'N'],
 'system:id': 'USDA/NAIP/DOQQ/m_3712213_sw_10_060_20180804_20190209',
 'system:index': 'm_3712213_sw_10_060_20180804_20190209',
 'system:time_end': '2018-08-04 00:00:00',
 'system:time_start': '2018-08-04 00:00:00',
 'system:version': 1585606585367435}

In [13]:

naip_props.get('NOMINAL_SCALE').getInfo()

naip_props.get('NOMINAL_SCALE').getInfo()

Out[13]:

0.6

Get image descriptive statistics¶

Including minimum, maximum, mean, standard deviation, and sum.

In [14]:

landsat_stats = geemap.image_stats(landsat, scale=90)
landsat_stats.getInfo()

landsat_stats = geemap.image_stats(landsat, scale=90) landsat_stats.getInfo()

Out[14]:

{'max': {'B1': 7624,
  'B10': 3155,
  'B11': 3127,
  'B2': 8471,
  'B3': 9778,
  'B4': 10679,
  'B5': 11606,
  'B6': 13054,
  'B7': 12327,
  'pixel_qa': 480,
  'radsat_qa': 254,
  'sr_aerosol': 228},
 'mean': {'B1': 373.1098468094287,
  'B10': 2933.4637979167583,
  'B11': 2916.278387909346,
  'B2': 427.40213139234174,
  'B3': 614.9744637045823,
  'B4': 591.3781773385491,
  'B5': 1954.134478186476,
  'B6': 1472.071307222312,
  'B7': 996.8232780577415,
  'pixel_qa': 322.8433703241347,
  'radsat_qa': 0.00019878780091270898,
  'sr_aerosol': 87.74885862483129},
 'min': {'B1': -1432,
  'B10': 2759,
  'B11': 2702,
  'B2': -1129,
  'B3': -345,
  'B4': -403,
  'B5': 35,
  'B6': 10,
  'B7': 5,
  'pixel_qa': 322,
  'radsat_qa': 0,
  'sr_aerosol': 8},
 'std': {'B1': 201.9355685609457,
  'B10': 67.57460806939051,
  'B11': 63.85549758560136,
  'B2': 230.81296623126636,
  'B3': 296.8097076885089,
  'B4': 393.63764571402265,
  'B5': 1202.7937141588027,
  'B6': 926.420271742664,
  'B7': 729.0233711578251,
  'pixel_qa': 4.9833065816273345,
  'radsat_qa': 0.1664709111036373,
  'sr_aerosol': 25.1855827242985},
 'sum': {'B1': 1557981451.9372544,
  'B10': 12249159935.513742,
  'B11': 12177399433.172562,
  'B2': 1784687804.2,
  'B3': 2567926888.180393,
  'B4': 2469396718.560784,
  'B5': 8159809497.49804,
  'B6': 6146875544.007842,
  'B7': 4162399334.5490217,
  'pixel_qa': 1347970027.027451,
  'radsat_qa': 830,
  'sr_aerosol': 366378380.98823535}}

In [15]:

naip_stats = geemap.image_stats(naip, scale=10)
naip_stats.getInfo()

naip_stats = geemap.image_stats(naip, scale=10) naip_stats.getInfo()

Out[15]:

{'max': {'B': 233, 'G': 233, 'N': 223, 'R': 229},
 'mean': {'B': 114.4638137606029,
  'G': 109.69790669773778,
  'N': 90.02379690730004,
  'R': 98.22685449511252},
 'min': {'B': 49, 'G': 33, 'N': 1, 'R': 20},
 'std': {'B': 36.49168534887196,
  'G': 38.489676683171794,
  'N': 46.037770089931975,
  'R': 45.42471323713558},
 'sum': {'B': 48679172.0627451,
  'G': 46652327.05098021,
  'N': 38285321.407842256,
  'R': 41773917.835293904}}

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Last update: 2022-03-14