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
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_54KTB_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_54KUB_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_53KPS_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_53KQS_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_53KRR_2016-07-27_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_53KRS_2016-07-27_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_54KZA_2016-07-28_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_54KZB_2016-07-28_final.stac-item
2016-07-28 10:00:36	ga_s2am_ard_3-2-1_55KBS_2016-07-28_final.stac-item
2016-07-29 09:32:22	ga_s2am_ard_3-2-1_56KPB_2016-07-29_final.stac-item
2016-07-29 09:32:22	ga_s2am_ard_3-2-1_56KNB_2016-07-29_final.stac-item
2016-07-29 09:32:22	ga_s2am_ard_3-2-1_56KLB_2016-07-29_final.stac-item
2016-07-29 09:32:22	ga_s2am_ard_3-2-1_56KMB_2016-07-29_final.stac-item
2016-07-31 10:11:02	ga_s2am_ard_3-2-1_54KWB_2016-07-31_final.stac-item
2016-07-31 10:11:02	ga_s2am_ard_3-2-1_54KXB_2016-07-31_final.stac-item
2016-07-31 10:11:02	ga_s2am_ard_3-2-1_54KYB_2016-07-31_final.stac-item
2016-07-31 10:11:02	ga_s2am_ard_3-2-1_54KZA_2016-07-31_final.stac-item
2016-07-31 10:11:02	ga_s2am_ard_3-2-1_54KZB_2016-07-31_final.stac-item
2016-07-31 10:11:02	ga_s2am_ard_3-2-1_55KBS_2016-07-31_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51KUS_2016-08-04_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51KVS_2016-08-04_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51KWS_2016-08-04_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51KXS_2016-08-04_final.stac-item
2016-08-08 09:32:21	ga_s2am_ard_3-2-1_56KPB_2016-08-08_final.stac-item
2016-08-08 09:32:21	ga_s2am_ard_3-2-1_56KNB_2016-08-08_final.stac-item
2016-08-08 09:32:21	ga_s2am_ard_3-2-1_56KLB_2016-08-08_final.stac-item
2016-08-08 09:32:21	ga_s2am_ard_3-2-1_56KMB_2016-08-08_final.stac-item
2023-08-25 09:42:42	ga_s2am_ard_3-2-1_56KMB_2023-08-25_final
2023-08-25 09:42:46	ga_s2am_ard_3-2-1_56KLB_2023-08-25_final
2023-08-25 09:42:49	ga_s2am_ard_3-2-1_56KKB_2023-08-25_final
2023-08-25 09:42:49	ga_s2am_ard_3-2-1_55KHS_2023-08-25_final
2023-08-25 09:42:52	ga_s2am_ard_3-2-1_55KGS_2023-08-25_final
2023-08-25 09:43:04	ga_s2am_ard_3-2-1_55KHR_2023-08-25_final
2023-08-25 11:23:22	ga_s2am_ard_3-2-1_52KCB_2023-08-25_final
2023-08-25 11:23:26	ga_s2am_ard_3-2-1_52KBB_2023-08-25_final
2023-08-25 11:23:27	ga_s2am_ard_3-2-1_51KZS_2023-08-25_final
2023-08-25 11:23:31	ga_s2am_ard_3-2-1_51KYS_2023-08-25_final
2023-08-25 11:23:34	ga_s2am_ard_3-2-1_51KXS_2023-08-25_final
2023-08-25 11:23:41	ga_s2am_ard_3-2-1_51KZR_2023-08-25_final
2023-08-26 10:53:16	ga_s2am_ard_3-2-1_53KMS_2023-08-26_final
2023-08-26 10:53:18	ga_s2am_ard_3-2-1_53KLS_2023-08-26_final
2023-08-26 10:53:20	ga_s2am_ard_3-2-1_53KKS_2023-08-26_final
2023-08-26 10:53:20	ga_s2am_ard_3-2-1_52KHB_2023-08-26_final
2023-08-26 10:53:26	ga_s2am_ard_3-2-1_52KGB_2023-08-26_final
2023-08-26 10:53:34	ga_s2am_ard_3-2-1_52KHA_2023-08-26_final
2023-08-31 10:02:50	ga_s2am_ard_3-2-1_55KES_2023-08-31_final
2023-08-31 10:02:53	ga_s2am_ard_3-2-1_55KDS_2023-08-31_final
2023-08-31 10:02:57	ga_s2am_ard_3-2-1_55KCS_2023-08-31_final
2023-08-31 10:03:00	ga_s2am_ard_3-2-1_55KBS_2023-08-31_final
2023-08-31 10:03:00	ga_s2am_ard_3-2-1_54KZB_2023-08-31_final
2023-08-31 10:03:15	ga_s2am_ard_3-2-1_54KZA_2023-08-31_final
2023-09-01 09:32:39	ga_s2am_ard_3-2-1_56KPB_2023-09-01_final
2023-09-01 09:32:43	ga_s2am_ard_3-2-1_56KNB_2023-09-01_final
2023-09-01 09:32:46	ga_s2am_ard_3-2-1_56KMB_2023-09-01_final
2023-09-01 09:32:52	ga_s2am_ard_3-2-1_56KLB_2023-09-01_final
2023-09-03 10:12:55	ga_s2am_ard_3-2-1_55KBS_2023-09-03_final
2023-09-03 10:12:55	ga_s2am_ard_3-2-1_54KZB_2023-09-03_final
2023-09-03 10:12:59	ga_s2am_ard_3-2-1_54KYB_2023-09-03_final
2023-09-03 10:13:03	ga_s2am_ard_3-2-1_54KXB_2023-09-03_final
2023-09-03 10:13:09	ga_s2am_ard_3-2-1_54KWB_2023-09-03_final
2023-09-03 10:13:10	ga_s2am_ard_3-2-1_54KZA_2023-09-03_final
2023-09-04 09:42:41	ga_s2am_ard_3-2-1_56KMB_2023-09-04_final
2023-09-04 09:42:45	ga_s2am_ard_3-2-1_56KLB_2023-09-04_final
2023-09-04 09:42:48	ga_s2am_ard_3-2-1_56KKB_2023-09-04_final
2023-09-04 09:42:48	ga_s2am_ard_3-2-1_55KHS_2023-09-04_final
2023-09-04 09:42:52	ga_s2am_ard_3-2-1_55KGS_2023-09-04_final
2023-09-04 09:43:03	ga_s2am_ard_3-2-1_55KHR_2023-09-04_final
2023-09-04 11:23:21	ga_s2am_ard_3-2-1_52KCB_2023-09-04_final
2023-09-04 11:23:26	ga_s2am_ard_3-2-1_52KBB_2023-09-04_final
2023-09-04 11:23:26	ga_s2am_ard_3-2-1_51KZS_2023-09-04_final
2023-09-04 11:23:30	ga_s2am_ard_3-2-1_51KYS_2023-09-04_final
2023-09-04 11:23:33	ga_s2am_ard_3-2-1_51KXS_2023-09-04_final
2023-09-04 11:23:41	ga_s2am_ard_3-2-1_51KZR_2023-09-04_final
2023-09-06 10:22:58	ga_s2am_ard_3-2-1_54KXB_2023-09-06_final
2023-09-06 10:23:02	ga_s2am_ard_3-2-1_54KWB_2023-09-06_final
2023-09-06 10:23:05	ga_s2am_ard_3-2-1_54KVB_2023-09-06_final
2023-09-06 10:23:08	ga_s2am_ard_3-2-1_54KUB_2023-09-06_final
2023-09-26 10:22:55	ga_s2am_ard_3-2-1_54KXB_2023-09-26_final
2023-09-26 10:22:59	ga_s2am_ard_3-2-1_54KWB_2023-09-26_final
2023-09-26 10:23:02	ga_s2am_ard_3-2-1_54KVB_2023-09-26_final
2023-09-26 10:23:05	ga_s2am_ard_3-2-1_54KUB_2023-09-26_final
2023-09-27 11:33:26	ga_s2am_ard_3-2-1_51KXS_2023-09-27_final
2023-09-27 11:33:29	ga_s2am_ard_3-2-1_51KWS_2023-09-27_final
2023-09-27 11:33:33	ga_s2am_ard_3-2-1_51KVS_2023-09-27_final
2023-09-27 11:33:36	ga_s2am_ard_3-2-1_51KUS_2023-09-27_final
2023-09-29 10:33:00	ga_s2am_ard_3-2-1_54KUB_2023-09-29_final
2023-09-29 10:33:04	ga_s2am_ard_3-2-1_54KTB_2023-09-29_final
2023-09-29 10:33:04	ga_s2am_ard_3-2-1_53KRS_2023-09-29_final
2023-09-29 10:33:08	ga_s2am_ard_3-2-1_53KQS_2023-09-29_final
2023-09-29 10:33:14	ga_s2am_ard_3-2-1_53KPS_2023-09-29_final
2023-09-29 10:33:17	ga_s2am_ard_3-2-1_53KRR_2023-09-29_final
2023-09-30 10:02:47	ga_s2am_ard_3-2-1_55KES_2023-09-30_final
2023-09-30 10:02:50	ga_s2am_ard_3-2-1_55KDS_2023-09-30_final
2023-09-30 10:02:54	ga_s2am_ard_3-2-1_55KCS_2023-09-30_final
2023-09-30 10:02:57	ga_s2am_ard_3-2-1_55KBS_2023-09-30_final
2023-09-30 10:02:57	ga_s2am_ard_3-2-1_54KZB_2023-09-30_final
2023-09-30 10:03:11	ga_s2am_ard_3-2-1_54KZA_2023-09-30_final
2023-10-01 09:32:36	ga_s2am_ard_3-2-1_56KPB_2023-10-01_final
2023-10-01 09:32:40	ga_s2am_ard_3-2-1_56KNB_2023-10-01_final
2023-10-01 09:32:43	ga_s2am_ard_3-2-1_56KMB_2023-10-01_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