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
2018-12-19 09:47:57	ga_s2am_ard_3-2-1_55GCR_2018-12-19_final.stac-item
2018-12-19 09:48:00	ga_s2am_ard_3-2-1_55GBR_2018-12-19_final.stac-item
2018-12-19 09:48:11	ga_s2am_ard_3-2-1_55GCQ_2018-12-19_final.stac-item
2018-12-19 09:48:26	ga_s2am_ard_3-2-1_55GCP_2018-12-19_final.stac-item
2018-12-19 09:48:40	ga_s2am_ard_3-2-1_55GCN_2018-12-19_final.stac-item
2018-12-25 10:05:13	ga_s2am_ard_3-2-1_55JBG_2018-12-25_final.stac-item
2018-12-25 10:05:27	ga_s2am_ard_3-2-1_55JBF_2018-12-25_final.stac-item
2018-12-25 10:05:42	ga_s2am_ard_3-2-1_55HBE_2018-12-25_final.stac-item
2018-12-28 10:12:14	ga_s2am_ard_3-2-1_55KBU_2018-12-28_final.stac-item
2018-12-28 10:12:15	ga_s2am_ard_3-2-1_54KZD_2018-12-28_final.stac-item
2018-12-28 10:12:28	ga_s2am_ard_3-2-1_55KBT_2018-12-28_final.stac-item
2018-12-28 10:12:29	ga_s2am_ard_3-2-1_54KZC_2018-12-28_final.stac-item
2018-12-28 10:12:43	ga_s2am_ard_3-2-1_55KBS_2018-12-28_final.stac-item
2018-12-28 10:12:43	ga_s2am_ard_3-2-1_54KZB_2018-12-28_final.stac-item
2018-12-28 10:12:58	ga_s2am_ard_3-2-1_54KZA_2018-12-28_final.stac-item
2019-01-01 09:57:55	ga_s2am_ard_3-2-1_55GCR_2019-01-01_final.stac-item
2019-01-01 09:57:59	ga_s2am_ard_3-2-1_55GBR_2019-01-01_final.stac-item
2019-01-01 09:58:07	ga_s2am_ard_3-2-1_55GCQ_2019-01-01_final.stac-item
2019-01-31 09:55:08	ga_s2am_ard_3-2-1_55JBH_2019-01-31_final.stac-item
2019-01-31 09:55:21	ga_s2am_ard_3-2-1_55JBG_2019-01-31_final.stac-item
2019-01-31 09:55:36	ga_s2am_ard_3-2-1_55JBF_2019-01-31_final.stac-item
2019-01-31 09:55:50	ga_s2am_ard_3-2-1_55HBE_2019-01-31_final.stac-item
2019-01-31 09:56:05	ga_s2am_ard_3-2-1_55HBD_2019-01-31_final.stac-item
2019-01-31 09:56:19	ga_s2am_ard_3-2-1_55HBC_2019-01-31_final.stac-item
2019-01-31 09:56:34	ga_s2am_ard_3-2-1_55HBB_2019-01-31_final.stac-item
2019-01-31 09:56:49	ga_s2am_ard_3-2-1_55HBA_2019-01-31_final.stac-item
2019-01-31 09:57:03	ga_s2am_ard_3-2-1_55HBV_2019-01-31_final.stac-item
2019-01-31 09:57:14	ga_s2am_ard_3-2-1_55HCU_2019-01-31_final.stac-item
2019-01-31 09:57:18	ga_s2am_ard_3-2-1_55HBU_2019-01-31_final.stac-item
2019-01-31 09:57:29	ga_s2am_ard_3-2-1_55HCT_2019-01-31_final.stac-item
2019-01-31 09:57:32	ga_s2am_ard_3-2-1_55HBT_2019-01-31_final.stac-item
2019-01-31 09:57:44	ga_s2am_ard_3-2-1_55HCS_2019-01-31_final.stac-item
2019-01-31 09:57:47	ga_s2am_ard_3-2-1_55HBS_2019-01-31_final.stac-item
2019-02-09 10:19:35	ga_s2am_ard_3-2-1_54LZQ_2019-02-09_final.stac-item
2019-02-10 09:55:08	ga_s2am_ard_3-2-1_55JBH_2019-02-10_final.stac-item
2019-02-10 09:55:21	ga_s2am_ard_3-2-1_55JBG_2019-02-10_final.stac-item
2019-02-10 09:55:36	ga_s2am_ard_3-2-1_55JBF_2019-02-10_final.stac-item
2019-02-10 09:55:50	ga_s2am_ard_3-2-1_55HBE_2019-02-10_final.stac-item
2019-02-20 09:56:48	ga_s2am_ard_3-2-1_55HBA_2019-02-20_final.stac-item
2019-02-20 09:57:28	ga_s2am_ard_3-2-1_55HBT_2019-02-20_final.stac-item
2019-02-20 09:57:34	ga_s2am_ard_3-2-1_55HBT_2019-02-20_final.stac-item
2019-02-20 09:57:46	ga_s2am_ard_3-2-1_55HBS_2019-02-20_final.stac-item
2019-02-20 09:57:57	ga_s2am_ard_3-2-1_55GCR_2019-02-20_final.stac-item
2019-02-20 09:58:01	ga_s2am_ard_3-2-1_55GBR_2019-02-20_final.stac-item
2019-02-20 09:58:10	ga_s2am_ard_3-2-1_55GCQ_2019-02-20_final.stac-item
2019-02-23 10:02:35	ga_s2am_ard_3-2-1_55KBT_2019-02-23_final.stac-item
2019-02-23 10:02:37	ga_s2am_ard_3-2-1_54KZC_2019-02-23_final.stac-item
2019-02-23 10:02:50	ga_s2am_ard_3-2-1_55KBS_2019-02-23_final.stac-item
2019-02-23 10:02:50	ga_s2am_ard_3-2-1_54KZB_2019-02-23_final.stac-item
2019-02-23 10:03:05	ga_s2am_ard_3-2-1_55KBR_2019-02-23_final.stac-item
2019-02-23 10:03:05	ga_s2am_ard_3-2-1_54KZA_2019-02-23_final.stac-item
2019-02-23 10:03:19	ga_s2am_ard_3-2-1_55KBQ_2019-02-23_final.stac-item
2019-02-23 10:03:20	ga_s2am_ard_3-2-1_54KZV_2019-02-23_final.stac-item
2019-02-23 10:03:34	ga_s2am_ard_3-2-1_55KBP_2019-02-23_final.stac-item
2019-02-23 10:03:34	ga_s2am_ard_3-2-1_54KZU_2019-02-23_final.stac-item
2019-02-23 10:03:48	ga_s2am_ard_3-2-1_54JZT_2019-02-23_final.stac-item
2019-02-23 10:03:49	ga_s2am_ard_3-2-1_55JBN_2019-02-23_final.stac-item
2019-02-23 10:04:03	ga_s2am_ard_3-2-1_54JZS_2019-02-23_final.stac-item
2019-02-23 10:04:03	ga_s2am_ard_3-2-1_55JBM_2019-02-23_final.stac-item
2019-02-23 10:04:18	ga_s2am_ard_3-2-1_55JBL_2019-02-23_final.stac-item
2023-02-12 10:03:51	ga_s2am_ard_3-2-1_54JZT_2023-02-12_final
2023-02-12 10:03:51	ga_s2am_ard_3-2-1_55JBN_2023-02-12_final
2023-02-12 10:04:05	ga_s2am_ard_3-2-1_54JZS_2023-02-12_final
2023-02-12 10:04:06	ga_s2am_ard_3-2-1_55JBM_2023-02-12_final
2023-02-12 10:04:20	ga_s2am_ard_3-2-1_55JBL_2023-02-12_nrt.stac-item
2023-02-12 10:04:20	ga_s2am_ard_3-2-1_55JBL_2023-02-12_final
2023-02-12 10:04:35	ga_s2am_ard_3-2-1_55JBK_2023-02-12_nrt.stac-item
2023-02-12 10:04:35	ga_s2am_ard_3-2-1_55JBK_2023-02-12_final
2023-02-12 10:04:49	ga_s2am_ard_3-2-1_55JBJ_2023-02-12_nrt.stac-item
2023-02-12 10:04:49	ga_s2am_ard_3-2-1_55JBJ_2023-02-12_final
2023-02-12 10:05:04	ga_s2am_ard_3-2-1_55JBH_2023-02-12_nrt.stac-item
2023-02-12 10:05:04	ga_s2am_ard_3-2-1_55JBH_2023-02-12_final
2023-02-12 10:05:18	ga_s2am_ard_3-2-1_55JBG_2023-02-12_nrt.stac-item
2023-02-12 10:05:18	ga_s2am_ard_3-2-1_55JBG_2023-02-12_final
2023-02-12 10:05:33	ga_s2am_ard_3-2-1_55JBF_2023-02-12_final
2023-02-12 10:05:47	ga_s2am_ard_3-2-1_55HBE_2023-02-12_final
2023-02-19 09:55:08	ga_s2am_ard_3-2-1_55JBH_2023-02-19_nrt.stac-item
2023-02-19 09:55:08	ga_s2am_ard_3-2-1_55JBH_2023-02-19_final
2023-02-19 09:55:21	ga_s2am_ard_3-2-1_55JBG_2023-02-19_final
2023-02-19 09:55:36	ga_s2am_ard_3-2-1_55JBF_2023-02-19_nrt.stac-item
2023-02-19 09:55:36	ga_s2am_ard_3-2-1_55JBF_2023-02-19_final
2023-02-19 09:55:51	ga_s2am_ard_3-2-1_55HBE_2023-02-19_final
2023-02-19 09:56:05	ga_s2am_ard_3-2-1_55HBD_2023-02-19_final
2023-02-19 09:56:20	ga_s2am_ard_3-2-1_55HBC_2023-02-19_final
2023-02-19 09:56:34	ga_s2am_ard_3-2-1_55HBB_2023-02-19_final
2023-02-19 09:56:49	ga_s2am_ard_3-2-1_55HBA_2023-02-19_final
2023-02-19 09:57:03	ga_s2am_ard_3-2-1_55HBV_2023-02-19_final
2023-02-19 09:57:14	ga_s2am_ard_3-2-1_55HCU_2023-02-19_final
2023-02-19 09:57:18	ga_s2am_ard_3-2-1_55HBU_2023-02-19_final
2023-02-19 09:57:29	ga_s2am_ard_3-2-1_55HCT_2023-02-19_final
2023-02-19 09:57:33	ga_s2am_ard_3-2-1_55HBT_2023-02-19_final
2023-02-19 09:57:44	ga_s2am_ard_3-2-1_55HCS_2023-02-19_final
2023-02-19 09:57:47	ga_s2am_ard_3-2-1_55HBS_2023-02-19_nrt.stac-item
2023-02-19 09:57:47	ga_s2am_ard_3-2-1_55HBS_2023-02-19_final
2023-02-19 09:57:58	ga_s2am_ard_3-2-1_55GCR_2023-02-19_nrt.stac-item
2023-02-19 09:57:58	ga_s2am_ard_3-2-1_55GCR_2023-02-19_final
2023-02-19 09:58:02	ga_s2am_ard_3-2-1_55GBR_2023-02-19_nrt.stac-item
2023-02-19 09:58:02	ga_s2am_ard_3-2-1_55GBR_2023-02-19_final
2023-02-19 09:58:11	ga_s2am_ard_3-2-1_55GCQ_2023-02-19_nrt.stac-item
2023-02-19 09:58:11	ga_s2am_ard_3-2-1_55GCQ_2023-02-19_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

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