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
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50KKA_2017-06-19_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50KKB_2017-06-19_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50KLA_2017-06-19_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KKA_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KKB_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLA_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_56KLB_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGR_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KGS_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KHR_2017-06-27_final.stac-item
2017-06-27 09:42:11	ga_s2am_ard_3-2-1_55KHS_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KBA_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KBB_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KCA_2017-06-27_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_52KCB_2017-06-27_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50KQA_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50KQB_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50KRA_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50KRB_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_51KTR_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_51KTS_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_51KUR_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_51KUS_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_51KVS_2017-07-03_final.stac-item
2017-07-25 10:37:28	ga_s2am_ard_3-2-1_53KPR_2017-07-25_final.stac-item
2017-07-25 10:37:28	ga_s2am_ard_3-2-1_53KPS_2017-07-25_final.stac-item
2017-07-25 10:37:28	ga_s2am_ard_3-2-1_53KQR_2017-07-25_final.stac-item
2017-07-25 10:37:28	ga_s2am_ard_3-2-1_53KQS_2017-07-25_final.stac-item
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_53KMS_2017-07-25_final.stac-item
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_53KNR_2017-07-25_final.stac-item
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_53KNS_2017-07-25_final.stac-item
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_53KPR_2017-07-25_final.stac-item
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_53KPS_2017-07-25_final.stac-item
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KNR_2017-08-14_final.stac-item
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KNS_2017-08-14_final.stac-item
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KPR_2017-08-14_final.stac-item
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KPS_2017-08-14_final.stac-item
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KQR_2017-08-14_final.stac-item
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KQS_2017-08-14_final.stac-item
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_53KMS_2017-08-14_final.stac-item
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_53KNR_2017-08-14_final.stac-item
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_53KNS_2017-08-14_final.stac-item
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_53KPR_2017-08-14_final.stac-item
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_53KPS_2017-08-14_final.stac-item
2019-07-17 11:23:40	ga_s2am_ard_3-2-1_52KBA_2019-07-17_final.stac-item
2019-07-17 11:23:41	ga_s2am_ard_3-2-1_51KZR_2019-07-17_final.stac-item
2019-07-17 11:23:44	ga_s2am_ard_3-2-1_51KYR_2019-07-17_final.stac-item
2019-07-17 11:23:48	ga_s2am_ard_3-2-1_51KXR_2019-07-17_final.stac-item
2023-09-09 12:13:49	ga_s2am_ard_3-2-1_49KGS_2023-09-09_nrt
2023-09-09 12:13:52	ga_s2am_ard_3-2-1_49KFS_2023-09-09_nrt
2023-09-09 12:13:59	ga_s2am_ard_3-2-1_50KKA_2023-09-09_final
2023-09-09 12:14:00	ga_s2am_ard_3-2-1_49KHR_2023-09-09_final
2023-09-09 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-09-09_final
2023-09-09 12:14:07	ga_s2am_ard_3-2-1_49KFR_2023-09-09_nrt
2023-09-13 11:53:36	ga_s2am_ard_3-2-1_50KQB_2023-09-13_final
2023-09-13 11:53:40	ga_s2am_ard_3-2-1_50KPB_2023-09-13_final
2023-09-13 11:53:43	ga_s2am_ard_3-2-1_50KNB_2023-09-13_final
2023-09-13 11:53:47	ga_s2am_ard_3-2-1_50KMB_2023-09-13_final
2023-09-13 11:53:51	ga_s2am_ard_3-2-1_50KQA_2023-09-13_final
2023-09-13 11:53:55	ga_s2am_ard_3-2-1_50KPA_2023-09-13_final
2023-09-13 11:53:58	ga_s2am_ard_3-2-1_50KNA_2023-09-13_final
2023-09-15 10:53:14	ga_s2am_ard_3-2-1_53KMS_2023-09-15_final
2023-09-15 10:53:16	ga_s2am_ard_3-2-1_53KLS_2023-09-15_final
2023-09-15 10:53:18	ga_s2am_ard_3-2-1_53KKS_2023-09-15_final
2023-09-15 10:53:18	ga_s2am_ard_3-2-1_52KHB_2023-09-15_final
2023-09-15 10:53:24	ga_s2am_ard_3-2-1_52KGB_2023-09-15_final
2023-09-15 10:53:29	ga_s2am_ard_3-2-1_53KLR_2023-09-15_final
2023-09-15 10:53:32	ga_s2am_ard_3-2-1_53KKR_2023-09-15_final
2023-09-15 10:53:32	ga_s2am_ard_3-2-1_52KHA_2023-09-15_final
2023-09-15 10:53:36	ga_s2am_ard_3-2-1_52KGA_2023-09-15_final
2023-09-16 10:22:57	ga_s2am_ard_3-2-1_54KXB_2023-09-16_final
2023-09-16 10:23:00	ga_s2am_ard_3-2-1_54KWB_2023-09-16_final
2023-09-16 10:23:04	ga_s2am_ard_3-2-1_54KVB_2023-09-16_final
2023-09-16 10:23:07	ga_s2am_ard_3-2-1_54KUB_2023-09-16_final
2023-09-16 10:23:10	ga_s2am_ard_3-2-1_54KXA_2023-09-16_final
2023-09-16 10:23:15	ga_s2am_ard_3-2-1_54KWA_2023-09-16_final
2023-09-16 10:23:21	ga_s2am_ard_3-2-1_54KUA_2023-09-16_final
2023-11-03 11:23:16	ga_s2am_ard_3-2-1_52KCB_2023-11-03_final
2023-11-03 11:23:20	ga_s2am_ard_3-2-1_52KBB_2023-11-03_final
2023-11-03 11:23:20	ga_s2am_ard_3-2-1_51KZS_2023-11-03_final
2023-11-03 11:23:23	ga_s2am_ard_3-2-1_51KYS_2023-11-03_final
2023-11-03 11:23:26	ga_s2am_ard_3-2-1_52KCA_2023-11-03_final
2023-11-03 11:23:27	ga_s2am_ard_3-2-1_51KXS_2023-11-03_final
2023-11-03 11:23:34	ga_s2am_ard_3-2-1_52KBA_2023-11-03_final
2023-11-03 11:23:34	ga_s2am_ard_3-2-1_51KZR_2023-11-03_final
2023-11-03 11:23:38	ga_s2am_ard_3-2-1_51KYR_2023-11-03_final
2023-11-03 11:23:41	ga_s2am_ard_3-2-1_51KXR_2023-11-03_final
2023-12-07 09:22:34	ga_s2am_ard_3-2-1_56KPB_2023-12-06_final
2023-12-07 09:22:47	ga_s2am_ard_3-2-1_56KPA_2023-12-06_nrt
2023-12-12 11:53:27	ga_s2am_ard_3-2-1_50KQB_2023-12-12_final
2023-12-12 11:53:31	ga_s2am_ard_3-2-1_50KPB_2023-12-12_final
2023-12-12 11:53:34	ga_s2am_ard_3-2-1_50KNB_2023-12-12_final
2023-12-12 11:53:38	ga_s2am_ard_3-2-1_50KMB_2023-12-12_final
2023-12-15 12:03:29	ga_s2am_ard_3-2-1_50KNB_2023-12-15_final
2023-12-15 12:03:33	ga_s2am_ard_3-2-1_50KMB_2023-12-15_final
2023-12-15 12:03:37	ga_s2am_ard_3-2-1_50KLB_2023-12-15_final
2023-12-15 12:03:40	ga_s2am_ard_3-2-1_50KKB_2023-12-15_final
2023-12-15 12:03:40	ga_s2am_ard_3-2-1_49KHS_2023-12-15_final
2023-12-15 12:03:51	ga_s2am_ard_3-2-1_50KLA_2023-12-15_final
2023-12-15 12:03:55	ga_s2am_ard_3-2-1_50KKA_2023-12-15_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

All years