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
2015-12-24 10:17:49	ga_s2am_ard_3-2-1_54HTE_2015-12-24_final.stac-item
2015-12-24 10:17:49	ga_s2am_ard_3-2-1_54HTF_2015-12-24_final.stac-item
2015-12-24 10:17:49	ga_s2am_ard_3-2-1_53HQA_2015-12-24_final.stac-item
2015-12-24 10:17:49	ga_s2am_ard_3-2-1_53HQV_2015-12-24_final.stac-item
2015-12-30 10:32:41	ga_s2am_ard_3-2-1_53KQA_2015-12-30_final.stac-item
2015-12-30 10:32:41	ga_s2am_ard_3-2-1_53KQU_2015-12-30_final.stac-item
2015-12-30 10:32:41	ga_s2am_ard_3-2-1_53KQV_2015-12-30_final.stac-item
2016-01-12 10:42:33	ga_s2am_ard_3-2-1_53KQA_2016-01-12_final.stac-item
2016-01-12 10:42:33	ga_s2am_ard_3-2-1_53KQU_2016-01-12_final.stac-item
2016-01-12 10:42:33	ga_s2am_ard_3-2-1_53KQV_2016-01-12_final.stac-item
2016-01-23 10:17:44	ga_s2am_ard_3-2-1_54HTE_2016-01-23_final.stac-item
2016-01-23 10:17:44	ga_s2am_ard_3-2-1_54HTF_2016-01-23_final.stac-item
2016-01-23 10:17:44	ga_s2am_ard_3-2-1_53HQV_2016-01-23_final.stac-item
2016-01-26 10:26:51	ga_s2am_ard_3-2-1_54HTF_2016-01-26_final.stac-item
2016-01-26 10:26:51	ga_s2am_ard_3-2-1_54HTG_2016-01-26_final.stac-item
2016-01-26 10:26:51	ga_s2am_ard_3-2-1_53HQA_2016-01-26_final.stac-item
2016-01-26 10:26:51	ga_s2am_ard_3-2-1_53HQB_2016-01-26_final.stac-item
2017-07-26 10:16:32	ga_s2am_ard_3-2-1_54HTF_2017-07-26_final.stac-item
2017-07-26 10:16:32	ga_s2am_ard_3-2-1_53HQA_2017-07-26_final.stac-item
2017-08-24 10:42:04	ga_s2am_ard_3-2-1_53KQA_2017-08-24_final.stac-item
2017-08-24 10:42:04	ga_s2am_ard_3-2-1_53KQU_2017-08-24_final.stac-item
2017-08-24 10:42:04	ga_s2am_ard_3-2-1_53KQV_2017-08-24_final.stac-item
2019-02-26 10:16:59	ga_s2am_ard_3-2-1_54HTF_2019-02-26_final.stac-item
2019-02-26 10:17:00	ga_s2am_ard_3-2-1_53HQA_2019-02-26_final.stac-item
2019-03-01 10:24:46	ga_s2am_ard_3-2-1_53JQK_2019-03-01_final.stac-item
2019-03-01 10:25:00	ga_s2am_ard_3-2-1_53JQJ_2019-03-01_final.stac-item
2019-03-01 10:25:15	ga_s2am_ard_3-2-1_53JQH_2019-03-01_final.stac-item
2019-03-01 10:25:30	ga_s2am_ard_3-2-1_53JQG_2019-03-01_final.stac-item
2019-03-01 10:25:44	ga_s2am_ard_3-2-1_53JQF_2019-03-01_final.stac-item
2019-03-01 10:25:56	ga_s2am_ard_3-2-1_54HTK_2019-03-01_final.stac-item
2019-03-01 10:25:58	ga_s2am_ard_3-2-1_53HQE_2019-03-01_final.stac-item
2019-03-01 10:26:11	ga_s2am_ard_3-2-1_54HTJ_2019-03-01_final.stac-item
2019-03-01 10:26:13	ga_s2am_ard_3-2-1_53HQD_2019-03-01_final.stac-item
2019-03-01 10:26:25	ga_s2am_ard_3-2-1_54HTH_2019-03-01_final.stac-item
2019-03-01 10:26:27	ga_s2am_ard_3-2-1_53HQC_2019-03-01_final.stac-item
2019-03-01 10:26:40	ga_s2am_ard_3-2-1_54HTG_2019-03-01_final.stac-item
2019-03-01 10:26:42	ga_s2am_ard_3-2-1_53HQB_2019-03-01_final.stac-item
2019-03-01 10:26:54	ga_s2am_ard_3-2-1_54HTF_2019-03-01_final.stac-item
2019-03-01 10:26:56	ga_s2am_ard_3-2-1_53HQA_2019-03-01_final.stac-item
2019-03-11 10:24:46	ga_s2am_ard_3-2-1_53JQK_2019-03-11_final.stac-item
2019-03-11 10:25:00	ga_s2am_ard_3-2-1_53JQJ_2019-03-11_final.stac-item
2019-03-11 10:25:15	ga_s2am_ard_3-2-1_53JQH_2019-03-11_final.stac-item
2019-03-11 10:25:30	ga_s2am_ard_3-2-1_53JQG_2019-03-11_final.stac-item
2019-03-11 10:25:44	ga_s2am_ard_3-2-1_53JQF_2019-03-11_final.stac-item
2019-03-11 10:25:56	ga_s2am_ard_3-2-1_54HTK_2019-03-11_final.stac-item
2019-03-11 10:25:59	ga_s2am_ard_3-2-1_53HQE_2019-03-11_final.stac-item
2019-03-11 10:26:11	ga_s2am_ard_3-2-1_54HTJ_2019-03-11_final.stac-item
2019-03-11 10:26:13	ga_s2am_ard_3-2-1_53HQD_2019-03-11_final.stac-item
2019-03-11 10:26:25	ga_s2am_ard_3-2-1_54HTH_2019-03-11_final.stac-item
2019-03-11 10:26:27	ga_s2am_ard_3-2-1_53HQC_2019-03-11_final.stac-item
2019-03-11 10:26:40	ga_s2am_ard_3-2-1_54HTG_2019-03-11_final.stac-item
2019-03-11 10:26:42	ga_s2am_ard_3-2-1_53HQB_2019-03-11_final.stac-item
2019-03-11 10:26:54	ga_s2am_ard_3-2-1_54HTF_2019-03-11_final.stac-item
2019-03-11 10:26:56	ga_s2am_ard_3-2-1_53HQA_2019-03-11_final.stac-item
2019-03-14 10:32:07	ga_s2am_ard_3-2-1_53KQA_2019-03-14_final.stac-item
2019-03-14 10:32:19	ga_s2am_ard_3-2-1_53KQV_2019-03-14_final.stac-item
2019-03-14 10:32:32	ga_s2am_ard_3-2-1_53KQU_2019-03-14_final.stac-item
2019-03-14 10:32:43	ga_s2am_ard_3-2-1_53KQT_2019-03-14_final.stac-item
2019-03-14 10:32:50	ga_s2am_ard_3-2-1_53KQT_2019-03-14_final.stac-item
2019-06-02 10:32:13	ga_s2am_ard_3-2-1_53KQA_2019-06-02_final.stac-item
2019-06-02 10:32:25	ga_s2am_ard_3-2-1_53KQV_2019-06-02_final.stac-item
2019-06-02 10:32:39	ga_s2am_ard_3-2-1_53KQU_2019-06-02_final.stac-item
2019-06-02 10:32:54	ga_s2am_ard_3-2-1_53KQT_2019-06-02_final.stac-item
2019-06-05 10:41:22	ga_s2am_ard_3-2-1_53LQD_2019-06-05_final.stac-item
2019-06-05 10:41:36	ga_s2am_ard_3-2-1_53LQC_2019-06-05_final
2019-06-05 10:41:47	ga_s2am_ard_3-2-1_53KRB_2019-06-05_final
2019-06-05 10:41:51	ga_s2am_ard_3-2-1_53KQB_2019-06-05_final
2019-06-05 10:42:05	ga_s2am_ard_3-2-1_53KQA_2019-06-05_final.stac-item
2019-06-05 10:42:20	ga_s2am_ard_3-2-1_53KQV_2019-06-05_final.stac-item
2019-06-05 10:42:34	ga_s2am_ard_3-2-1_53KQU_2019-06-05_final.stac-item
2019-06-06 10:17:05	ga_s2am_ard_3-2-1_54HTF_2019-06-06_final.stac-item
2019-06-06 10:17:07	ga_s2am_ard_3-2-1_53HQA_2019-06-06_final.stac-item
2019-06-19 10:25:09	ga_s2am_ard_3-2-1_53JQJ_2019-06-19_final.stac-item
2019-06-19 10:25:24	ga_s2am_ard_3-2-1_53JQH_2019-06-19_final.stac-item
2019-06-19 10:25:38	ga_s2am_ard_3-2-1_53JQG_2019-06-19_final.stac-item
2019-06-19 10:25:53	ga_s2am_ard_3-2-1_53JQF_2019-06-19_final.stac-item
2019-06-19 10:26:05	ga_s2am_ard_3-2-1_54HTK_2019-06-19_final.stac-item
2019-06-19 10:26:07	ga_s2am_ard_3-2-1_53HQE_2019-06-19_final.stac-item
2019-06-19 10:26:19	ga_s2am_ard_3-2-1_54HTJ_2019-06-19_final.stac-item
2019-06-19 10:26:21	ga_s2am_ard_3-2-1_53HQD_2019-06-19_final.stac-item
2019-06-19 10:26:34	ga_s2am_ard_3-2-1_54HTH_2019-06-19_final.stac-item
2019-06-19 10:26:36	ga_s2am_ard_3-2-1_53HQC_2019-06-19_final.stac-item
2019-06-19 10:26:48	ga_s2am_ard_3-2-1_54HTG_2019-06-19_final.stac-item
2019-06-19 10:26:50	ga_s2am_ard_3-2-1_53HQB_2019-06-19_final.stac-item
2019-06-19 10:27:03	ga_s2am_ard_3-2-1_54HTF_2019-06-19_final.stac-item
2019-06-19 10:27:05	ga_s2am_ard_3-2-1_53HQA_2019-06-19_final.stac-item
2019-10-07 10:25:22	ga_s2am_ard_3-2-1_53JQH_2019-10-07_final.stac-item
2019-10-07 10:25:37	ga_s2am_ard_3-2-1_53JQG_2019-10-07_final.stac-item
2019-10-07 10:25:51	ga_s2am_ard_3-2-1_53JQF_2019-10-07_final.stac-item
2019-10-07 10:26:03	ga_s2am_ard_3-2-1_54HTK_2019-10-07_final.stac-item
2019-10-07 10:26:06	ga_s2am_ard_3-2-1_53HQE_2019-10-07_final.stac-item
2019-10-07 10:26:18	ga_s2am_ard_3-2-1_54HTJ_2019-10-07_final.stac-item
2019-10-07 10:26:20	ga_s2am_ard_3-2-1_53HQD_2019-10-07_final.stac-item
2019-10-07 10:26:33	ga_s2am_ard_3-2-1_54HTH_2019-10-07_final.stac-item
2019-10-07 10:26:35	ga_s2am_ard_3-2-1_53HQC_2019-10-07_final.stac-item
2019-10-07 10:26:47	ga_s2am_ard_3-2-1_54HTG_2019-10-07_final.stac-item
2019-10-07 10:26:49	ga_s2am_ard_3-2-1_53HQB_2019-10-07_final.stac-item
2019-10-07 10:27:01	ga_s2am_ard_3-2-1_54HTF_2019-10-07_final.stac-item
2019-10-07 10:27:03	ga_s2am_ard_3-2-1_53HQA_2019-10-07_final.stac-item
2019-10-27 10:27:02	ga_s2am_ard_3-2-1_54HTF_2019-10-27_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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