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
2018-12-15 11:43:42	ga_s2am_ard_3-2-1_50KQA_2018-12-15_final.stac-item
2018-12-15 11:43:57	ga_s2am_ard_3-2-1_50KQV_2018-12-15_final.stac-item
2018-12-15 11:44:11	ga_s2am_ard_3-2-1_50KQU_2018-12-15_final.stac-item
2018-12-15 11:44:26	ga_s2am_ard_3-2-1_50JQT_2018-12-15_final.stac-item
2018-12-15 11:44:33	ga_s2am_ard_3-2-1_50JQT_2018-12-15_final.stac-item
2018-12-15 11:44:33	ga_s2am_ard_3-2-1_50JQS_2018-12-15_final.stac-item
2018-12-15 11:44:40	ga_s2am_ard_3-2-1_50JQS_2018-12-15_final.stac-item
2018-12-15 11:44:55	ga_s2am_ard_3-2-1_50JQR_2018-12-15_final.stac-item
2018-12-15 11:45:09	ga_s2am_ard_3-2-1_50JQQ_2018-12-15_final.stac-item
2018-12-25 11:43:43	ga_s2am_ard_3-2-1_50KQA_2018-12-25_final.stac-item
2018-12-25 11:43:58	ga_s2am_ard_3-2-1_50KQV_2018-12-25_final.stac-item
2018-12-25 11:44:12	ga_s2am_ard_3-2-1_50KQU_2018-12-25_final.stac-item
2018-12-25 11:44:27	ga_s2am_ard_3-2-1_50JQT_2018-12-25_final.stac-item
2018-12-28 11:53:10	ga_s2am_ard_3-2-1_50KQC_2018-12-28_final.stac-item
2018-12-28 11:53:25	ga_s2am_ard_3-2-1_50KQB_2018-12-28_final.stac-item
2018-12-28 11:53:40	ga_s2am_ard_3-2-1_50KQA_2018-12-28_final.stac-item
2018-12-28 11:53:54	ga_s2am_ard_3-2-1_50KQV_2018-12-28_final.stac-item
2018-12-28 11:54:06	ga_s2am_ard_3-2-1_50KQU_2018-12-28_final.stac-item
2019-01-01 11:36:13	ga_s2am_ard_3-2-1_50JQL_2019-01-01_final.stac-item
2019-01-01 11:36:20	ga_s2am_ard_3-2-1_50JPL_2019-01-01_final.stac-item
2019-01-01 11:36:28	ga_s2am_ard_3-2-1_50HQK_2019-01-01_final.stac-item
2019-01-01 11:36:32	ga_s2am_ard_3-2-1_50HPK_2019-01-01_final.stac-item
2019-01-04 11:43:45	ga_s2am_ard_3-2-1_50KQA_2019-01-04_final.stac-item
2019-01-04 11:44:00	ga_s2am_ard_3-2-1_50KQV_2019-01-04_final.stac-item
2019-01-04 11:44:14	ga_s2am_ard_3-2-1_50KQU_2019-01-04_final.stac-item
2019-04-04 11:44:06	ga_s2am_ard_3-2-1_50KQV_2019-04-04_final.stac-item
2019-04-04 11:44:21	ga_s2am_ard_3-2-1_50KQU_2019-04-04_final.stac-item
2019-04-04 11:44:35	ga_s2am_ard_3-2-1_50JQT_2019-04-04_final.stac-item
2019-04-04 11:44:50	ga_s2am_ard_3-2-1_50JQS_2019-04-04_final.stac-item
2019-04-04 11:45:04	ga_s2am_ard_3-2-1_50JQR_2019-04-04_final.stac-item
2019-04-04 11:45:18	ga_s2am_ard_3-2-1_50JQQ_2019-04-04_final.stac-item
2019-04-04 11:45:33	ga_s2am_ard_3-2-1_50JQP_2019-04-04_final.stac-item
2019-04-04 11:45:37	ga_s2am_ard_3-2-1_50JPP_2019-04-04_final.stac-item
2019-04-04 11:45:47	ga_s2am_ard_3-2-1_50JQN_2019-04-04_final.stac-item
2019-04-04 11:45:51	ga_s2am_ard_3-2-1_50JPN_2019-04-04_final.stac-item
2019-04-04 11:46:01	ga_s2am_ard_3-2-1_50JQM_2019-04-04_final.stac-item
2019-04-04 11:46:06	ga_s2am_ard_3-2-1_50JPM_2019-04-04_final.stac-item
2019-04-04 11:46:16	ga_s2am_ard_3-2-1_50JQL_2019-04-04_final.stac-item
2019-04-04 11:46:20	ga_s2am_ard_3-2-1_50JPL_2019-04-04_final.stac-item
2019-04-04 11:46:31	ga_s2am_ard_3-2-1_50HQK_2019-04-04_final.stac-item
2019-04-04 11:46:34	ga_s2am_ard_3-2-1_50HPK_2019-04-04_final.stac-item
2019-04-04 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2019-04-04_final.stac-item
2019-04-04 11:46:49	ga_s2am_ard_3-2-1_50HPJ_2019-04-04_final.stac-item
2019-04-04 11:46:54	ga_s2am_ard_3-2-1_50HQH_2019-04-04_final.stac-item
2019-04-21 11:37:06	ga_s2am_ard_3-2-1_50HQH_2019-04-21_final.stac-item
2019-04-21 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-04-21_final.stac-item
2019-05-01 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2019-05-01_final.stac-item
2019-05-01 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2019-05-01_final.stac-item
2019-05-01 11:37:06	ga_s2am_ard_3-2-1_50HQH_2019-05-01_final.stac-item
2019-05-01 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-05-01_final.stac-item
2019-06-23 11:45:54	ga_s2am_ard_3-2-1_50JPN_2019-06-23_final.stac-item
2019-06-23 11:46:02	ga_s2am_ard_3-2-1_50JQM_2019-06-23_final.stac-item
2019-06-23 11:46:23	ga_s2am_ard_3-2-1_50JPL_2019-06-23_final.stac-item
2019-06-23 11:46:38	ga_s2am_ard_3-2-1_50HPK_2019-06-23_final.stac-item
2019-06-23 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2019-06-23_final.stac-item
2019-06-23 11:46:58	ga_s2am_ard_3-2-1_50HQH_2019-06-23_final.stac-item
2019-06-23 11:47:06	ga_s2am_ard_3-2-1_50HPH_2019-06-23_final.stac-item
2020-02-08 11:43:43	ga_s2am_ard_3-2-1_50KQA_2020-02-08_final.stac-item
2020-02-08 11:45:10	ga_s2am_ard_3-2-1_50JQQ_2020-02-08_final.stac-item
2020-02-08 11:45:24	ga_s2am_ard_3-2-1_50JQP_2020-02-08_final.stac-item
2020-02-08 11:45:28	ga_s2am_ard_3-2-1_50JPP_2020-02-08_final.stac-item
2020-02-08 11:45:38	ga_s2am_ard_3-2-1_50JQN_2020-02-08_final.stac-item
2020-02-08 11:45:42	ga_s2am_ard_3-2-1_50JPN_2020-02-08_final.stac-item
2020-02-08 11:45:53	ga_s2am_ard_3-2-1_50JQM_2020-02-08_final.stac-item
2020-02-08 11:45:57	ga_s2am_ard_3-2-1_50JPM_2020-02-08_final.stac-item
2020-02-08 11:46:07	ga_s2am_ard_3-2-1_50JQL_2020-02-08_final.stac-item
2020-02-08 11:46:11	ga_s2am_ard_3-2-1_50JPL_2020-02-08_final.stac-item
2020-02-08 11:46:22	ga_s2am_ard_3-2-1_50HQK_2020-02-08_final.stac-item
2020-02-08 11:46:26	ga_s2am_ard_3-2-1_50HPK_2020-02-08_final.stac-item
2020-02-08 11:46:35	ga_s2am_ard_3-2-1_50HQJ_2020-02-08_final.stac-item
2020-02-08 11:46:40	ga_s2am_ard_3-2-1_50HPJ_2020-02-08_final.stac-item
2020-02-08 11:46:46	ga_s2am_ard_3-2-1_50HQH_2020-02-08_final.stac-item
2020-02-11 11:54:06	ga_s2am_ard_3-2-1_50KQU_2020-02-11_final.stac-item
2020-02-15 11:36:13	ga_s2am_ard_3-2-1_50JQL_2020-02-15_final.stac-item
2020-02-15 11:36:20	ga_s2am_ard_3-2-1_50JPL_2020-02-15_final.stac-item
2020-02-15 11:36:27	ga_s2am_ard_3-2-1_50HQK_2020-02-15_final.stac-item
2020-02-15 11:36:31	ga_s2am_ard_3-2-1_50HPK_2020-02-15_final.stac-item
2020-02-15 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2020-02-15_final.stac-item
2020-02-15 11:36:45	ga_s2am_ard_3-2-1_50HPJ_2020-02-15_final.stac-item
2020-02-15 11:36:56	ga_s2am_ard_3-2-1_50HQH_2020-02-15_final.stac-item
2020-02-15 11:37:00	ga_s2am_ard_3-2-1_50HPH_2020-02-15_final.stac-item
2020-02-21 11:53:41	ga_s2am_ard_3-2-1_50KQA_2020-02-21_final.stac-item
2020-02-21 11:53:55	ga_s2am_ard_3-2-1_50KQV_2020-02-21_final.stac-item
2020-02-21 11:54:03	ga_s2am_ard_3-2-1_50KQV_2020-02-21_final.stac-item
2020-02-21 11:54:04	ga_s2am_ard_3-2-1_50KQU_2020-02-21_final.stac-item
2020-02-21 11:54:08	ga_s2am_ard_3-2-1_50KQU_2020-02-21_final.stac-item
2022-05-28 11:45:38	ga_s2am_ard_3-2-1_50JQP_2022-05-28_final.stac-item
2022-05-28 11:45:45	ga_s2am_ard_3-2-1_50JQP_2022-05-28_final.stac-item
2022-05-28 11:45:47	ga_s2am_ard_3-2-1_50JPP_2022-05-28_final.stac-item
2022-05-28 11:45:54	ga_s2am_ard_3-2-1_50JQN_2022-05-28_final.stac-item
2022-05-28 11:45:58	ga_s2am_ard_3-2-1_50JPN_2022-05-28_final.stac-item
2022-05-28 11:46:08	ga_s2am_ard_3-2-1_50JQM_2022-05-28_final.stac-item
2022-05-28 11:46:12	ga_s2am_ard_3-2-1_50JPM_2022-05-28_final.stac-item
2022-05-28 11:46:23	ga_s2am_ard_3-2-1_50JQL_2022-05-28_final.stac-item
2022-05-28 11:46:27	ga_s2am_ard_3-2-1_50JPL_2022-05-28_final.stac-item
2022-05-28 11:46:37	ga_s2am_ard_3-2-1_50HQK_2022-05-28_final.stac-item
2022-05-28 11:46:41	ga_s2am_ard_3-2-1_50HPK_2022-05-28_final.stac-item
2022-05-28 11:46:50	ga_s2am_ard_3-2-1_50HQJ_2022-05-28_final.stac-item
2022-05-28 11:46:55	ga_s2am_ard_3-2-1_50HPJ_2022-05-28_final.stac-item
2022-05-28 11:47:01	ga_s2am_ard_3-2-1_50HQH_2022-05-28_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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