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
2022-08-21 14:23:53	ga_s2am_ard_3-2-1_43FDA_2022-08-21_interim
2022-08-21 14:23:55	ga_s2am_ard_3-2-1_43FCA_2022-08-21_interim
2022-08-28 14:13:58	ga_s2am_ard_3-2-1_43FCA_2022-08-28_interim
2022-08-31 14:23:53	ga_s2am_ard_3-2-1_43FDA_2022-08-31_interim
2022-08-31 14:23:55	ga_s2am_ard_3-2-1_43FCA_2022-08-31_interim
2022-09-07 14:13:55	ga_s2am_ard_3-2-1_43FDA_2022-09-07_interim
2022-09-07 14:13:57	ga_s2am_ard_3-2-1_43FCA_2022-09-07_interim
2022-09-10 14:23:51	ga_s2am_ard_3-2-1_43FDA_2022-09-10_interim
2022-09-10 14:23:53	ga_s2am_ard_3-2-1_43FCA_2022-09-10_interim
2022-09-17 14:13:53	ga_s2am_ard_3-2-1_43FDA_2022-09-17_interim
2022-09-17 14:13:55	ga_s2am_ard_3-2-1_43FCA_2022-09-17_interim
2022-09-20 14:23:48	ga_s2am_ard_3-2-1_43FDA_2022-09-20_interim
2022-09-20 14:23:50	ga_s2am_ard_3-2-1_43FCA_2022-09-20_interim
2022-09-27 14:13:51	ga_s2am_ard_3-2-1_43FDA_2022-09-27_interim
2022-09-27 14:13:53	ga_s2am_ard_3-2-1_43FCA_2022-09-27_interim
2022-09-30 14:23:48	ga_s2am_ard_3-2-1_43FDA_2022-09-30_interim
2022-09-30 14:23:50	ga_s2am_ard_3-2-1_43FCA_2022-09-30_interim
2022-10-07 14:13:50	ga_s2am_ard_3-2-1_43FDA_2022-10-07_interim
2022-10-07 14:13:52	ga_s2am_ard_3-2-1_43FCA_2022-10-07_interim
2022-10-10 14:23:47	ga_s2am_ard_3-2-1_43FDA_2022-10-10_interim
2022-10-10 14:23:49	ga_s2am_ard_3-2-1_43FCA_2022-10-10_interim
2022-10-17 14:13:47	ga_s2am_ard_3-2-1_43FDA_2022-10-17_interim
2022-10-17 14:13:49	ga_s2am_ard_3-2-1_43FCA_2022-10-17_interim
2022-10-20 14:23:42	ga_s2am_ard_3-2-1_43FDA_2022-10-20_interim
2022-10-20 14:23:44	ga_s2am_ard_3-2-1_43FCA_2022-10-20_interim
2022-10-27 14:13:47	ga_s2am_ard_3-2-1_43FDA_2022-10-27_interim
2022-10-27 14:13:49	ga_s2am_ard_3-2-1_43FCA_2022-10-27_interim
2022-10-30 14:23:44	ga_s2am_ard_3-2-1_43FDA_2022-10-30_interim
2022-10-30 14:23:46	ga_s2am_ard_3-2-1_43FCA_2022-10-30_interim
2022-11-06 14:13:48	ga_s2am_ard_3-2-1_43FDA_2022-11-06_interim
2022-11-06 14:13:50	ga_s2am_ard_3-2-1_43FCA_2022-11-06_interim
2022-11-09 14:23:44	ga_s2am_ard_3-2-1_43FDA_2022-11-09_interim
2022-11-09 14:23:46	ga_s2am_ard_3-2-1_43FCA_2022-11-09_interim
2022-11-16 14:13:46	ga_s2am_ard_3-2-1_43FDA_2022-11-16_interim
2022-11-16 14:13:48	ga_s2am_ard_3-2-1_43FCA_2022-11-16_interim
2022-11-19 14:23:42	ga_s2am_ard_3-2-1_43FDA_2022-11-19_interim
2022-11-19 14:23:44	ga_s2am_ard_3-2-1_43FCA_2022-11-19_interim
2022-11-26 14:13:43	ga_s2am_ard_3-2-1_43FDA_2022-11-26_interim
2022-11-26 14:13:45	ga_s2am_ard_3-2-1_43FCA_2022-11-26_interim
2022-11-29 14:23:41	ga_s2am_ard_3-2-1_43FDA_2022-11-29_interim
2022-11-29 14:23:43	ga_s2am_ard_3-2-1_43FCA_2022-11-29_interim
2022-12-06 14:13:44	ga_s2am_ard_3-2-1_43FDA_2022-12-06_interim
2022-12-06 14:13:46	ga_s2am_ard_3-2-1_43FCA_2022-12-06_interim
2022-12-09 14:23:41	ga_s2am_ard_3-2-1_43FDA_2022-12-09_interim
2022-12-09 14:23:43	ga_s2am_ard_3-2-1_43FCA_2022-12-09_interim
2022-12-16 14:13:43	ga_s2am_ard_3-2-1_43FDA_2022-12-16_interim
2022-12-16 14:13:45	ga_s2am_ard_3-2-1_43FCA_2022-12-16_interim
2022-12-19 14:23:39	ga_s2am_ard_3-2-1_43FDA_2022-12-19_interim
2022-12-19 14:23:41	ga_s2am_ard_3-2-1_43FCA_2022-12-19_interim
2022-12-26 14:13:42	ga_s2am_ard_3-2-1_43FDA_2022-12-26_interim
2022-12-26 14:13:44	ga_s2am_ard_3-2-1_43FCA_2022-12-26_interim
2022-12-29 14:23:39	ga_s2am_ard_3-2-1_43FDA_2022-12-29_interim
2022-12-29 14:23:41	ga_s2am_ard_3-2-1_43FCA_2022-12-29_interim
2023-01-05 14:13:43	ga_s2am_ard_3-2-1_43FDA_2023-01-05_interim
2023-01-05 14:13:45	ga_s2am_ard_3-2-1_43FCA_2023-01-05_interim
2023-01-08 14:23:39	ga_s2am_ard_3-2-1_43FDA_2023-01-08_interim
2023-01-08 14:23:41	ga_s2am_ard_3-2-1_43FCA_2023-01-08_interim
2023-01-15 14:13:40	ga_s2am_ard_3-2-1_43FDA_2023-01-15_interim
2023-01-15 14:13:42	ga_s2am_ard_3-2-1_43FCA_2023-01-15_interim
2023-01-18 14:23:36	ga_s2am_ard_3-2-1_43FDA_2023-01-18_interim
2023-01-18 14:23:38	ga_s2am_ard_3-2-1_43FCA_2023-01-18_interim
2023-01-25 14:13:41	ga_s2am_ard_3-2-1_43FDA_2023-01-25_interim
2023-01-25 14:13:43	ga_s2am_ard_3-2-1_43FCA_2023-01-25_interim
2023-01-28 14:23:38	ga_s2am_ard_3-2-1_43FDA_2023-01-28_interim
2023-01-28 14:23:40	ga_s2am_ard_3-2-1_43FCA_2023-01-28_interim
2023-08-26 14:23:49	ga_s2am_ard_3-2-1_42FYF_2023-08-26_final
2023-09-05 14:23:47	ga_s2am_ard_3-2-1_42FYF_2023-09-05_final
2023-09-12 14:13:51	ga_s2am_ard_3-2-1_42FYF_2023-09-12_final
2023-09-15 14:23:47	ga_s2am_ard_3-2-1_42FYF_2023-09-15_final
2023-09-22 14:13:48	ga_s2am_ard_3-2-1_42FYF_2023-09-22_final
2023-09-25 14:23:44	ga_s2am_ard_3-2-1_42FYF_2023-09-25_final
2023-10-02 14:13:46	ga_s2am_ard_3-2-1_42FYF_2023-10-02_final
2023-10-05 14:23:43	ga_s2am_ard_3-2-1_42FYF_2023-10-05_final
2023-10-12 14:13:44	ga_s2am_ard_3-2-1_42FYF_2023-10-12_final
2023-10-22 14:13:44	ga_s2am_ard_3-2-1_42FYF_2023-10-22_final
2023-10-25 14:23:42	ga_s2am_ard_3-2-1_42FYF_2023-10-25_final
2023-11-01 14:13:43	ga_s2am_ard_3-2-1_42FYF_2023-11-01_final
2023-11-04 14:23:42	ga_s2am_ard_3-2-1_42FYF_2023-11-04_final
2023-11-14 14:23:42	ga_s2am_ard_3-2-1_42FYF_2023-11-14_final
2023-11-24 14:23:37	ga_s2am_ard_3-2-1_42FYF_2023-11-24_final
2023-12-04 14:23:36	ga_s2am_ard_3-2-1_42FYF_2023-12-04_final
2023-12-11 14:13:39	ga_s2am_ard_3-2-1_42FYF_2023-12-11_final
2023-12-14 14:23:39	ga_s2am_ard_3-2-1_42FYF_2023-12-14_final
2023-12-21 14:13:40	ga_s2am_ard_3-2-1_42FYF_2023-12-21_final
2023-12-31 14:13:41	ga_s2am_ard_3-2-1_42FYF_2023-12-31_final
2024-01-03 14:23:40	ga_s2am_ard_3-2-1_42FYF_2024-01-03_final
2024-01-10 14:13:39	ga_s2am_ard_3-2-1_42FYF_2024-01-10_final
2024-01-13 14:23:37	ga_s2am_ard_3-2-1_42FYF_2024-01-13_final
2024-01-20 14:13:38	ga_s2am_ard_3-2-1_42FYF_2024-01-20_final
2024-01-23 14:23:35	ga_s2am_ard_3-2-1_42FYF_2024-01-23_final
2024-02-09 14:13:40	ga_s2am_ard_3-2-1_42FYF_2024-02-09_final
2024-02-12 14:23:40	ga_s2am_ard_3-2-1_42FYF_2024-02-12_final
2024-02-19 14:13:42	ga_s2am_ard_3-2-1_42FYF_2024-02-19_final
2024-02-22 14:23:41	ga_s2am_ard_3-2-1_42FYF_2024-02-22_final
2024-02-29 14:13:46	ga_s2am_ard_3-2-1_42FYF_2024-02-29_final
2024-03-03 14:23:42	ga_s2am_ard_3-2-1_42FYF_2024-03-03_final
2024-03-13 14:23:43	ga_s2am_ard_3-2-1_42FYF_2024-03-13_final
2024-03-20 14:13:45	ga_s2am_ard_3-2-1_42FYF_2024-03-20_final
2024-03-23 14:23:43	ga_s2am_ard_3-2-1_42FYF_2024-03-23_final
2024-03-30 14:13:46	ga_s2am_ard_3-2-1_42FYF_2024-03-30_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