Search ga_s2bm_ard_3 across 2023

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

First 100 results (query limit)

Time (local)	Label
2023-02-27 10:05:21	ga_s2bm_ard_3-2-1_55JBG_2023-02-27_final
2023-02-27 10:07:08	ga_s2bm_ard_3-2-1_54HXE_2023-02-27_final
2023-02-27 10:07:47	ga_s2bm_ard_3-2-1_54HUC_2023-02-27_nrt
2023-02-27 10:07:49	ga_s2bm_ard_3-2-1_54HXB_2023-02-27_nrt
2023-02-28 09:37:34	ga_s2bm_ard_3-2-1_55HET_2023-02-28_final
2023-02-28 09:37:39	ga_s2bm_ard_3-2-1_56HKB_2023-02-28_nrt
2023-02-28 09:37:40	ga_s2bm_ard_3-2-1_55HGS_2023-02-28_nrt
2023-02-28 09:37:41	ga_s2bm_ard_3-2-1_55HDT_2023-02-28_final
2023-02-28 09:37:44	ga_s2bm_ard_3-2-1_55HFS_2023-02-28_final
2023-02-28 09:37:48	ga_s2bm_ard_3-2-1_55HES_2023-02-28_final
2023-02-28 09:37:52	ga_s2bm_ard_3-2-1_55HDS_2023-02-28_final
2023-02-28 09:37:54	ga_s2bm_ard_3-2-1_56GKA_2023-02-28_nrt
2023-02-28 09:37:55	ga_s2bm_ard_3-2-1_55GGR_2023-02-28_nrt
2023-02-28 09:37:59	ga_s2bm_ard_3-2-1_55GFR_2023-02-28_final
2023-02-28 09:38:02	ga_s2bm_ard_3-2-1_55GER_2023-02-28_final
2023-02-28 09:38:06	ga_s2bm_ard_3-2-1_55GDR_2023-02-28_final
2023-02-28 09:38:08	ga_s2bm_ard_3-2-1_56GKV_2023-02-28_nrt
2023-02-28 09:38:09	ga_s2bm_ard_3-2-1_55GGQ_2023-02-28_nrt
2023-02-28 09:38:13	ga_s2bm_ard_3-2-1_55GFQ_2023-02-28_final
2023-02-28 09:38:17	ga_s2bm_ard_3-2-1_55GEQ_2023-02-28_final
2023-02-28 09:38:20	ga_s2bm_ard_3-2-1_55GGP_2023-02-28_nrt
2023-02-28 09:38:21	ga_s2bm_ard_3-2-1_55GDQ_2023-02-28_final
2023-02-28 09:38:21	ga_s2bm_ard_3-2-1_56GKU_2023-02-28_nrt
2023-02-28 09:38:27	ga_s2bm_ard_3-2-1_55GFP_2023-02-28_final
2023-02-28 09:38:31	ga_s2bm_ard_3-2-1_55GEP_2023-02-28_final
2023-02-28 09:38:35	ga_s2bm_ard_3-2-1_55GDP_2023-02-28_final
2023-02-28 09:38:41	ga_s2bm_ard_3-2-1_55GCP_2023-02-28_final
2023-02-28 09:38:42	ga_s2bm_ard_3-2-1_55GFN_2023-02-28_final
2023-02-28 09:38:46	ga_s2bm_ard_3-2-1_55GEN_2023-02-28_final
2023-02-28 09:38:50	ga_s2bm_ard_3-2-1_55GDN_2023-02-28_final
2023-02-28 09:38:53	ga_s2bm_ard_3-2-1_55GCN_2023-02-28_final
2023-02-28 09:38:56	ga_s2bm_ard_3-2-1_55GFM_2023-02-28_nrt
2023-02-28 09:39:00	ga_s2bm_ard_3-2-1_55GEM_2023-02-28_final
2023-02-28 09:39:03	ga_s2bm_ard_3-2-1_55GDM_2023-02-28_final
2023-02-28 11:10:05	ga_s2bm_ard_3-2-1_53LKJ_2023-02-28_final
2023-02-28 11:10:12	ga_s2bm_ard_3-2-1_52LHP_2023-02-28_nrt
2023-02-28 11:10:15	ga_s2bm_ard_3-2-1_52LGP_2023-02-28_nrt
2023-02-28 11:10:19	ga_s2bm_ard_3-2-1_52LFP_2023-02-28_nrt
2023-02-28 11:10:21	ga_s2bm_ard_3-2-1_52LEP_2023-02-28_nrt
2023-02-28 11:10:26	ga_s2bm_ard_3-2-1_52LHN_2023-02-28_final
2023-02-28 11:10:30	ga_s2bm_ard_3-2-1_52LGN_2023-02-28_final
2023-02-28 11:10:33	ga_s2bm_ard_3-2-1_52LFN_2023-02-28_final
2023-02-28 11:10:36	ga_s2bm_ard_3-2-1_52LEN_2023-02-28_nrt
2023-02-28 11:10:38	ga_s2bm_ard_3-2-1_52LHM_2023-02-28_final
2023-02-28 11:10:44	ga_s2bm_ard_3-2-1_52LGM_2023-02-28_final
2023-02-28 11:10:48	ga_s2bm_ard_3-2-1_52LFM_2023-02-28_final
2023-02-28 11:10:51	ga_s2bm_ard_3-2-1_52LEM_2023-02-28_nrt
2023-02-28 11:10:58	ga_s2bm_ard_3-2-1_52LDM_2023-02-28_nrt
2023-02-28 11:10:58	ga_s2bm_ard_3-2-1_52LGL_2023-02-28_final
2023-02-28 11:11:02	ga_s2bm_ard_3-2-1_52LFL_2023-02-28_final
2023-02-28 11:11:05	ga_s2bm_ard_3-2-1_52LEL_2023-02-28_final
2023-02-28 11:11:09	ga_s2bm_ard_3-2-1_52LDL_2023-02-28_nrt
2023-02-28 11:11:13	ga_s2bm_ard_3-2-1_52LGK_2023-02-28_final
2023-02-28 11:11:17	ga_s2bm_ard_3-2-1_52LFK_2023-02-28_final
2023-03-02 10:14:58	ga_s2bm_ard_3-2-1_54JWP_2023-03-02_final
2023-03-02 10:14:58	ga_s2bm_ard_3-2-1_54JYN_2023-03-02_final
2023-03-02 10:15:01	ga_s2bm_ard_3-2-1_54JVP_2023-03-02_final
2023-03-02 10:15:08	ga_s2bm_ard_3-2-1_54JUP_2023-03-02_final
2023-03-02 10:15:08	ga_s2bm_ard_3-2-1_54JXN_2023-03-02_final
2023-03-02 10:15:12	ga_s2bm_ard_3-2-1_54JWN_2023-03-02_final
2023-03-02 10:15:16	ga_s2bm_ard_3-2-1_54JVN_2023-03-02_final
2023-03-02 10:15:20	ga_s2bm_ard_3-2-1_54JUN_2023-03-02_final
2023-03-02 10:15:23	ga_s2bm_ard_3-2-1_54JXM_2023-03-02_final
2023-03-02 10:15:27	ga_s2bm_ard_3-2-1_54JWM_2023-03-02_final
2023-03-02 10:15:30	ga_s2bm_ard_3-2-1_54JVM_2023-03-02_final
2023-03-02 10:15:33	ga_s2bm_ard_3-2-1_54JUM_2023-03-02_final
2023-03-02 10:15:38	ga_s2bm_ard_3-2-1_54JXL_2023-03-02_final
2023-03-02 10:15:41	ga_s2bm_ard_3-2-1_54JWL_2023-03-02_final
2023-03-02 10:15:45	ga_s2bm_ard_3-2-1_54JVL_2023-03-02_final
2023-03-02 10:15:48	ga_s2bm_ard_3-2-1_54JUL_2023-03-02_final
2023-03-02 10:15:51	ga_s2bm_ard_3-2-1_54HXK_2023-03-02_final
2023-03-02 10:15:56	ga_s2bm_ard_3-2-1_54HWK_2023-03-02_final
2023-03-02 10:15:59	ga_s2bm_ard_3-2-1_54HVK_2023-03-02_final
2023-03-02 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2023-03-02_final
2023-03-02 10:16:03	ga_s2bm_ard_3-2-1_54HUK_2023-03-02_final
2023-03-02 10:16:10	ga_s2bm_ard_3-2-1_54HWJ_2023-03-02_final
2023-03-02 10:16:14	ga_s2bm_ard_3-2-1_54HVJ_2023-03-02_final
2023-03-02 10:16:17	ga_s2bm_ard_3-2-1_54HUJ_2023-03-02_final
2023-03-02 10:16:21	ga_s2bm_ard_3-2-1_54HTJ_2023-03-02_final
2023-03-02 10:16:25	ga_s2bm_ard_3-2-1_54HWH_2023-03-02_final
2023-03-02 10:16:28	ga_s2bm_ard_3-2-1_54HVH_2023-03-02_final
2023-03-02 10:16:32	ga_s2bm_ard_3-2-1_54HUH_2023-03-02_final
2023-03-02 10:16:35	ga_s2bm_ard_3-2-1_54HTH_2023-03-02_final
2023-03-02 10:16:39	ga_s2bm_ard_3-2-1_54HWG_2023-03-02_final
2023-03-02 10:16:43	ga_s2bm_ard_3-2-1_54HVG_2023-03-02_final
2023-03-02 10:16:46	ga_s2bm_ard_3-2-1_54HUG_2023-03-02_final
2023-03-02 10:16:49	ga_s2bm_ard_3-2-1_54HTG_2023-03-02_final
2023-03-02 10:16:53	ga_s2bm_ard_3-2-1_53HQB_2023-03-02_final
2023-03-02 10:16:53	ga_s2bm_ard_3-2-1_54HWF_2023-03-02_final
2023-03-02 10:16:57	ga_s2bm_ard_3-2-1_54HVF_2023-03-02_final
2023-03-02 10:17:01	ga_s2bm_ard_3-2-1_54HUF_2023-03-02_final
2023-03-02 10:17:04	ga_s2bm_ard_3-2-1_54HWE_2023-03-02_final
2023-03-02 10:17:04	ga_s2bm_ard_3-2-1_54HTF_2023-03-02_final
2023-03-02 10:17:05	ga_s2bm_ard_3-2-1_53HQA_2023-03-02_final
2023-03-02 10:17:12	ga_s2bm_ard_3-2-1_54HVE_2023-03-02_final
2023-03-02 10:17:15	ga_s2bm_ard_3-2-1_54HUE_2023-03-02_final
2023-03-02 10:17:26	ga_s2bm_ard_3-2-1_54HVD_2023-03-02_final
2023-03-02 10:17:30	ga_s2bm_ard_3-2-1_54HUD_2023-03-02_final
2023-03-02 10:17:33	ga_s2bm_ard_3-2-1_54HTD_2023-03-02_nrt
2023-03-02 10:17:34	ga_s2bm_ard_3-2-1_53HQU_2023-03-02_nrt

Return to ga_s2bm_ard_3 across 2023 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

2023

All months