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
2015-07-12 11:01:07	ga_s2am_ard_3-2-1_53KKA_2015-07-12_final.stac-item
2015-07-12 11:01:07	ga_s2am_ard_3-2-1_53KLA_2015-07-12_final.stac-item
2015-07-12 11:01:07	ga_s2am_ard_3-2-1_52KFF_2015-07-12_final.stac-item
2015-07-12 11:01:07	ga_s2am_ard_3-2-1_52KGF_2015-07-12_final.stac-item
2015-07-12 11:01:07	ga_s2am_ard_3-2-1_52KHF_2015-07-12_final.stac-item
2015-08-21 11:01:09	ga_s2am_ard_3-2-1_53KKA_2015-08-21_final.stac-item
2015-08-21 11:01:09	ga_s2am_ard_3-2-1_53KLA_2015-08-21_final.stac-item
2015-08-21 11:01:09	ga_s2am_ard_3-2-1_52KGF_2015-08-21_final.stac-item
2015-08-21 11:01:09	ga_s2am_ard_3-2-1_52KHF_2015-08-21_final
2015-08-21 11:01:09	ga_s2am_ard_3-2-1_52KFF_2015-08-21_final
2015-09-04 10:42:04	ga_s2am_ard_3-2-1_53KNA_2015-09-04_final.stac-item
2015-09-04 10:42:04	ga_s2am_ard_3-2-1_53KPA_2015-09-04_final.stac-item
2015-09-13 11:12:17	ga_s2am_ard_3-2-1_52KCF_2015-09-13_final.stac-item
2015-09-13 11:12:17	ga_s2am_ard_3-2-1_52KDF_2015-09-13_final.stac-item
2015-09-13 11:12:17	ga_s2am_ard_3-2-1_52KEF_2015-09-13_final.stac-item
2015-10-02 10:01:38	ga_s2am_ard_3-2-1_55KCA_2015-10-02_final.stac-item
2015-10-02 10:01:38	ga_s2am_ard_3-2-1_55KDA_2015-10-02_final.stac-item
2015-10-02 10:01:38	ga_s2am_ard_3-2-1_55KFA_2015-10-02_final.stac-item
2015-10-03 11:12:17	ga_s2am_ard_3-2-1_52KCF_2015-10-03_final.stac-item
2015-10-03 11:12:17	ga_s2am_ard_3-2-1_52KDF_2015-10-03_final.stac-item
2015-10-03 11:12:17	ga_s2am_ard_3-2-1_52KEF_2015-10-03_final.stac-item
2015-10-23 11:08:22	ga_s2am_ard_3-2-1_52KCF_2015-10-23_final.stac-item
2015-10-23 11:08:22	ga_s2am_ard_3-2-1_52KDF_2015-10-23_final.stac-item
2015-10-23 11:08:22	ga_s2am_ard_3-2-1_52KEF_2015-10-23_final.stac-item
2015-10-23 11:08:22	ga_s2am_ard_3-2-1_52KFF_2015-10-23_final.stac-item
2015-10-24 10:42:07	ga_s2am_ard_3-2-1_53KNA_2015-10-24_final.stac-item
2015-10-24 10:42:07	ga_s2am_ard_3-2-1_53KPA_2015-10-24_final.stac-item
2015-11-18 09:47:56	ga_s2am_ard_3-2-1_56KKF_2015-11-18_final.stac-item
2015-11-18 09:47:56	ga_s2am_ard_3-2-1_55KFA_2015-11-18_final.stac-item
2015-11-24 10:08:31	ga_s2am_ard_3-2-1_54KXF_2015-11-24_final.stac-item
2015-11-24 10:08:31	ga_s2am_ard_3-2-1_54KYF_2015-11-24_final.stac-item
2015-11-24 10:08:31	ga_s2am_ard_3-2-1_54KZF_2015-11-24_final.stac-item
2015-11-24 10:08:31	ga_s2am_ard_3-2-1_55KBA_2015-11-24_final.stac-item
2015-11-28 09:47:27	ga_s2am_ard_3-2-1_56KKF_2015-11-28_final.stac-item
2015-11-28 09:47:27	ga_s2am_ard_3-2-1_55KFA_2015-11-28_final.stac-item
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_54KTF_2015-11-30_final.stac-item
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_54KUF_2015-11-30_final.stac-item
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_54KVF_2015-11-30_final.stac-item
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_53KQA_2015-11-30_final.stac-item
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_53KRA_2015-11-30_final.stac-item
2018-01-29 09:57:02	ga_s2am_ard_3-2-1_55KFA_2018-01-29_final.stac-item
2018-02-05 09:50:50	ga_s2am_ard_3-2-1_56KKF_2018-02-05_final.stac-item
2018-02-05 09:50:50	ga_s2am_ard_3-2-1_55KFA_2018-02-05_final.stac-item
2018-02-09 11:11:58	ga_s2am_ard_3-2-1_52KCF_2018-02-09_final.stac-item
2018-02-09 11:11:58	ga_s2am_ard_3-2-1_52KDF_2018-02-09_final.stac-item
2018-02-09 11:11:58	ga_s2am_ard_3-2-1_52KEF_2018-02-09_final.stac-item
2018-02-09 11:11:58	ga_s2am_ard_3-2-1_52KFF_2018-02-09_final.stac-item
2018-02-10 10:37:23	ga_s2am_ard_3-2-1_54KTF_2018-02-10_final.stac-item
2018-02-10 10:37:23	ga_s2am_ard_3-2-1_53KNA_2018-02-10_final.stac-item
2018-02-10 10:37:23	ga_s2am_ard_3-2-1_53KPA_2018-02-10_final.stac-item
2018-02-10 10:37:23	ga_s2am_ard_3-2-1_53KQA_2018-02-10_final.stac-item
2018-02-10 10:37:23	ga_s2am_ard_3-2-1_53KRA_2018-02-10_final.stac-item
2018-02-14 10:17:02	ga_s2am_ard_3-2-1_54KVF_2018-02-14_final.stac-item
2018-02-14 10:17:02	ga_s2am_ard_3-2-1_54KWF_2018-02-14_final.stac-item
2018-02-14 10:17:02	ga_s2am_ard_3-2-1_54KXF_2018-02-14_final.stac-item
2018-02-14 10:17:02	ga_s2am_ard_3-2-1_54KYF_2018-02-14_final.stac-item
2018-02-25 09:50:51	ga_s2am_ard_3-2-1_56KKF_2018-02-25_final.stac-item
2018-02-25 09:50:51	ga_s2am_ard_3-2-1_55KFA_2018-02-25_final.stac-item
2018-11-17 10:41:48	ga_s2am_ard_3-2-1_54KTF_2018-11-17_final.stac-item
2018-11-17 10:41:53	ga_s2am_ard_3-2-1_53KRA_2018-11-17_final.stac-item
2018-11-17 10:41:57	ga_s2am_ard_3-2-1_53KQA_2018-11-17_final.stac-item
2018-11-17 10:42:01	ga_s2am_ard_3-2-1_53KPA_2018-11-17_final.stac-item
2018-11-17 10:42:04	ga_s2am_ard_3-2-1_53KNA_2018-11-17_final.stac-item
2018-11-18 10:11:42	ga_s2am_ard_3-2-1_55KCA_2018-11-18_final.stac-item
2018-11-18 10:11:45	ga_s2am_ard_3-2-1_55KBA_2018-11-18_final.stac-item
2018-11-18 10:11:46	ga_s2am_ard_3-2-1_54KZF_2018-11-18_final.stac-item
2018-11-18 10:11:50	ga_s2am_ard_3-2-1_54KYF_2018-11-18_final.stac-item
2018-11-18 10:11:56	ga_s2am_ard_3-2-1_54KXF_2018-11-18_final.stac-item
2018-11-23 11:01:56	ga_s2am_ard_3-2-1_53KLA_2018-11-23_final.stac-item
2018-11-23 11:02:03	ga_s2am_ard_3-2-1_53KKA_2018-11-23_final.stac-item
2018-11-23 11:02:04	ga_s2am_ard_3-2-1_52KHF_2018-11-23_final.stac-item
2018-11-23 11:02:08	ga_s2am_ard_3-2-1_52KGF_2018-11-23_final.stac-item
2018-11-23 11:02:11	ga_s2am_ard_3-2-1_52KFF_2018-11-23_final.stac-item
2018-11-25 10:01:35	ga_s2am_ard_3-2-1_55KFA_2018-11-25_final.stac-item
2018-11-25 10:01:42	ga_s2am_ard_3-2-1_55KDA_2018-11-25_final.stac-item
2018-11-25 10:01:45	ga_s2am_ard_3-2-1_55KCA_2018-11-25_final.stac-item
2018-12-02 09:51:31	ga_s2am_ard_3-2-1_56KKF_2018-12-02_final.stac-item
2018-12-02 09:51:39	ga_s2am_ard_3-2-1_55KFA_2018-12-02_final.stac-item
2018-12-03 11:01:55	ga_s2am_ard_3-2-1_53KLA_2018-12-03_final.stac-item
2018-12-03 11:02:02	ga_s2am_ard_3-2-1_53KKA_2018-12-03_final.stac-item
2018-12-03 11:02:03	ga_s2am_ard_3-2-1_52KHF_2018-12-03_final.stac-item
2018-12-03 11:02:07	ga_s2am_ard_3-2-1_52KGF_2018-12-03_final.stac-item
2018-12-03 11:02:10	ga_s2am_ard_3-2-1_52KFF_2018-12-03_final.stac-item
2018-12-10 10:51:57	ga_s2am_ard_3-2-1_53KNA_2018-12-10_final.stac-item
2018-12-10 10:52:00	ga_s2am_ard_3-2-1_53KMA_2018-12-10_final.stac-item
2018-12-10 10:52:03	ga_s2am_ard_3-2-1_53KLA_2018-12-10_final.stac-item
2018-12-10 10:52:06	ga_s2am_ard_3-2-1_53KKA_2018-12-10_final.stac-item
2018-12-10 10:52:11	ga_s2am_ard_3-2-1_52KHF_2018-12-10_final.stac-item
2019-03-18 10:11:42	ga_s2am_ard_3-2-1_55KCA_2019-03-18_final.stac-item
2019-03-18 10:11:49	ga_s2am_ard_3-2-1_55KCA_2019-03-18_final.stac-item
2019-03-18 10:11:50	ga_s2am_ard_3-2-1_55KBA_2019-03-18_final.stac-item
2019-03-18 10:11:51	ga_s2am_ard_3-2-1_54KZF_2019-03-18_final.stac-item
2019-03-18 10:11:53	ga_s2am_ard_3-2-1_54KYF_2019-03-18_final.stac-item
2019-03-18 10:11:59	ga_s2am_ard_3-2-1_54KXF_2019-03-18_final.stac-item
2019-03-24 10:31:55	ga_s2am_ard_3-2-1_54KVF_2019-03-24_final.stac-item
2019-03-24 10:31:59	ga_s2am_ard_3-2-1_54KUF_2019-03-24_final.stac-item
2019-03-24 10:32:02	ga_s2am_ard_3-2-1_54KTF_2019-03-24_final.stac-item
2019-03-24 10:32:03	ga_s2am_ard_3-2-1_53KRA_2019-03-24_final.stac-item
2019-03-24 10:32:09	ga_s2am_ard_3-2-1_53KQA_2019-03-24_final.stac-item
2019-06-07 09:41:44	ga_s2am_ard_3-2-1_56KLF_2019-06-07_final.stac-item

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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