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

99 results

Time (local)	Label
2023-02-21 10:29:51	ga_s2am_ard_3-2-1_54LXP_2023-02-21_nrt.stac-item
2023-02-21 10:30:59	ga_s2am_ard_3-2-1_54LUK_2023-02-21_nrt.stac-item
2023-02-21 10:32:01	ga_s2am_ard_3-2-1_54KTF_2023-02-21_nrt.stac-item
2023-02-21 10:33:03	ga_s2am_ard_3-2-1_53KQS_2023-02-21_nrt.stac-item
2023-02-21 10:33:35	ga_s2am_ard_3-2-1_53KPQ_2023-02-21_nrt.stac-item
2023-02-21 10:34:58	ga_s2am_ard_3-2-1_53JQJ_2023-02-21_nrt.stac-item
2023-02-21 12:10:26	ga_s2am_ard_3-2-1_50LNP_2023-02-21_nrt.stac-item
2023-02-21 12:10:28	ga_s2am_ard_3-2-1_50LMP_2023-02-21_nrt.stac-item
2023-02-21 12:13:27	ga_s2am_ard_3-2-1_50KKC_2023-02-21_nrt.stac-item
2023-02-21 12:13:27	ga_s2am_ard_3-2-1_49KHT_2023-02-21_nrt.stac-item
2023-02-21 12:13:37	ga_s2am_ard_3-2-1_50KKB_2023-02-21_nrt.stac-item
2023-02-21 12:13:41	ga_s2am_ard_3-2-1_49KGS_2023-02-21_nrt.stac-item
2023-02-21 12:13:51	ga_s2am_ard_3-2-1_50KKA_2023-02-21_nrt.stac-item
2023-02-21 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-02-21_nrt.stac-item
2023-02-21 12:13:59	ga_s2am_ard_3-2-1_49KFR_2023-02-21_nrt.stac-item
2023-02-21 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2023-02-21_nrt.stac-item
2023-02-21 12:14:14	ga_s2am_ard_3-2-1_49KFQ_2023-02-21_nrt.stac-item
2023-02-21 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-02-21_nrt.stac-item
2023-02-21 12:14:39	ga_s2am_ard_3-2-1_49JGN_2023-02-21_nrt.stac-item
2023-02-21 12:14:43	ga_s2am_ard_3-2-1_49JFN_2023-02-21_nrt.stac-item
2023-02-21 12:14:50	ga_s2am_ard_3-2-1_49JFN_2023-02-21_nrt.stac-item
2023-02-21 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-02-21_nrt.stac-item
2023-02-21 12:14:57	ga_s2am_ard_3-2-1_49JFM_2023-02-21_nrt.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_nrt.stac-item
2023-02-21 12:15:12	ga_s2am_ard_3-2-1_49JFL_2023-02-21_nrt.stac-item
2023-02-21 12:15:17	ga_s2am_ard_3-2-1_49JGK_2023-02-21_nrt.stac-item
2023-02-21 12:15:19	ga_s2am_ard_3-2-1_49JFK_2023-02-21_nrt.stac-item
2023-02-22 09:59:36	ga_s2am_ard_3-2-1_55LHJ_2023-02-22_nrt.stac-item
2023-02-22 09:59:41	ga_s2am_ard_3-2-1_55LGJ_2023-02-22_nrt.stac-item
2023-02-22 09:59:45	ga_s2am_ard_3-2-1_55LFJ_2023-02-22_nrt.stac-item
2023-02-22 09:59:46	ga_s2am_ard_3-2-1_55LHH_2023-02-22_nrt.stac-item
2023-02-22 09:59:48	ga_s2am_ard_3-2-1_55LEJ_2023-02-22_nrt.stac-item
2023-02-22 09:59:55	ga_s2am_ard_3-2-1_55LGH_2023-02-22_nrt.stac-item
2023-02-22 09:59:59	ga_s2am_ard_3-2-1_55LFH_2023-02-22_nrt.stac-item
2023-02-22 10:00:02	ga_s2am_ard_3-2-1_55LEH_2023-02-22_nrt.stac-item
2023-02-22 10:00:06	ga_s2am_ard_3-2-1_55LDH_2023-02-22_nrt.stac-item
2023-02-22 10:00:10	ga_s2am_ard_3-2-1_55LGG_2023-02-22_nrt.stac-item
2023-02-22 10:00:14	ga_s2am_ard_3-2-1_55LFG_2023-02-22_nrt.stac-item
2023-02-22 10:00:17	ga_s2am_ard_3-2-1_55LEG_2023-02-22_nrt.stac-item
2023-02-22 10:00:20	ga_s2am_ard_3-2-1_55LDG_2023-02-22_nrt.stac-item
2023-02-22 10:00:25	ga_s2am_ard_3-2-1_55LGF_2023-02-22_nrt.stac-item
2023-02-22 10:00:28	ga_s2am_ard_3-2-1_55LFF_2023-02-22_nrt.stac-item
2023-02-22 10:00:34	ga_s2am_ard_3-2-1_55LDF_2023-02-22_nrt.stac-item
2023-02-22 10:00:38	ga_s2am_ard_3-2-1_55LGE_2023-02-22_nrt.stac-item
2023-02-22 10:00:42	ga_s2am_ard_3-2-1_55LFE_2023-02-22_nrt.stac-item
2023-02-22 10:00:46	ga_s2am_ard_3-2-1_55LEE_2023-02-22_nrt.stac-item
2023-02-22 10:00:49	ga_s2am_ard_3-2-1_55LGD_2023-02-22_nrt.stac-item
2023-02-22 10:00:49	ga_s2am_ard_3-2-1_55LDE_2023-02-22_nrt.stac-item
2023-02-22 10:00:57	ga_s2am_ard_3-2-1_55LFD_2023-02-22_nrt.stac-item
2023-02-22 10:01:01	ga_s2am_ard_3-2-1_55LED_2023-02-22_nrt.stac-item
2023-02-22 10:01:04	ga_s2am_ard_3-2-1_55LDD_2023-02-22_nrt.stac-item
2023-02-22 10:01:18	ga_s2am_ard_3-2-1_55LDC_2023-02-22_nrt.stac-item
2023-02-22 10:01:44	ga_s2am_ard_3-2-1_55KEA_2023-02-22_nrt.stac-item
2023-02-22 10:01:53	ga_s2am_ard_3-2-1_55KFV_2023-02-22_nrt.stac-item
2023-02-22 10:02:17	ga_s2am_ard_3-2-1_55KDU_2023-02-22_nrt.stac-item
2023-02-22 10:02:20	ga_s2am_ard_3-2-1_55KCU_2023-02-22_nrt.stac-item
2023-02-22 10:03:16	ga_s2am_ard_3-2-1_54KZV_2023-02-22_nrt.stac-item
2023-02-22 10:03:36	ga_s2am_ard_3-2-1_54KZU_2023-02-22_nrt.stac-item
2023-02-22 10:03:50	ga_s2am_ard_3-2-1_54JZT_2023-02-22_nrt.stac-item
2023-02-22 10:04:05	ga_s2am_ard_3-2-1_54JZS_2023-02-22_nrt.stac-item
2023-02-22 10:04:19	ga_s2am_ard_3-2-1_55JBL_2023-02-22_nrt.stac-item
2023-02-22 10:04:23	ga_s2am_ard_3-2-1_54JYR_2023-02-22_nrt.stac-item
2023-02-22 10:04:30	ga_s2am_ard_3-2-1_54JXR_2023-02-22_nrt.stac-item
2023-02-22 10:04:51	ga_s2am_ard_3-2-1_54JYP_2023-02-22_nrt.stac-item
2023-02-22 10:05:10	ga_s2am_ard_3-2-1_54JXN_2023-02-22_nrt.stac-item
2023-02-22 10:05:35	ga_s2am_ard_3-2-1_54JYL_2023-02-22_nrt.stac-item
2023-02-22 10:05:36	ga_s2am_ard_3-2-1_55HCE_2023-02-22_nrt.stac-item
2023-02-22 10:05:42	ga_s2am_ard_3-2-1_54JWL_2023-02-22_nrt.stac-item
2023-02-22 10:05:56	ga_s2am_ard_3-2-1_54HWK_2023-02-22_nrt.stac-item
2023-02-22 10:06:16	ga_s2am_ard_3-2-1_55HBC_2023-02-22_nrt.stac-item
2023-02-22 10:07:44	ga_s2am_ard_3-2-1_54HUC_2023-02-22_nrt.stac-item
2023-02-22 10:07:46	ga_s2am_ard_3-2-1_54HXB_2023-02-22_nrt.stac-item
2023-02-22 10:07:47	ga_s2am_ard_3-2-1_54HWB_2023-02-22_nrt.stac-item
2023-02-22 10:07:49	ga_s2am_ard_3-2-1_54HVB_2023-02-22_nrt.stac-item
2023-02-22 10:07:49	ga_s2am_ard_3-2-1_54HUB_2023-02-22_nrt.stac-item
2023-02-22 11:40:22	ga_s2am_ard_3-2-1_51LXJ_2023-02-22_nrt.stac-item
2023-02-22 11:40:40	ga_s2am_ard_3-2-1_51LWH_2023-02-22_nrt.stac-item
2023-02-22 11:40:46	ga_s2am_ard_3-2-1_51LUH_2023-02-22_nrt.stac-item
2023-02-22 11:40:58	ga_s2am_ard_3-2-1_51LVG_2023-02-22_nrt.stac-item
2023-02-22 11:41:04	ga_s2am_ard_3-2-1_51LXF_2023-02-22_nrt.stac-item
2023-02-22 11:42:02	ga_s2am_ard_3-2-1_51LTC_2023-02-22_nrt.stac-item
2023-02-22 11:42:11	ga_s2am_ard_3-2-1_51KVB_2023-02-22_nrt.stac-item
2023-02-22 11:42:32	ga_s2am_ard_3-2-1_51KTA_2023-02-22_nrt.stac-item
2023-02-22 11:42:39	ga_s2am_ard_3-2-1_51KVV_2023-02-22_nrt.stac-item
2023-02-22 11:42:43	ga_s2am_ard_3-2-1_51KUV_2023-02-22_nrt.stac-item
2023-02-22 11:43:30	ga_s2am_ard_3-2-1_50KRB_2023-02-22_nrt.stac-item
2023-02-22 11:43:41	ga_s2am_ard_3-2-1_51KUR_2023-02-22_nrt.stac-item
2023-02-22 11:43:56	ga_s2am_ard_3-2-1_51KUQ_2023-02-22_nrt.stac-item
2023-02-22 11:44:17	ga_s2am_ard_3-2-1_50KQU_2023-02-22_nrt.stac-item
2023-02-22 11:44:28	ga_s2am_ard_3-2-1_51JTN_2023-02-22_nrt.stac-item
2023-02-22 11:45:06	ga_s2am_ard_3-2-1_51JTK_2023-02-22_nrt.stac-item
2023-02-22 11:45:08	ga_s2am_ard_3-2-1_50JQQ_2023-02-22_nrt.stac-item
2023-02-22 11:45:09	ga_s2am_ard_3-2-1_50JPR_2023-02-22_nrt.stac-item
2023-02-22 11:45:41	ga_s2am_ard_3-2-1_51JTH_2023-02-22_nrt.stac-item
2023-02-22 11:45:48	ga_s2am_ard_3-2-1_50JPN_2023-02-22_nrt.stac-item
2023-02-22 11:45:54	ga_s2am_ard_3-2-1_51JTG_2023-02-22_nrt.stac-item
2023-02-22 11:46:05	ga_s2am_ard_3-2-1_51JTF_2023-02-22_nrt.stac-item
2023-02-22 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-02-22_nrt.stac-item
2023-02-22 11:47:07	ga_s2am_ard_3-2-1_50HMH_2023-02-22_nrt.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

All years