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

74 results

Time (local)	Label
2024-04-21 10:36:43	ga_s2bm_ard_3-2-1_53HLC_2024-04-21_nrt
2024-04-21 10:36:58	ga_s2bm_ard_3-2-1_53HLB_2024-04-21_nrt
2024-04-21 10:37:02	ga_s2bm_ard_3-2-1_53HNA_2024-04-21_nrt
2024-04-21 12:13:25	ga_s2bm_ard_3-2-1_49KFU_2024-04-21_nrt
2024-04-21 12:13:29	ga_s2bm_ard_3-2-1_50KKC_2024-04-21_nrt
2024-04-21 12:13:31	ga_s2bm_ard_3-2-1_49KGT_2024-04-21_nrt
2024-04-21 12:15:14	ga_s2bm_ard_3-2-1_49JFL_2024-04-21_nrt
2024-04-22 09:59:38	ga_s2bm_ard_3-2-1_55LHJ_2024-04-22_nrt
2024-04-22 09:59:44	ga_s2bm_ard_3-2-1_55LGJ_2024-04-22_nrt
2024-04-22 09:59:47	ga_s2bm_ard_3-2-1_55LFJ_2024-04-22_nrt
2024-04-22 09:59:48	ga_s2bm_ard_3-2-1_55LHH_2024-04-22_nrt
2024-04-22 09:59:51	ga_s2bm_ard_3-2-1_55LEJ_2024-04-22_nrt
2024-04-22 09:59:58	ga_s2bm_ard_3-2-1_55LGH_2024-04-22_nrt
2024-04-22 10:00:02	ga_s2bm_ard_3-2-1_55LFH_2024-04-22_nrt
2024-04-22 10:00:05	ga_s2bm_ard_3-2-1_55LEH_2024-04-22_nrt
2024-04-22 10:00:09	ga_s2bm_ard_3-2-1_55LDH_2024-04-22_nrt
2024-04-22 10:00:13	ga_s2bm_ard_3-2-1_55LGG_2024-04-22_nrt
2024-04-22 10:00:16	ga_s2bm_ard_3-2-1_55LFG_2024-04-22_nrt
2024-04-22 10:00:19	ga_s2bm_ard_3-2-1_55LEG_2024-04-22_nrt
2024-04-22 10:00:22	ga_s2bm_ard_3-2-1_55LDG_2024-04-22_nrt
2024-04-22 10:00:27	ga_s2bm_ard_3-2-1_55LGF_2024-04-22_nrt
2024-04-22 10:00:31	ga_s2bm_ard_3-2-1_55LFF_2024-04-22_nrt
2024-04-22 10:00:34	ga_s2bm_ard_3-2-1_55LEF_2024-04-22_nrt
2024-04-22 10:00:37	ga_s2bm_ard_3-2-1_55LDF_2024-04-22_nrt
2024-04-22 10:00:41	ga_s2bm_ard_3-2-1_55LGE_2024-04-22_nrt
2024-04-22 10:00:45	ga_s2bm_ard_3-2-1_55LFE_2024-04-22_nrt
2024-04-22 10:00:49	ga_s2bm_ard_3-2-1_55LEE_2024-04-22_nrt
2024-04-22 10:00:51	ga_s2bm_ard_3-2-1_55LGD_2024-04-22_nrt
2024-04-22 10:00:52	ga_s2bm_ard_3-2-1_55LDE_2024-04-22_nrt
2024-04-22 10:00:59	ga_s2bm_ard_3-2-1_55LFD_2024-04-22_nrt
2024-04-22 10:01:03	ga_s2bm_ard_3-2-1_55LED_2024-04-22_nrt
2024-04-22 10:01:06	ga_s2bm_ard_3-2-1_55LDD_2024-04-22_nrt
2024-04-22 10:01:21	ga_s2bm_ard_3-2-1_55LDC_2024-04-22_nrt
2024-04-22 10:01:36	ga_s2bm_ard_3-2-1_55KDB_2024-04-22_nrt
2024-04-22 10:01:47	ga_s2bm_ard_3-2-1_55KEA_2024-04-22_nrt
2024-04-22 10:01:55	ga_s2bm_ard_3-2-1_55KFV_2024-04-22_nrt
2024-04-22 10:02:16	ga_s2bm_ard_3-2-1_55KEU_2024-04-22_nrt
2024-04-22 10:03:21	ga_s2bm_ard_3-2-1_55KCQ_2024-04-22_nrt
2024-04-22 10:03:35	ga_s2bm_ard_3-2-1_55KCP_2024-04-22_nrt
2024-04-22 10:03:38	ga_s2bm_ard_3-2-1_55KBP_2024-04-22_nrt
2024-04-22 10:03:53	ga_s2bm_ard_3-2-1_54JZT_2024-04-22_nrt
2024-04-22 10:04:54	ga_s2bm_ard_3-2-1_54JYP_2024-04-22_nrt
2024-04-22 10:05:19	ga_s2bm_ard_3-2-1_55JBG_2024-04-22_nrt
2024-04-22 10:05:45	ga_s2bm_ard_3-2-1_54JWL_2024-04-22_nrt
2024-04-22 10:06:19	ga_s2bm_ard_3-2-1_55HBC_2024-04-22_nrt
2024-04-22 10:06:33	ga_s2bm_ard_3-2-1_55HBB_2024-04-22_nrt
2024-04-22 10:06:34	ga_s2bm_ard_3-2-1_54HVH_2024-04-22_nrt
2024-04-22 10:07:03	ga_s2bm_ard_3-2-1_54HYE_2024-04-22_nrt
2024-04-22 10:07:45	ga_s2bm_ard_3-2-1_54HUC_2024-04-22_nrt
2024-04-22 10:07:47	ga_s2bm_ard_3-2-1_54HXB_2024-04-22_nrt
2024-04-22 10:07:48	ga_s2bm_ard_3-2-1_54HWB_2024-04-22_nrt
2024-04-22 10:07:49	ga_s2bm_ard_3-2-1_54HVB_2024-04-22_nrt
2024-04-22 11:40:25	ga_s2bm_ard_3-2-1_51LXJ_2024-04-22_nrt
2024-04-22 11:40:28	ga_s2bm_ard_3-2-1_51LWJ_2024-04-22_nrt
2024-04-22 11:40:31	ga_s2bm_ard_3-2-1_51LVJ_2024-04-22_nrt
2024-04-22 11:40:39	ga_s2bm_ard_3-2-1_51LXH_2024-04-22_nrt
2024-04-22 11:40:43	ga_s2bm_ard_3-2-1_51LWH_2024-04-22_nrt
2024-04-22 11:40:46	ga_s2bm_ard_3-2-1_51LVH_2024-04-22_nrt
2024-04-22 11:40:54	ga_s2bm_ard_3-2-1_51LXG_2024-04-22_nrt
2024-04-22 11:41:04	ga_s2bm_ard_3-2-1_51LUG_2024-04-22_nrt
2024-04-22 11:41:12	ga_s2bm_ard_3-2-1_51LWF_2024-04-22_nrt
2024-04-22 11:41:17	ga_s2bm_ard_3-2-1_51LXE_2024-04-22_nrt
2024-04-22 11:41:37	ga_s2bm_ard_3-2-1_51LTE_2024-04-22_nrt
2024-04-22 11:41:41	ga_s2bm_ard_3-2-1_51LWD_2024-04-22_nrt
2024-04-22 11:41:50	ga_s2bm_ard_3-2-1_51LTD_2024-04-22_nrt
2024-04-22 11:42:08	ga_s2bm_ard_3-2-1_50LRH_2024-04-22_nrt
2024-04-22 11:42:20	ga_s2bm_ard_3-2-1_51KTB_2024-04-22_nrt
2024-04-22 11:42:20	ga_s2bm_ard_3-2-1_50KRG_2024-04-22_nrt
2024-04-22 11:42:34	ga_s2bm_ard_3-2-1_51KTA_2024-04-22_nrt
2024-04-22 11:42:35	ga_s2bm_ard_3-2-1_50KRF_2024-04-22_nrt
2024-04-22 11:42:49	ga_s2bm_ard_3-2-1_51KTV_2024-04-22_nrt
2024-04-22 11:42:50	ga_s2bm_ard_3-2-1_50KRE_2024-04-22_nrt
2024-04-22 11:47:30	ga_s2bm_ard_3-2-1_50HPF_2024-04-22_nrt
2024-04-22 11:47:32	ga_s2bm_ard_3-2-1_50HNF_2024-04-22_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