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
2015-09-11 12:13:46	ga_s2am_ard_3-2-1_49KHS_2015-09-11_final
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_49KHS_2015-10-21_final
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HMG_2015-10-22_final
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HMG_2015-11-14_final
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HMG_2015-11-21_final
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HNG_2015-11-21_final
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KHS_2015-11-30_final
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50HMG_2015-12-04_final
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HNG_2015-12-08_final
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HMG_2016-01-03_final
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HNG_2016-01-07_final
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KHS_2016-01-16_final
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HMG_2016-01-20_final
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49KHS_2016-02-08_final
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49KHS_2016-02-15_final
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HMG_2016-02-19_final
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50HMG_2016-03-03_final
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KHS_2016-03-09_final
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HMG_2016-03-20_final
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HMG_2016-04-02_final
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KHS_2016-04-15_final
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HMG_2016-04-29_final
2016-04-29 11:47:17	ga_s2am_ard_3-2-1_50HMG_2016-04-29_final
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMG_2016-05-09_final
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KHS_2016-05-15_final
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHS_2016-05-18_final
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50HMG_2016-05-22_final
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HMG_2016-05-29_final
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HNG_2016-05-29_final
2016-06-04 12:02:54	ga_s2am_ard_3-2-1_49KHS_2016-06-04_final
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HNG_2016-06-05_final
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KHS_2016-06-07_final
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HMG_2016-06-11_final
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HMG_2016-06-18_final
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HNG_2016-06-18_final
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_50HNG_2016-06-25_final
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHS_2016-06-27_final
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HMG_2016-07-01_final
2016-07-07 12:13:46	ga_s2am_ard_3-2-1_49KHS_2016-07-07_final
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HNG_2016-07-08_final
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-07-14_final
2016-07-17 12:13:25	ga_s2am_ard_3-2-1_49KHS_2016-07-17_final
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HMG_2016-07-21_final
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HMG_2016-07-28_final
2016-08-06 12:13:25	ga_s2am_ard_3-2-1_49KHS_2016-08-06_final
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50HMG_2016-08-10_final
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HMG_2016-08-17_final
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HNG_2016-08-17_final
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49KHS_2016-08-23_final
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_50HNG_2016-08-24_final
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHS_2016-08-26_final
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50HMG_2016-08-30_final
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HMG_2016-09-06_final
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50HMG_2016-09-19_final
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HMG_2016-09-26_final
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-02_final
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49KHS_2016-10-05_final
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HMG_2016-10-09_final
2016-10-15 12:13:39	ga_s2am_ard_3-2-1_49KHS_2016-10-15_final
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HMG_2016-10-16_final
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-22_final
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49KHS_2016-10-25_final
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HMG_2016-10-26_final
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HMG_2016-10-29_final
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KHS_2016-11-01_final
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49KHS_2016-11-04_final
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMG_2016-11-05_final
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-11_final
2016-11-14 12:13:20	ga_s2am_ard_3-2-1_49KHS_2016-11-14_final
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KHS_2016-11-14_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HMG_2016-11-15_final
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HMG_2016-11-18_final
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-21_final
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HNG_2016-11-22_final
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KHS_2016-11-24_final
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HMG_2016-11-28_final
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KHS_2016-12-04_final
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HMG_2016-12-05_final
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HNG_2016-12-05_final
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HMG_2016-12-08_final
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-12-11_final
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_50HNG_2016-12-12_final
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHS_2016-12-14_final
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HMG_2016-12-15_final
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HNG_2016-12-15_final
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHS_2016-12-21_final
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KHS_2016-12-24_final
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HMG_2016-12-25_final
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HMG_2016-12-28_final
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHS_2016-12-31_final
2023-08-17 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-08-17_final
2023-08-17 12:04:05	ga_s2am_ard_3-2-1_49KHR_2023-08-17_final
2023-08-17 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-08-17_final
2023-08-17 12:05:21	ga_s2am_ard_3-2-1_49JGL_2023-08-17_final
2023-08-17 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2023-08-17_final
2023-08-17 12:06:04	ga_s2am_ard_3-2-1_49JGH_2023-08-17_final
2023-08-18 11:36:58	ga_s2am_ard_3-2-1_50HPJ_2023-08-18_final
2023-08-27 12:03:36	ga_s2am_ard_3-2-1_49KHT_2023-08-27_nrt
2023-08-27 12:05:38	ga_s2am_ard_3-2-1_49JFK_2023-08-27_nrt
2023-08-27 12:06:18	ga_s2am_ard_3-2-1_49JGG_2023-08-27_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

All years