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

55 results

Time (local)	Label
2022-10-28 10:17:45	ga_s2am_ard_3-2-1_53HQT_2022-10-28_nrt.stac-item
2022-12-07 10:17:42	ga_s2am_ard_3-2-1_53HQT_2022-12-07_nrt.stac-item
2022-12-17 10:17:41	ga_s2am_ard_3-2-1_53HQT_2022-12-17_nrt.stac-item
2022-12-27 10:17:40	ga_s2am_ard_3-2-1_53HQT_2022-12-27_nrt.stac-item
2023-01-06 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-01-06_nrt.stac-item
2023-01-16 10:17:38	ga_s2am_ard_3-2-1_53HQT_2023-01-16_nrt.stac-item
2023-01-26 10:17:39	ga_s2am_ard_3-2-1_53HQT_2023-01-26_nrt.stac-item
2023-02-05 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-02-05_nrt.stac-item
2023-02-15 10:17:39	ga_s2am_ard_3-2-1_53HQT_2023-02-15_nrt.stac-item
2023-02-25 10:17:39	ga_s2am_ard_3-2-1_53HQT_2023-02-25_nrt
2023-03-07 10:17:37	ga_s2am_ard_3-2-1_53HQT_2023-03-07_nrt
2023-03-17 10:17:39	ga_s2am_ard_3-2-1_53HQT_2023-03-17_nrt
2023-03-27 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-03-27_nrt
2023-04-06 10:17:41	ga_s2am_ard_3-2-1_53HQT_2023-04-06_nrt
2023-04-16 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-04-16_nrt
2023-04-26 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-04-26_nrt
2023-05-06 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-05-06_nrt
2023-05-16 10:17:41	ga_s2am_ard_3-2-1_53HQT_2023-05-16_nrt
2023-05-26 10:17:43	ga_s2am_ard_3-2-1_53HQT_2023-05-26_nrt
2023-06-05 10:17:44	ga_s2am_ard_3-2-1_53HQT_2023-06-05_nrt
2023-06-15 10:17:44	ga_s2am_ard_3-2-1_53HQT_2023-06-15_nrt
2023-06-25 10:17:43	ga_s2am_ard_3-2-1_53HQT_2023-06-25_nrt
2023-07-05 10:17:45	ga_s2am_ard_3-2-1_53HQT_2023-07-05_nrt
2023-07-15 10:17:45	ga_s2am_ard_3-2-1_53HQT_2023-07-15_nrt
2023-07-25 10:17:45	ga_s2am_ard_3-2-1_53HQT_2023-07-25_nrt
2023-08-04 10:17:45	ga_s2am_ard_3-2-1_53HQT_2023-08-04_nrt
2023-08-14 10:17:45	ga_s2am_ard_3-2-1_53HQT_2023-08-14_nrt
2023-08-24 10:17:46	ga_s2am_ard_3-2-1_53HQT_2023-08-24_nrt
2023-09-03 10:17:45	ga_s2am_ard_3-2-1_53HQT_2023-09-03_nrt
2023-09-13 10:17:44	ga_s2am_ard_3-2-1_53HQT_2023-09-13_nrt
2023-09-23 10:17:42	ga_s2am_ard_3-2-1_53HQT_2023-09-23_nrt
2023-10-03 10:17:42	ga_s2am_ard_3-2-1_53HQT_2023-10-03_nrt
2023-10-13 10:17:38	ga_s2am_ard_3-2-1_53HQT_2023-10-13_nrt
2023-10-23 10:17:40	ga_s2am_ard_3-2-1_53HQT_2023-10-23_nrt
2023-11-02 10:17:39	ga_s2am_ard_3-2-1_53HQT_2023-11-02_nrt
2023-11-12 10:17:39	ga_s2am_ard_3-2-1_53HQT_2023-11-12_nrt
2023-11-22 10:17:36	ga_s2am_ard_3-2-1_53HQT_2023-11-22_nrt
2023-12-02 10:17:32	ga_s2am_ard_3-2-1_53HQT_2023-12-02_nrt
2023-12-12 10:17:35	ga_s2am_ard_3-2-1_53HQT_2023-12-12_nrt
2023-12-22 10:17:36	ga_s2am_ard_3-2-1_53HQT_2023-12-22_nrt
2024-01-01 10:17:37	ga_s2am_ard_3-2-1_53HQT_2024-01-01_nrt
2024-01-11 10:17:35	ga_s2am_ard_3-2-1_53HQT_2024-01-11_nrt
2024-01-21 10:17:32	ga_s2am_ard_3-2-1_53HQT_2024-01-21_nrt
2024-01-31 10:17:35	ga_s2am_ard_3-2-1_53HQT_2024-01-31_nrt
2024-02-10 10:17:36	ga_s2am_ard_3-2-1_53HQT_2024-02-10_nrt
2024-02-20 10:17:38	ga_s2am_ard_3-2-1_53HQT_2024-02-20_nrt
2024-03-01 10:17:40	ga_s2am_ard_3-2-1_53HQT_2024-03-01_nrt
2024-03-11 10:17:40	ga_s2am_ard_3-2-1_53HQT_2024-03-11_nrt
2024-03-21 10:17:41	ga_s2am_ard_3-2-1_53HQT_2024-03-21_nrt
2024-03-31 10:17:39	ga_s2am_ard_3-2-1_53HQT_2024-03-31_nrt
2024-04-10 10:17:40	ga_s2am_ard_3-2-1_53HQT_2024-04-10_nrt
2024-04-20 10:17:43	ga_s2am_ard_3-2-1_53HQT_2024-04-20_nrt
2024-04-30 10:17:43	ga_s2am_ard_3-2-1_53HQT_2024-04-30_nrt
2024-05-10 10:17:43	ga_s2am_ard_3-2-1_53HQT_2024-05-10_nrt
2024-05-20 10:17:41	ga_s2am_ard_3-2-1_53HQT_2024-05-20_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