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

40 results

Time (local)	Label
2017-12-06 09:32:49	ga_s2bm_ard_3-2-1_55GEP_2017-12-06_final.stac-item
2018-04-28 11:24:29	ga_s2bm_ard_3-2-1_51HVD_2018-04-28_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51LUF_2018-06-23_final.stac-item
2019-03-28 09:28:32	ga_s2bm_ard_3-2-1_55GFP_2019-03-27_final.stac-item
2019-05-25 10:24:27	ga_s2bm_ard_3-2-1_53JRM_2019-05-25_final.stac-item
2019-12-16 11:15:34	ga_s2bm_ard_3-2-1_51JYH_2019-12-16_final.stac-item
2020-02-25 10:43:45	ga_s2bm_ard_3-2-1_53KPP_2020-02-25_final.stac-item
2020-03-26 10:44:04	ga_s2bm_ard_3-2-1_53JNN_2020-03-26_final.stac-item
2020-04-04 11:16:17	ga_s2bm_ard_3-2-1_52HBK_2020-04-04_final.stac-item
2020-10-09 10:33:56	ga_s2bm_ard_3-2-1_53KPP_2020-10-09_final.stac-item
2020-10-31 09:33:53	ga_s2bm_ard_3-2-1_56JNS_2020-10-31_final.stac-item
2020-12-20 09:33:31	ga_s2bm_ard_3-2-1_56JNT_2020-12-20_final.stac-item
2020-12-24 10:52:06	ga_s2bm_ard_3-2-1_53KMA_2020-12-24_final.stac-item
2020-12-26 11:33:31	ga_s2bm_ard_3-2-1_51KUS_2020-12-26_final.stac-item
2021-01-01 10:11:17	ga_s2bm_ard_3-2-1_55LCC_2021-01-01_final.stac-item
2021-08-22 10:24:18	ga_s2bm_ard_3-2-1_53JRM_2021-08-22_final.stac-item
2021-09-24 10:34:11	ga_s2bm_ard_3-2-1_53JNN_2021-09-24_final.stac-item
2021-10-09 11:23:36	ga_s2bm_ard_3-2-1_52KBA_2021-10-09_final.stac-item
2021-10-14 10:35:02	ga_s2bm_ard_3-2-1_53JQJ_2021-10-14_final.stac-item
2021-11-03 10:34:28	ga_s2bm_ard_3-2-1_53JNM_2021-11-03_final.stac-item
2021-11-15 09:38:47	ga_s2bm_ard_3-2-1_55GDN_2021-11-15_final.stac-item
2022-03-23 10:34:19	ga_s2bm_ard_3-2-1_53JPM_2022-03-23_final.stac-item
2022-04-26 10:11:35	ga_s2bm_ard_3-2-1_54KYG_2022-04-26_final.stac-item
2022-06-11 10:33:52	ga_s2bm_ard_3-2-1_53KQP_2022-06-11_final.stac-item
2022-07-21 10:33:54	ga_s2bm_ard_3-2-1_53KQP_2022-07-21_final.stac-item
2022-08-12 11:16:44	ga_s2bm_ard_3-2-1_51HXD_2022-08-12_final.stac-item
2022-10-09 10:34:19	ga_s2bm_ard_3-2-1_53JPM_2022-10-09_final.stac-item
2022-10-23 10:14:47	ga_s2bm_ard_3-2-1_54JYP_2022-10-23_final.stac-item
2022-11-27 11:03:19	ga_s2bm_ard_3-2-1_52KEB_2022-11-27_final.stac-item
2023-01-07 10:33:50	ga_s2bm_ard_3-2-1_53KPP_2023-01-07_final.stac-item
2023-01-09 11:10:40	ga_s2bm_ard_3-2-1_52LGM_2023-01-09_final.stac-item
2023-03-28 10:33:52	ga_s2bm_ard_3-2-1_53KQP_2023-03-28_final
2023-05-07 10:34:02	ga_s2bm_ard_3-2-1_53JRN_2023-05-07_final
2023-07-10 10:16:36	ga_s2bm_ard_3-2-1_54HUH_2023-07-10_final
2023-08-25 10:33:57	ga_s2bm_ard_3-2-1_53KPP_2023-08-25_final
2023-11-23 10:33:44	ga_s2bm_ard_3-2-1_53KQP_2023-11-23_final
2024-01-24 09:32:54	ga_s2bm_ard_3-2-1_56KMA_2024-01-24_final
2024-03-09 10:23:45	ga_s2bm_ard_3-2-1_54KTU_2024-03-09_final
2024-05-01 10:34:18	ga_s2bm_ard_3-2-1_53JQM_2024-05-01_final
2024-05-01 10:36:36	ga_s2bm_ard_3-2-1_53HNC_2024-05-01_final

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