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
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_51HTB_2015-12-08_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51HTB_2015-12-25_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_51HTB_2016-01-07_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51HTB_2016-02-06_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_51HTB_2016-04-06_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51HTB_2016-04-23_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51HTB_2016-05-03_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51HTB_2016-05-16_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51HTB_2016-06-05_final.stac-item
2016-06-12 11:22:42	ga_s2am_ard_3-2-1_51HTB_2016-06-12_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_51HTB_2016-06-25_final.stac-item
2016-07-02 11:22:40	ga_s2am_ard_3-2-1_51HTB_2016-07-02_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51HTB_2016-07-15_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_51HTB_2016-07-22_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51HTB_2016-08-04_final.stac-item
2016-08-11 11:22:31	ga_s2am_ard_3-2-1_51HTB_2016-08-11_final.stac-item
2016-08-31 11:22:38	ga_s2am_ard_3-2-1_51HTB_2016-08-31_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51HTB_2016-09-13_final.stac-item
2016-09-20 11:22:33	ga_s2am_ard_3-2-1_51HTB_2016-09-20_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51HTB_2016-10-03_final.stac-item
2016-10-10 11:22:34	ga_s2am_ard_3-2-1_51HTB_2016-10-10_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_51HTB_2016-10-23_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51HTB_2016-10-30_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_51HTB_2016-11-02_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HTB_2016-11-12_final.stac-item
2016-11-19 11:19:19	ga_s2am_ard_3-2-1_51HTB_2016-11-19_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51HTB_2016-11-22_final.stac-item
2016-11-29 11:23:19	ga_s2am_ard_3-2-1_51HTB_2016-11-29_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51HTB_2016-12-09_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51HTB_2016-12-12_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51HTB_2016-12-22_final.stac-item
2016-12-29 11:21:06	ga_s2am_ard_3-2-1_51HTB_2016-12-29_final.stac-item
2022-12-21 11:37:27	ga_s2am_ard_3-2-1_51HTA_2022-12-21_nrt.stac-item
2022-12-31 11:37:27	ga_s2am_ard_3-2-1_51HTA_2022-12-31_nrt.stac-item
2023-01-10 11:37:27	ga_s2am_ard_3-2-1_51HTA_2023-01-10_nrt.stac-item
2023-01-20 11:37:23	ga_s2am_ard_3-2-1_51HTA_2023-01-20_nrt.stac-item
2023-01-30 11:37:27	ga_s2am_ard_3-2-1_51HTA_2023-01-30_nrt.stac-item
2023-02-09 11:37:27	ga_s2am_ard_3-2-1_51HTA_2023-02-09_nrt.stac-item
2023-02-16 11:27:11	ga_s2am_ard_3-2-1_51HTB_2023-02-16_nrt.stac-item
2023-02-19 11:37:12	ga_s2am_ard_3-2-1_51HTB_2023-02-19_nrt.stac-item
2023-02-19 11:37:26	ga_s2am_ard_3-2-1_51HTA_2023-02-19_nrt.stac-item
2023-03-01 11:37:24	ga_s2am_ard_3-2-1_51HTA_2023-03-01_nrt
2023-03-01 11:37:29	ga_s2am_ard_3-2-1_51HTA_2023-03-01_nrt
2023-03-11 11:37:22	ga_s2am_ard_3-2-1_51HTA_2023-03-11_nrt
2023-03-11 11:37:27	ga_s2am_ard_3-2-1_51HTA_2023-03-11_nrt
2023-03-21 11:37:25	ga_s2am_ard_3-2-1_51HTA_2023-03-21_nrt
2023-03-21 11:37:30	ga_s2am_ard_3-2-1_51HTA_2023-03-21_nrt
2023-03-31 11:37:25	ga_s2am_ard_3-2-1_51HTA_2023-03-31_nrt
2023-03-31 11:37:30	ga_s2am_ard_3-2-1_51HTA_2023-03-31_nrt
2023-04-10 11:37:27	ga_s2am_ard_3-2-1_51HTA_2023-04-10_nrt
2023-04-10 11:37:32	ga_s2am_ard_3-2-1_51HTA_2023-04-10_nrt
2023-04-20 11:37:21	ga_s2am_ard_3-2-1_51HTA_2023-04-20_nrt
2023-04-20 11:37:26	ga_s2am_ard_3-2-1_51HTA_2023-04-20_nrt
2023-04-30 11:37:28	ga_s2am_ard_3-2-1_51HTA_2023-04-30_nrt
2023-05-10 11:37:24	ga_s2am_ard_3-2-1_51HTA_2023-05-10_nrt
2023-05-10 11:37:28	ga_s2am_ard_3-2-1_51HTA_2023-05-10_nrt
2023-05-20 11:37:30	ga_s2am_ard_3-2-1_51HTA_2023-05-20_nrt
2023-05-30 11:37:28	ga_s2am_ard_3-2-1_51HTA_2023-05-30_nrt
2023-05-30 11:37:32	ga_s2am_ard_3-2-1_51HTA_2023-05-30_nrt
2023-06-09 11:37:31	ga_s2am_ard_3-2-1_51HTA_2023-06-09_nrt
2023-06-19 11:37:32	ga_s2am_ard_3-2-1_51HTA_2023-06-19_nrt
2023-06-29 11:37:32	ga_s2am_ard_3-2-1_51HTA_2023-06-29_nrt
2023-07-09 11:37:33	ga_s2am_ard_3-2-1_51HTA_2023-07-09_nrt
2023-07-19 11:37:32	ga_s2am_ard_3-2-1_51HTA_2023-07-19_nrt
2023-07-29 11:37:29	ga_s2am_ard_3-2-1_51HTA_2023-07-29_nrt
2023-07-29 11:37:33	ga_s2am_ard_3-2-1_51HTA_2023-07-29_nrt
2023-08-05 11:27:18	ga_s2am_ard_3-2-1_51HTB_2023-08-05_final
2023-08-08 11:37:29	ga_s2am_ard_3-2-1_51HTA_2023-08-08_nrt
2023-08-18 11:37:34	ga_s2am_ard_3-2-1_51HTA_2023-08-18_nrt
2023-08-28 11:37:34	ga_s2am_ard_3-2-1_51HTA_2023-08-28_nrt
2023-09-07 11:37:33	ga_s2am_ard_3-2-1_51HTA_2023-09-07_nrt
2023-09-17 11:37:31	ga_s2am_ard_3-2-1_51HTA_2023-09-17_nrt
2023-09-27 11:37:30	ga_s2am_ard_3-2-1_51HTA_2023-09-27_nrt
2023-10-07 11:37:28	ga_s2am_ard_3-2-1_51HTA_2023-10-07_nrt
2023-10-17 11:37:27	ga_s2am_ard_3-2-1_51HTA_2023-10-17_nrt
2023-10-27 11:37:28	ga_s2am_ard_3-2-1_51HTA_2023-10-27_nrt
2023-11-06 11:37:29	ga_s2am_ard_3-2-1_51HTA_2023-11-06_nrt
2023-11-16 11:37:26	ga_s2am_ard_3-2-1_51HTA_2023-11-16_nrt
2023-11-26 11:37:22	ga_s2am_ard_3-2-1_51HTA_2023-11-26_nrt
2023-12-06 11:37:21	ga_s2am_ard_3-2-1_51HTA_2023-12-06_nrt
2023-12-16 11:37:24	ga_s2am_ard_3-2-1_51HTA_2023-12-16_nrt
2023-12-26 11:37:25	ga_s2am_ard_3-2-1_51HTA_2023-12-26_nrt
2024-01-05 11:37:24	ga_s2am_ard_3-2-1_51HTA_2024-01-05_nrt
2024-01-15 11:37:21	ga_s2am_ard_3-2-1_51HTA_2024-01-15_nrt
2024-01-25 11:37:22	ga_s2am_ard_3-2-1_51HTA_2024-01-25_interim.stac-item
2024-02-04 11:37:24	ga_s2am_ard_3-2-1_51HTA_2024-02-04_nrt
2024-02-14 11:37:25	ga_s2am_ard_3-2-1_51HTA_2024-02-14_nrt
2024-02-24 11:37:22	ga_s2am_ard_3-2-1_51HTA_2024-02-24_nrt
2024-02-24 11:37:26	ga_s2am_ard_3-2-1_51HTA_2024-02-24_nrt
2024-03-05 11:37:23	ga_s2am_ard_3-2-1_51HTA_2024-03-05_nrt
2024-03-05 11:37:28	ga_s2am_ard_3-2-1_51HTA_2024-03-05_nrt
2024-03-15 11:37:24	ga_s2am_ard_3-2-1_51HTA_2024-03-15_nrt
2024-03-15 11:37:28	ga_s2am_ard_3-2-1_51HTA_2024-03-15_nrt
2024-03-25 11:37:29	ga_s2am_ard_3-2-1_51HTA_2024-03-25_nrt
2024-04-04 11:37:25	ga_s2am_ard_3-2-1_51HTA_2024-04-04_nrt
2024-04-14 11:37:30	ga_s2am_ard_3-2-1_51HTA_2024-04-14_nrt
2024-04-24 11:37:30	ga_s2am_ard_3-2-1_51HTA_2024-04-24_nrt
2024-05-04 11:37:31	ga_s2am_ard_3-2-1_51HTA_2024-05-04_nrt
2024-05-14 11:37:31	ga_s2am_ard_3-2-1_51HTA_2024-05-14_nrt
2024-05-24 11:37:27	ga_s2am_ard_3-2-1_51HTA_2024-05-24_nrt

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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