Search ga_s2bm_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

93 results

Time (local)	Label
2022-10-28 09:28:34	ga_s2bm_ard_3-2-1_55GGN_2022-10-27_nrt.stac-item
2022-10-28 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2022-10-27_nrt.stac-item
2022-12-07 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2022-12-06_nrt.stac-item
2022-12-17 09:28:39	ga_s2bm_ard_3-2-1_55GGN_2022-12-16_nrt.stac-item
2022-12-27 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2022-12-26_nrt.stac-item
2023-01-06 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2023-01-05_nrt.stac-item
2023-01-16 09:28:30	ga_s2bm_ard_3-2-1_55GGN_2023-01-15_nrt.stac-item
2023-01-16 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2023-01-15_nrt.stac-item
2023-01-26 09:28:33	ga_s2bm_ard_3-2-1_55GGN_2023-01-25_nrt.stac-item
2023-01-26 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2023-01-25_nrt.stac-item
2023-02-05 09:28:33	ga_s2bm_ard_3-2-1_55GGN_2023-02-04_nrt.stac-item
2023-02-05 09:28:39	ga_s2bm_ard_3-2-1_55GGN_2023-02-04_nrt.stac-item
2023-02-15 09:28:32	ga_s2bm_ard_3-2-1_55GGN_2023-02-14_nrt.stac-item
2023-02-15 09:28:39	ga_s2bm_ard_3-2-1_55GGN_2023-02-14_nrt.stac-item
2023-02-25 09:28:34	ga_s2bm_ard_3-2-1_55GGN_2023-02-24_nrt
2023-02-25 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2023-02-24_nrt
2023-03-07 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2023-03-06_nrt
2023-03-07 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2023-03-06_nrt
2023-03-17 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2023-03-16_nrt
2023-03-17 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2023-03-16_nrt
2023-03-27 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2023-03-26_nrt
2023-03-27 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2023-03-26_nrt
2023-04-06 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2023-04-05_nrt
2023-04-06 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2023-04-05_nrt
2023-04-16 09:28:42	ga_s2bm_ard_3-2-1_55GGN_2023-04-15_nrt
2023-04-26 09:28:35	ga_s2bm_ard_3-2-1_55GGN_2023-04-25_nrt
2023-04-26 09:28:42	ga_s2bm_ard_3-2-1_55GGN_2023-04-25_nrt
2023-05-06 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2023-05-05_nrt
2023-05-06 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2023-05-05_nrt
2023-05-16 09:28:39	ga_s2bm_ard_3-2-1_55GGN_2023-05-15_nrt
2023-05-16 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-05-15_nrt
2023-05-26 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2023-05-25_nrt
2023-05-26 09:28:50	ga_s2bm_ard_3-2-1_55GGN_2023-05-25_nrt
2023-06-05 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2023-06-04_nrt
2023-06-05 09:28:48	ga_s2bm_ard_3-2-1_55GGN_2023-06-04_nrt
2023-06-15 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2023-06-14_nrt
2023-06-15 09:28:47	ga_s2bm_ard_3-2-1_55GGN_2023-06-14_nrt
2023-06-25 09:28:39	ga_s2bm_ard_3-2-1_55GGN_2023-06-24_nrt
2023-06-25 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-06-24_nrt
2023-07-05 09:28:42	ga_s2bm_ard_3-2-1_55GGN_2023-07-04_nrt
2023-07-05 09:28:49	ga_s2bm_ard_3-2-1_55GGN_2023-07-04_nrt
2023-07-15 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2023-07-14_nrt
2023-07-15 09:28:47	ga_s2bm_ard_3-2-1_55GGN_2023-07-14_nrt
2023-07-25 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2023-07-24_nrt
2023-07-25 09:28:48	ga_s2bm_ard_3-2-1_55GGN_2023-07-24_nrt
2023-08-04 09:28:45	ga_s2bm_ard_3-2-1_55GGN_2023-08-03_nrt
2023-08-14 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-08-13_nrt
2023-08-24 09:28:45	ga_s2bm_ard_3-2-1_55GGN_2023-08-23_nrt
2023-09-03 09:28:45	ga_s2bm_ard_3-2-1_55GGN_2023-09-02_nrt
2023-09-13 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2023-09-12_nrt
2023-09-23 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2023-09-22_nrt
2023-09-23 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2023-09-22_nrt
2023-10-03 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2023-10-02_nrt
2023-10-03 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2023-10-02_nrt
2023-10-13 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2023-10-12_nrt
2023-10-13 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2023-10-12_nrt
2023-10-23 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2023-10-22_nrt
2023-10-23 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2023-10-22_nrt
2023-11-02 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2023-11-01_nrt
2023-11-02 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2023-11-01_nrt
2023-11-12 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2023-11-11_nrt
2023-11-12 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-11-11_nrt
2023-11-22 09:28:34	ga_s2bm_ard_3-2-1_55GGN_2023-11-21_nrt
2023-11-22 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2023-11-21_nrt
2023-12-02 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2023-12-01_nrt
2023-12-02 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-12-01_nrt
2023-12-12 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2023-12-11_nrt
2023-12-22 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2023-12-21_nrt
2024-01-01 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2023-12-31_nrt
2024-01-11 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2024-01-10_nrt
2024-01-21 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2024-01-20_interim.stac-item
2024-01-31 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2024-01-30_nrt
2024-01-31 09:28:42	ga_s2bm_ard_3-2-1_55GGN_2024-01-30_nrt
2024-02-10 09:28:39	ga_s2bm_ard_3-2-1_55GGN_2024-02-09_nrt
2024-02-10 09:28:45	ga_s2bm_ard_3-2-1_55GGN_2024-02-09_nrt
2024-02-20 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2024-02-19_nrt
2024-02-20 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2024-02-19_nrt
2024-03-01 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2024-02-29_nrt
2024-03-11 09:28:31	ga_s2bm_ard_3-2-1_55GGN_2024-03-10_nrt
2024-03-11 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2024-03-10_nrt
2024-03-21 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2024-03-20_nrt
2024-03-31 09:28:36	ga_s2bm_ard_3-2-1_55GGN_2024-03-30_nrt
2024-03-31 09:28:43	ga_s2bm_ard_3-2-1_55GGN_2024-03-30_nrt
2024-04-10 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2024-04-09_nrt
2024-04-10 09:28:45	ga_s2bm_ard_3-2-1_55GGN_2024-04-09_nrt
2024-04-20 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2024-04-19_nrt
2024-04-20 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2024-04-19_nrt
2024-04-30 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2024-04-29_nrt
2024-05-10 09:28:37	ga_s2bm_ard_3-2-1_55GGN_2024-05-09_nrt
2024-05-10 09:28:44	ga_s2bm_ard_3-2-1_55GGN_2024-05-09_nrt
2024-05-20 09:28:34	ga_s2bm_ard_3-2-1_55GGN_2024-05-19_nrt
2024-05-20 09:28:41	ga_s2bm_ard_3-2-1_55GGN_2024-05-19_nrt
2024-05-30 09:28:40	ga_s2bm_ard_3-2-1_55GGN_2024-05-29_nrt

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years