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

54 results

Time (local)	Label
2022-10-29 12:13:32	ga_s2bm_ard_3-2-1_49KFT_2022-10-29_nrt.stac-item
2022-12-18 12:13:32	ga_s2bm_ard_3-2-1_49KFT_2022-12-18_nrt.stac-item
2022-12-28 12:13:32	ga_s2bm_ard_3-2-1_49KFT_2022-12-28_nrt.stac-item
2023-01-07 12:13:31	ga_s2bm_ard_3-2-1_49KFT_2023-01-07_nrt.stac-item
2023-01-17 12:13:30	ga_s2bm_ard_3-2-1_49KFT_2023-01-17_nrt.stac-item
2023-01-27 12:13:31	ga_s2bm_ard_3-2-1_49KFT_2023-01-27_nrt.stac-item
2023-02-06 12:13:31	ga_s2bm_ard_3-2-1_49KFT_2023-02-06_nrt.stac-item
2023-02-16 12:13:31	ga_s2bm_ard_3-2-1_49KFT_2023-02-16_nrt.stac-item
2023-02-26 12:13:34	ga_s2bm_ard_3-2-1_49KFT_2023-02-26_nrt
2023-03-08 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-03-08_nrt
2023-03-18 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-03-18_nrt
2023-03-28 12:13:36	ga_s2bm_ard_3-2-1_49KFT_2023-03-28_nrt
2023-04-07 12:13:36	ga_s2bm_ard_3-2-1_49KFT_2023-04-07_nrt
2023-04-17 12:13:35	ga_s2bm_ard_3-2-1_49KFT_2023-04-17_nrt
2023-04-27 12:13:35	ga_s2bm_ard_3-2-1_49KFT_2023-04-27_nrt
2023-05-07 12:13:36	ga_s2bm_ard_3-2-1_49KFT_2023-05-07_nrt
2023-05-17 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-05-17_nrt
2023-05-27 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-05-27_nrt
2023-06-06 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-06-06_nrt
2023-06-16 12:13:38	ga_s2bm_ard_3-2-1_49KFT_2023-06-16_nrt
2023-06-26 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-06-26_nrt
2023-07-06 12:13:38	ga_s2bm_ard_3-2-1_49KFT_2023-07-06_nrt
2023-07-16 12:13:38	ga_s2bm_ard_3-2-1_49KFT_2023-07-16_nrt
2023-07-26 12:13:39	ga_s2bm_ard_3-2-1_49KFT_2023-07-26_nrt
2023-08-05 12:13:38	ga_s2bm_ard_3-2-1_49KFT_2023-08-05_nrt
2023-08-15 12:13:38	ga_s2bm_ard_3-2-1_49KFT_2023-08-15_nrt
2023-08-25 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-08-25_nrt
2023-09-04 12:13:37	ga_s2bm_ard_3-2-1_49KFT_2023-09-04_nrt
2023-09-14 12:13:36	ga_s2bm_ard_3-2-1_49KFT_2023-09-14_nrt
2023-09-24 12:13:36	ga_s2bm_ard_3-2-1_49KFT_2023-09-24_nrt
2023-10-04 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2023-10-04_nrt
2023-10-14 12:13:35	ga_s2bm_ard_3-2-1_49KFT_2023-10-14_nrt
2023-10-24 12:13:34	ga_s2bm_ard_3-2-1_49KFT_2023-10-24_nrt
2023-11-03 12:13:35	ga_s2bm_ard_3-2-1_49KFT_2023-11-03_nrt
2023-11-13 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2023-11-13_nrt
2023-11-23 12:13:28	ga_s2bm_ard_3-2-1_49KFT_2023-11-23_nrt
2023-12-03 12:13:30	ga_s2bm_ard_3-2-1_49KFT_2023-12-03_nrt
2023-12-13 12:13:31	ga_s2bm_ard_3-2-1_49KFT_2023-12-13_nrt
2023-12-23 12:13:34	ga_s2bm_ard_3-2-1_49KFT_2023-12-23_nrt
2024-01-02 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-01-02_nrt
2024-01-12 12:13:31	ga_s2bm_ard_3-2-1_49KFT_2024-01-12_nrt
2024-01-22 12:13:32	ga_s2bm_ard_3-2-1_49KFT_2024-01-22_interim.stac-item
2024-02-01 12:13:30	ga_s2bm_ard_3-2-1_49KFT_2024-02-01_nrt
2024-02-11 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-02-11_nrt
2024-02-21 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-02-21_nrt
2024-03-12 12:13:29	ga_s2bm_ard_3-2-1_49KFT_2024-03-12_nrt
2024-03-22 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-03-22_nrt
2024-04-01 12:13:32	ga_s2bm_ard_3-2-1_49KFT_2024-04-01_nrt
2024-04-11 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-04-11_nrt
2024-04-21 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-04-21_nrt
2024-05-01 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-05-01_nrt
2024-05-11 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-05-11_interim
2024-05-21 12:13:32	ga_s2bm_ard_3-2-1_49KFT_2024-05-21_nrt
2024-05-31 12:13:33	ga_s2bm_ard_3-2-1_49KFT_2024-05-31_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