Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-10-08 10:24:09	ga_s2am_ard_3-2-1_54JTM_2015-10-08_final.stac-item
2015-10-08 10:24:09	ga_s2am_ard_3-2-1_54JUM_2015-10-08_final.stac-item
2015-10-08 10:24:09	ga_s2am_ard_3-2-1_54JVM_2015-10-08_final.stac-item
2015-10-08 10:24:09	ga_s2am_ard_3-2-1_53JPG_2015-10-08_final.stac-item
2015-10-08 10:24:09	ga_s2am_ard_3-2-1_53JQF_2015-10-08_final.stac-item
2015-10-08 10:24:09	ga_s2am_ard_3-2-1_53JQG_2015-10-08_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JKM_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JLM_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JMM_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JNM_2015-11-14_final.stac-item
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_54JTM_2015-11-17_final.stac-item
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_54JUM_2015-11-17_final.stac-item
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_54JVM_2015-11-17_final.stac-item
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_53JPG_2015-11-17_final.stac-item
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_53JQF_2015-11-17_final.stac-item
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_53JQG_2015-11-17_final.stac-item
2015-11-24 10:15:11	ga_s2am_ard_3-2-1_54JUM_2015-11-24_final.stac-item
2015-11-24 10:15:11	ga_s2am_ard_3-2-1_54JVM_2015-11-24_final.stac-item
2015-11-24 10:15:11	ga_s2am_ard_3-2-1_54JWM_2015-11-24_final.stac-item
2015-11-24 10:15:11	ga_s2am_ard_3-2-1_54JXM_2015-11-24_final.stac-item
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51JUG_2015-11-25_final.stac-item
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51JVG_2015-11-25_final.stac-item
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51JWG_2015-11-25_final.stac-item
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51JXG_2015-11-25_final.stac-item
2015-11-28 11:36:02	ga_s2am_ard_3-2-1_50JQM_2015-11-28_final.stac-item
2018-02-26 09:22:41	ga_s2am_ard_3-2-1_56JMM_2018-02-25_final.stac-item
2018-02-26 09:22:41	ga_s2am_ard_3-2-1_56JNM_2018-02-25_final.stac-item
2018-03-01 09:33:52	ga_s2am_ard_3-2-1_56JKM_2018-03-01_final.stac-item
2018-03-01 09:33:52	ga_s2am_ard_3-2-1_56JLM_2018-03-01_final.stac-item
2018-03-01 09:33:52	ga_s2am_ard_3-2-1_56JMM_2018-03-01_final.stac-item
2018-03-01 09:33:52	ga_s2am_ard_3-2-1_55JGF_2018-03-01_final.stac-item
2018-03-01 09:33:52	ga_s2am_ard_3-2-1_55JGG_2018-03-01_final.stac-item
2018-03-08 09:22:41	ga_s2am_ard_3-2-1_56JMM_2018-03-07_final.stac-item
2018-03-08 09:22:41	ga_s2am_ard_3-2-1_56JNM_2018-03-07_final.stac-item
2018-03-14 09:41:04	ga_s2am_ard_3-2-1_56JKM_2018-03-14_final.stac-item
2018-03-14 09:41:04	ga_s2am_ard_3-2-1_55JDG_2018-03-14_final.stac-item
2018-03-14 09:41:04	ga_s2am_ard_3-2-1_55JEG_2018-03-14_final.stac-item
2018-03-14 09:41:04	ga_s2am_ard_3-2-1_55JFG_2018-03-14_final.stac-item
2018-03-14 09:41:04	ga_s2am_ard_3-2-1_55JGG_2018-03-14_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53JKG_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_52JEM_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_52JFM_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_52JGM_2018-03-15_final.stac-item
2018-03-16 10:17:02	ga_s2am_ard_3-2-1_54JTM_2018-03-16_final.stac-item
2018-03-16 10:17:02	ga_s2am_ard_3-2-1_54JUM_2018-03-16_final.stac-item
2018-03-16 10:17:02	ga_s2am_ard_3-2-1_54JVM_2018-03-16_final.stac-item
2018-03-16 10:17:02	ga_s2am_ard_3-2-1_53JPG_2018-03-16_final.stac-item
2018-03-16 10:17:02	ga_s2am_ard_3-2-1_53JQG_2018-03-16_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52JEM_2018-03-18_final.stac-item
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JBM_2018-03-18_final.stac-item
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JCM_2018-03-18_final.stac-item
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JDM_2018-03-18_final.stac-item
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JEM_2018-03-18_final.stac-item
2018-03-19 10:27:04	ga_s2am_ard_3-2-1_53JMG_2018-03-19_final.stac-item
2018-03-19 10:27:04	ga_s2am_ard_3-2-1_53JNG_2018-03-19_final.stac-item
2018-03-19 10:27:04	ga_s2am_ard_3-2-1_53JPG_2018-03-19_final.stac-item
2018-03-19 10:27:04	ga_s2am_ard_3-2-1_53JQG_2018-03-19_final.stac-item
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53JKG_2018-09-18_final.stac-item
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53JLG_2018-09-18_final.stac-item
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53JMG_2018-09-18_final.stac-item
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_52JGL_2018-09-18_final.stac-item
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_52JGM_2018-09-18_final.stac-item
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53JNG_2018-09-18_final.stac-item
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53JKG_2018-09-28_final.stac-item
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53JLG_2018-09-28_final.stac-item
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53JMG_2018-09-28_final.stac-item
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_52JGL_2018-09-28_final.stac-item
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_52JGM_2018-09-28_final.stac-item
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53JNG_2018-09-28_final.stac-item
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_56JKM_2018-09-30_final.stac-item
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55JDG_2018-09-30_final.stac-item
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55JEG_2018-09-30_final.stac-item
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55JFG_2018-09-30_final.stac-item
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55JGG_2018-09-30_final.stac-item
2018-10-04 09:22:41	ga_s2am_ard_3-2-1_56JMM_2018-10-03_final.stac-item
2018-10-04 09:22:41	ga_s2am_ard_3-2-1_56JNM_2018-10-03_final.stac-item
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_51JXG_2018-10-07_final.stac-item
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_51JYF_2018-10-07_final.stac-item
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_51JYG_2018-10-07_final.stac-item
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_52JBM_2018-10-07_final.stac-item
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_52JCM_2018-10-07_final.stac-item
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_56JKM_2018-10-10_final.stac-item
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55JFG_2018-10-10_final.stac-item
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55JGG_2018-10-10_final.stac-item
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52JBM_2018-10-14_final.stac-item
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52JCM_2018-10-14_final.stac-item
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52JDM_2018-10-14_final.stac-item
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52JEM_2018-10-14_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JXG_2018-10-17_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JYF_2018-10-17_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51JYG_2018-10-17_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JBM_2018-10-17_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JCM_2018-10-17_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JDG_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JEG_2018-10-20_final.stac-item
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JFG_2018-10-20_final.stac-item
2024-01-12 09:45:03	ga_s2am_ard_3-2-1_56JKM_2024-01-12_final
2024-01-12 09:45:06	ga_s2am_ard_3-2-1_55JGG_2024-01-12_final
2024-01-12 09:45:10	ga_s2am_ard_3-2-1_55JFG_2024-01-12_final
2024-01-12 09:45:13	ga_s2am_ard_3-2-1_55JEG_2024-01-12_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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