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
2016-07-07 12:13:46	ga_s2am_ard_3-2-1_49KHS_2016-07-07_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
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-08-03_final
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHS_2016-12-14_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
2021-01-02 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-01-02_final
2021-01-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-09_final
2021-01-12 12:13:41	ga_s2am_ard_3-2-1_49KHS_2021-01-12_final
2021-01-19 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-19_final
2021-01-22 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-01-22_final
2021-01-29 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-29_final
2021-02-01 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-02-01_final
2021-02-08 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-02-08_final
2021-02-11 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-02-11_final
2021-02-18 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-18_final
2021-02-21 12:13:39	ga_s2am_ard_3-2-1_49KHS_2021-02-21_final
2021-02-28 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-28_final
2021-03-03 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-03-03_final
2021-03-10 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-03-10_final
2021-03-13 12:13:39	ga_s2am_ard_3-2-1_49KHS_2021-03-13_final
2021-03-20 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-03-20_final
2021-03-23 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-03-23_final
2021-03-30 12:03:42	ga_s2am_ard_3-2-1_49KHS_2021-03-30_final
2021-04-02 12:13:37	ga_s2am_ard_3-2-1_49KHS_2021-04-02_final
2021-04-09 12:03:40	ga_s2am_ard_3-2-1_49KHS_2021-04-09_final
2021-04-12 12:13:34	ga_s2am_ard_3-2-1_49KHS_2021-04-12_final
2021-04-19 12:03:39	ga_s2am_ard_3-2-1_49KHS_2021-04-19_final
2021-04-22 12:13:35	ga_s2am_ard_3-2-1_49KHS_2021-04-22_final
2021-04-22 12:13:35	ga_s2am_ard_3-2-1_49KHS_2021-04-22_final
2021-04-29 12:03:42	ga_s2am_ard_3-2-1_49KHS_2021-04-29_final
2021-05-02 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-05-02_final
2021-05-09 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-05-09_final
2021-05-12 12:13:39	ga_s2am_ard_3-2-1_49KHS_2021-05-12_final
2021-05-19 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-05-19_final
2021-05-22 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-05-22_final
2021-05-29 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-05-29_final
2021-06-01 12:13:41	ga_s2am_ard_3-2-1_49KHS_2021-06-01_final
2021-06-08 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-06-08_final
2021-06-11 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-06-11_final
2021-06-18 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-06-18_final
2021-06-21 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-06-21_final
2021-06-28 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-06-28_final
2021-07-01 12:13:42	ga_s2am_ard_3-2-1_49KHS_2021-07-01_final
2021-07-08 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-07-08_final
2021-07-11 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-11_final
2021-07-18 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-18_final
2021-07-21 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-21_final
2021-07-28 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-28_final
2021-07-31 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-31_final
2021-08-07 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-08-07_final
2021-08-10 12:13:42	ga_s2am_ard_3-2-1_49KHS_2021-08-10_final
2021-08-17 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-08-17_final
2021-08-20 12:13:42	ga_s2am_ard_3-2-1_49KHS_2021-08-20_final
2021-08-27 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-08-27_final
2021-08-30 12:13:41	ga_s2am_ard_3-2-1_49KHS_2021-08-30_final
2021-09-06 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-09-06_final
2021-09-09 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-09-09_final
2021-09-16 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-09-16_final
2021-09-19 12:13:42	ga_s2am_ard_3-2-1_49KHS_2021-09-19_final
2021-09-26 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-09-26_final
2021-09-29 12:13:44	ga_s2am_ard_3-2-1_49KHS_2021-09-29_final
2021-10-06 12:03:49	ga_s2am_ard_3-2-1_49KHS_2021-10-06_final
2021-10-09 12:13:45	ga_s2am_ard_3-2-1_49KHS_2021-10-09_final
2021-10-16 12:03:50	ga_s2am_ard_3-2-1_49KHS_2021-10-16_final
2021-10-19 12:13:45	ga_s2am_ard_3-2-1_49KHS_2021-10-19_final
2021-10-26 12:03:49	ga_s2am_ard_3-2-1_49KHS_2021-10-26_final
2021-10-29 12:13:45	ga_s2am_ard_3-2-1_49KHS_2021-10-29_final
2021-11-05 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-11-05_final
2021-11-08 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-11-08_final
2021-11-15 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-11-15_final
2021-11-18 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-11-18_final
2021-11-25 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-11-25_final
2021-11-28 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-11-28_final
2021-12-05 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-12-05_final
2021-12-08 12:13:39	ga_s2am_ard_3-2-1_49KHS_2021-12-08_final
2021-12-15 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-12-15_final
2021-12-18 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-12-18_final
2021-12-25 12:03:46	ga_s2am_ard_3-2-1_49KHS_2021-12-25_final
2021-12-28 12:13:41	ga_s2am_ard_3-2-1_49KHS_2021-12-28_final
2023-01-02 12:13:39	ga_s2am_ard_3-2-1_49KHS_2023-01-02_final
2023-01-09 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-01-09_final
2023-01-12 12:13:38	ga_s2am_ard_3-2-1_49KHS_2023-01-12_final
2023-01-19 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-01-19_final
2023-01-22 12:13:35	ga_s2am_ard_3-2-1_49KHS_2023-01-22_final
2023-01-29 12:03:42	ga_s2am_ard_3-2-1_49KHS_2023-01-29_final
2023-02-01 12:13:38	ga_s2am_ard_3-2-1_49KHS_2023-02-01_final
2023-02-08 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-02-08_final
2023-02-11 12:13:38	ga_s2am_ard_3-2-1_49KHS_2023-02-11_final
2023-02-18 12:03:41	ga_s2am_ard_3-2-1_49KHS_2023-02-18_final
2023-02-21 12:13:37	ga_s2am_ard_3-2-1_49KHS_2023-02-21_final
2023-02-28 12:03:42	ga_s2am_ard_3-2-1_49KHS_2023-02-28_final
2023-03-03 12:13:42	ga_s2am_ard_3-2-1_49KHS_2023-03-03_final
2023-08-07 12:03:41	ga_s2am_ard_3-2-1_49KHS_2023-08-07_final
2023-08-07 12:03:49	ga_s2am_ard_3-2-1_49KHS_2023-08-07_final
2023-08-17 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-08-17_final
2023-08-20 12:13:46	ga_s2am_ard_3-2-1_49KHS_2023-08-20_final
2023-08-27 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-08-27_final
2023-08-30 12:13:45	ga_s2am_ard_3-2-1_49KHS_2023-08-30_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

All years