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

66 results

Time (local)	Label
2023-12-01 09:50:56	ga_s2bm_ard_3-2-1_56LLJ_2023-12-01_nrt
2023-12-01 09:50:58	ga_s2bm_ard_3-2-1_56LKJ_2023-12-01_nrt
2023-12-01 09:50:59	ga_s2bm_ard_3-2-1_55LHD_2023-12-01_nrt
2023-12-01 09:51:00	ga_s2bm_ard_3-2-1_55LGD_2023-12-01_nrt
2023-12-01 09:51:01	ga_s2bm_ard_3-2-1_56LLH_2023-12-01_nrt
2023-12-01 09:51:02	ga_s2bm_ard_3-2-1_55LFD_2023-12-01_nrt
2023-12-01 09:51:07	ga_s2bm_ard_3-2-1_56LKH_2023-12-01_nrt
2023-12-01 09:51:09	ga_s2bm_ard_3-2-1_55LHC_2023-12-01_final
2023-12-01 09:51:12	ga_s2bm_ard_3-2-1_55LGC_2023-12-01_final
2023-12-01 09:51:16	ga_s2bm_ard_3-2-1_55LFC_2023-12-01_final
2023-12-01 09:51:22	ga_s2bm_ard_3-2-1_56KKG_2023-12-01_final
2023-12-01 09:51:23	ga_s2bm_ard_3-2-1_55KHB_2023-12-01_final
2023-12-01 09:51:27	ga_s2bm_ard_3-2-1_55KGB_2023-12-01_final
2023-12-01 09:51:30	ga_s2bm_ard_3-2-1_55KFB_2023-12-01_final
2023-12-01 09:51:37	ga_s2bm_ard_3-2-1_56KKF_2023-12-01_final
2023-12-01 09:51:38	ga_s2bm_ard_3-2-1_55KHA_2023-12-01_nrt
2023-12-01 09:51:41	ga_s2bm_ard_3-2-1_55KGA_2023-12-01_nrt
2023-12-01 09:51:45	ga_s2bm_ard_3-2-1_55KFA_2023-12-01_final
2023-12-01 09:51:50	ga_s2bm_ard_3-2-1_55KEA_2023-12-01_nrt
2023-12-01 09:51:51	ga_s2bm_ard_3-2-1_56KKE_2023-12-01_nrt
2023-12-01 09:51:52	ga_s2bm_ard_3-2-1_55KHV_2023-12-01_nrt
2023-12-01 09:51:56	ga_s2bm_ard_3-2-1_55KGV_2023-12-01_nrt
2023-12-01 09:51:59	ga_s2bm_ard_3-2-1_55KFV_2023-12-01_nrt
2023-12-01 09:52:03	ga_s2bm_ard_3-2-1_55KEV_2023-12-01_final
2023-12-01 09:52:05	ga_s2bm_ard_3-2-1_56KKD_2023-12-01_nrt
2023-12-01 09:52:07	ga_s2bm_ard_3-2-1_55KHU_2023-12-01_nrt
2023-12-01 09:52:10	ga_s2bm_ard_3-2-1_55KGU_2023-12-01_final
2023-12-01 09:52:14	ga_s2bm_ard_3-2-1_55KFU_2023-12-01_final
2023-12-01 09:52:16	ga_s2bm_ard_3-2-1_56KKC_2023-12-01_nrt
2023-12-01 09:52:17	ga_s2bm_ard_3-2-1_55KEU_2023-12-01_final
2023-12-01 09:52:21	ga_s2bm_ard_3-2-1_55KHT_2023-12-01_nrt
2023-12-01 09:52:25	ga_s2bm_ard_3-2-1_55KGT_2023-12-01_final
2023-12-01 09:52:28	ga_s2bm_ard_3-2-1_55KFT_2023-12-01_final
2023-12-01 09:52:32	ga_s2bm_ard_3-2-1_55KET_2023-12-01_final
2023-12-01 09:52:32	ga_s2bm_ard_3-2-1_55KHS_2023-12-01_final
2023-12-01 09:52:39	ga_s2bm_ard_3-2-1_55KGS_2023-12-01_final
2023-12-01 09:52:43	ga_s2bm_ard_3-2-1_55KFS_2023-12-01_final
2023-12-01 09:52:46	ga_s2bm_ard_3-2-1_55KES_2023-12-01_final
2023-12-01 09:52:52	ga_s2bm_ard_3-2-1_55KDS_2023-12-01_final
2023-12-01 09:52:53	ga_s2bm_ard_3-2-1_55KGR_2023-12-01_final
2023-12-01 09:52:57	ga_s2bm_ard_3-2-1_55KFR_2023-12-01_final
2023-12-01 09:53:01	ga_s2bm_ard_3-2-1_55KER_2023-12-01_final
2023-12-01 09:53:04	ga_s2bm_ard_3-2-1_55KDR_2023-12-01_final
2023-12-01 09:53:08	ga_s2bm_ard_3-2-1_55KGQ_2023-12-01_final
2023-12-01 09:53:12	ga_s2bm_ard_3-2-1_55KFQ_2023-12-01_final
2023-12-01 09:53:15	ga_s2bm_ard_3-2-1_55KEQ_2023-12-01_final
2023-12-01 09:53:18	ga_s2bm_ard_3-2-1_55KDQ_2023-12-01_final
2023-12-01 09:53:22	ga_s2bm_ard_3-2-1_55KGP_2023-12-01_final
2023-12-01 09:53:26	ga_s2bm_ard_3-2-1_55KFP_2023-12-01_final
2023-12-01 09:53:30	ga_s2bm_ard_3-2-1_55KEP_2023-12-01_final
2023-12-01 09:53:33	ga_s2bm_ard_3-2-1_55KDP_2023-12-01_final
2023-12-01 09:53:35	ga_s2bm_ard_3-2-1_55JGN_2023-12-01_final
2023-12-01 09:53:41	ga_s2bm_ard_3-2-1_55JFN_2023-12-01_final
2023-12-01 09:53:44	ga_s2bm_ard_3-2-1_55JEN_2023-12-01_final
2023-12-01 09:53:45	ga_s2bm_ard_3-2-1_55JGM_2023-12-01_final
2023-12-01 09:53:48	ga_s2bm_ard_3-2-1_55JDN_2023-12-01_final
2023-12-01 09:53:55	ga_s2bm_ard_3-2-1_55JCN_2023-12-01_final
2023-12-01 09:53:55	ga_s2bm_ard_3-2-1_55JFM_2023-12-01_final
2023-12-01 09:53:59	ga_s2bm_ard_3-2-1_55JEM_2023-12-01_final
2023-12-01 09:54:02	ga_s2bm_ard_3-2-1_55JDM_2023-12-01_final
2023-12-01 09:54:06	ga_s2bm_ard_3-2-1_55JCM_2023-12-01_final
2023-12-01 09:54:09	ga_s2bm_ard_3-2-1_55JFL_2023-12-01_final
2023-12-01 09:54:11	ga_s2bm_ard_3-2-1_55JEL_2023-12-01_final
2023-12-01 09:54:12	ga_s2bm_ard_3-2-1_55JDL_2023-12-01_final
2023-12-01 09:54:14	ga_s2bm_ard_3-2-1_55JCL_2023-12-01_final
2023-12-01 09:54:15	ga_s2bm_ard_3-2-1_55JFK_2023-12-01_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