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
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_50KKA_2018-01-28_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_50KKB_2018-01-28_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49KGR_2018-01-28_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49KHR_2018-01-28_final.stac-item
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_54KZA_2018-01-29_final.stac-item
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_54KZB_2018-01-29_final.stac-item
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_55KBS_2018-01-29_final.stac-item
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_55KCS_2018-01-29_final.stac-item
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_55KDS_2018-01-29_final.stac-item
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_55KES_2018-01-29_final.stac-item
2018-01-31 10:43:07	ga_s2am_ard_3-2-1_53KMS_2018-01-31_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_56KKA_2018-02-02_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_56KKB_2018-02-02_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_56KLB_2018-02-02_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_55KGR_2018-02-02_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_55KGS_2018-02-02_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_55KHR_2018-02-02_final.stac-item
2018-02-02 09:41:04	ga_s2am_ard_3-2-1_55KHS_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51KXS_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51KYR_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51KYS_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51KZR_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51KZS_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_52KBA_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_52KBB_2018-02-02_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_52KCB_2018-02-02_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_53KKR_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_53KKS_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_53KLS_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_53KMS_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_52KGA_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_52KGB_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_52KHA_2018-02-13_final.stac-item
2018-02-13 10:52:02	ga_s2am_ard_3-2-1_52KHB_2018-02-13_final.stac-item
2018-02-25 09:50:51	ga_s2am_ard_3-2-1_55KFS_2018-02-25_final.stac-item
2018-02-25 09:50:51	ga_s2am_ard_3-2-1_55KGR_2018-02-25_final.stac-item
2018-02-25 09:50:51	ga_s2am_ard_3-2-1_55KGS_2018-02-25_final.stac-item
2018-02-25 09:52:43	ga_s2am_ard_3-2-1_55KDS_2018-02-25_final.stac-item
2018-02-25 09:52:43	ga_s2am_ard_3-2-1_55KES_2018-02-25_final.stac-item
2018-02-25 09:52:43	ga_s2am_ard_3-2-1_55KFS_2018-02-25_final.stac-item
2018-11-19 11:23:10	ga_s2am_ard_3-2-1_52KCB_2018-11-19_final.stac-item
2018-11-19 11:23:14	ga_s2am_ard_3-2-1_52KBB_2018-11-19_final.stac-item
2018-11-19 11:23:15	ga_s2am_ard_3-2-1_51KZS_2018-11-19_final.stac-item
2018-11-19 11:23:18	ga_s2am_ard_3-2-1_51KYS_2018-11-19_final.stac-item
2018-11-19 11:23:22	ga_s2am_ard_3-2-1_51KXS_2018-11-19_final.stac-item
2018-11-19 11:23:28	ga_s2am_ard_3-2-1_52KBA_2018-11-19_final.stac-item
2018-11-19 11:23:29	ga_s2am_ard_3-2-1_51KZR_2018-11-19_final.stac-item
2018-11-19 11:23:33	ga_s2am_ard_3-2-1_51KYR_2018-11-19_final.stac-item
2018-11-25 10:02:37	ga_s2am_ard_3-2-1_55KES_2018-11-25_final.stac-item
2018-11-25 10:02:40	ga_s2am_ard_3-2-1_55KDS_2018-11-25_final.stac-item
2018-11-25 10:02:44	ga_s2am_ard_3-2-1_55KCS_2018-11-25_final.stac-item
2018-11-25 10:02:47	ga_s2am_ard_3-2-1_55KBS_2018-11-25_final.stac-item
2018-11-25 10:02:47	ga_s2am_ard_3-2-1_54KZB_2018-11-25_final.stac-item
2018-11-25 10:03:01	ga_s2am_ard_3-2-1_54KZA_2018-11-25_final.stac-item
2018-11-29 11:23:08	ga_s2am_ard_3-2-1_52KCB_2018-11-29_final.stac-item
2018-11-29 11:23:12	ga_s2am_ard_3-2-1_52KBB_2018-11-29_final.stac-item
2018-11-29 11:23:12	ga_s2am_ard_3-2-1_51KZS_2018-11-29_final.stac-item
2018-11-29 11:23:16	ga_s2am_ard_3-2-1_51KYS_2018-11-29_final.stac-item
2018-11-29 11:23:19	ga_s2am_ard_3-2-1_51KXS_2018-11-29_final.stac-item
2018-11-29 11:23:26	ga_s2am_ard_3-2-1_52KBA_2018-11-29_final.stac-item
2018-11-29 11:23:27	ga_s2am_ard_3-2-1_51KZR_2018-11-29_final.stac-item
2018-11-29 11:23:30	ga_s2am_ard_3-2-1_51KYR_2018-11-29_final.stac-item
2018-12-02 09:52:33	ga_s2am_ard_3-2-1_55KGS_2018-12-02_final.stac-item
2018-12-02 09:52:37	ga_s2am_ard_3-2-1_55KFS_2018-12-02_final.stac-item
2018-12-02 09:52:41	ga_s2am_ard_3-2-1_55KES_2018-12-02_final.stac-item
2018-12-02 09:52:47	ga_s2am_ard_3-2-1_55KDS_2018-12-02_final.stac-item
2018-12-02 09:52:48	ga_s2am_ard_3-2-1_55KGR_2018-12-02_final.stac-item
2018-12-03 11:02:59	ga_s2am_ard_3-2-1_53KKS_2018-12-03_final.stac-item
2018-12-03 11:03:01	ga_s2am_ard_3-2-1_52KHB_2018-12-03_final.stac-item
2018-12-03 11:03:04	ga_s2am_ard_3-2-1_52KGB_2018-12-03_final.stac-item
2018-12-03 11:03:08	ga_s2am_ard_3-2-1_52KFB_2018-12-03_final.stac-item
2018-12-03 11:03:11	ga_s2am_ard_3-2-1_53KKR_2018-12-03_final.stac-item
2018-12-03 11:03:11	ga_s2am_ard_3-2-1_52KEB_2018-12-03_final.stac-item
2018-12-03 11:03:14	ga_s2am_ard_3-2-1_52KHA_2018-12-03_final.stac-item
2018-12-03 11:03:19	ga_s2am_ard_3-2-1_52KGA_2018-12-03_final.stac-item
2019-05-31 11:33:26	ga_s2am_ard_3-2-1_51KXS_2019-05-31_final.stac-item
2019-05-31 11:33:30	ga_s2am_ard_3-2-1_51KWS_2019-05-31_final.stac-item
2019-05-31 11:33:33	ga_s2am_ard_3-2-1_51KVS_2019-05-31_final.stac-item
2019-05-31 11:33:37	ga_s2am_ard_3-2-1_51KUS_2019-05-31_final.stac-item
2019-06-13 11:43:28	ga_s2am_ard_3-2-1_51KVS_2019-06-13_final.stac-item
2019-06-13 11:43:32	ga_s2am_ard_3-2-1_51KUS_2019-06-13_final.stac-item
2019-06-13 11:43:35	ga_s2am_ard_3-2-1_51KTS_2019-06-13_final.stac-item
2019-06-13 11:43:36	ga_s2am_ard_3-2-1_50KRB_2019-06-13_final.stac-item
2019-06-13 11:43:39	ga_s2am_ard_3-2-1_50KQB_2019-06-13_final.stac-item
2019-06-13 11:43:50	ga_s2am_ard_3-2-1_51KTR_2019-06-13_final.stac-item
2019-06-13 11:43:50	ga_s2am_ard_3-2-1_50KRA_2019-06-13_final.stac-item
2019-06-13 11:43:54	ga_s2am_ard_3-2-1_50KQA_2019-06-13_final.stac-item
2019-08-03 11:13:20	ga_s2am_ard_3-2-1_52KEB_2019-08-03_final.stac-item
2019-08-03 11:13:23	ga_s2am_ard_3-2-1_52KDB_2019-08-03_final.stac-item
2019-08-03 11:13:26	ga_s2am_ard_3-2-1_52KCB_2019-08-03_final.stac-item
2019-08-03 11:13:30	ga_s2am_ard_3-2-1_52KBB_2019-08-03_final.stac-item
2019-08-03 11:13:33	ga_s2am_ard_3-2-1_51KZS_2019-08-03_final.stac-item
2019-08-03 11:13:45	ga_s2am_ard_3-2-1_51KZR_2019-08-03_final.stac-item
2019-08-07 10:53:11	ga_s2am_ard_3-2-1_53KMS_2019-08-07_final.stac-item
2019-08-07 10:53:14	ga_s2am_ard_3-2-1_53KLS_2019-08-07_final.stac-item
2019-08-07 10:53:17	ga_s2am_ard_3-2-1_53KKS_2019-08-07_final.stac-item
2019-08-07 10:53:18	ga_s2am_ard_3-2-1_52KHB_2019-08-07_final.stac-item
2019-08-07 10:53:24	ga_s2am_ard_3-2-1_52KGB_2019-08-07_final.stac-item
2019-08-07 10:53:32	ga_s2am_ard_3-2-1_53KKR_2019-08-07_final.stac-item
2019-08-07 10:53:32	ga_s2am_ard_3-2-1_52KHA_2019-08-07_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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