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

84 results

Time (local)	Label
2024-04-22 09:59:47	ga_s2bm_ard_3-2-1_55LFJ_2024-04-22_nrt
2024-04-22 09:59:51	ga_s2bm_ard_3-2-1_55LEJ_2024-04-22_nrt
2024-04-22 10:00:02	ga_s2bm_ard_3-2-1_55LFH_2024-04-22_nrt
2024-04-22 10:00:19	ga_s2bm_ard_3-2-1_55LEG_2024-04-22_nrt
2024-04-22 10:00:31	ga_s2bm_ard_3-2-1_55LFF_2024-04-22_nrt
2024-04-22 10:00:45	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 10:01:21	ga_s2bm_ard_3-2-1_55LDC_2024-04-22_nrt
2024-04-22 10:03:21	ga_s2bm_ard_3-2-1_55KCQ_2024-04-22_nrt
2024-04-22 10:03:38	ga_s2bm_ard_3-2-1_55KBP_2024-04-22_nrt
2024-04-22 10:07:45	ga_s2bm_ard_3-2-1_54HUC_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 11:40:35	ga_s2bm_ard_3-2-1_51LUJ_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 11:40:49	ga_s2bm_ard_3-2-1_51LUH_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 11:41:07	ga_s2bm_ard_3-2-1_51LXF_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 11:41:44	ga_s2bm_ard_3-2-1_51LVD_2024-04-22_nrt
2024-04-22 11:41:50	ga_s2bm_ard_3-2-1_51LTD_2024-04-22_nrt
2024-04-22 11:42:05	ga_s2bm_ard_3-2-1_51LTC_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
2024-04-22 11:47:34	ga_s2bm_ard_3-2-1_50HLF_2024-04-22_nrt
2024-04-23 09:29:40	ga_s2bm_ard_3-2-1_56LPP_2024-04-22_nrt
2024-04-23 09:29:54	ga_s2bm_ard_3-2-1_56LPN_2024-04-22_nrt
2024-04-23 09:30:04	ga_s2bm_ard_3-2-1_56LPM_2024-04-23_nrt
2024-04-23 09:31:26	ga_s2bm_ard_3-2-1_56KPG_2024-04-23_nrt
2024-04-23 09:31:27	ga_s2bm_ard_3-2-1_56KNG_2024-04-23_nrt
2024-04-23 09:31:30	ga_s2bm_ard_3-2-1_56KPF_2024-04-23_nrt
2024-04-23 09:31:31	ga_s2bm_ard_3-2-1_56KNF_2024-04-23_nrt
2024-04-23 09:32:28	ga_s2bm_ard_3-2-1_56KNC_2024-04-23_nrt
2024-04-23 09:32:30	ga_s2bm_ard_3-2-1_56KMC_2024-04-23_nrt
2024-04-23 09:32:48	ga_s2bm_ard_3-2-1_56KPA_2024-04-23_nrt
2024-04-23 09:33:03	ga_s2bm_ard_3-2-1_56KPV_2024-04-23_nrt
2024-04-23 09:33:06	ga_s2bm_ard_3-2-1_56KNV_2024-04-23_nrt
2024-04-23 09:33:10	ga_s2bm_ard_3-2-1_56KMV_2024-04-23_nrt
2024-04-23 09:33:17	ga_s2bm_ard_3-2-1_56KPU_2024-04-23_nrt
2024-04-23 09:33:21	ga_s2bm_ard_3-2-1_56KNU_2024-04-23_nrt
2024-04-23 09:33:30	ga_s2bm_ard_3-2-1_56JPT_2024-04-23_nrt
2024-04-23 09:33:40	ga_s2bm_ard_3-2-1_56JPS_2024-04-23_nrt
2024-04-23 09:35:58	ga_s2bm_ard_3-2-1_56HMH_2024-04-23_nrt
2024-04-23 09:36:37	ga_s2bm_ard_3-2-1_56HLF_2024-04-23_nrt
2024-04-23 09:36:51	ga_s2bm_ard_3-2-1_56HLE_2024-04-23_nrt
2024-04-23 09:36:55	ga_s2bm_ard_3-2-1_56HKE_2024-04-23_nrt
2024-04-23 09:37:03	ga_s2bm_ard_3-2-1_56HLD_2024-04-23_nrt
2024-04-23 09:37:09	ga_s2bm_ard_3-2-1_56HKD_2024-04-23_nrt
2024-04-23 09:37:24	ga_s2bm_ard_3-2-1_56HKC_2024-04-23_nrt
2024-04-23 09:37:25	ga_s2bm_ard_3-2-1_55HGT_2024-04-23_nrt
2024-04-23 09:37:38	ga_s2bm_ard_3-2-1_56HKB_2024-04-23_nrt
2024-04-23 09:37:39	ga_s2bm_ard_3-2-1_55HGS_2024-04-23_nrt
2024-04-23 09:37:53	ga_s2bm_ard_3-2-1_56GKA_2024-04-23_nrt
2024-04-23 09:37:54	ga_s2bm_ard_3-2-1_55GGR_2024-04-23_nrt
2024-04-23 09:38:07	ga_s2bm_ard_3-2-1_56GKV_2024-04-23_nrt
2024-04-23 09:38:08	ga_s2bm_ard_3-2-1_55GGQ_2024-04-23_nrt
2024-04-23 09:38:19	ga_s2bm_ard_3-2-1_55GGP_2024-04-23_nrt
2024-04-23 09:38:20	ga_s2bm_ard_3-2-1_56GKU_2024-04-23_nrt
2024-04-23 09:38:55	ga_s2bm_ard_3-2-1_55GFM_2024-04-23_nrt
2024-04-23 11:10:11	ga_s2bm_ard_3-2-1_52LHP_2024-04-23_nrt
2024-04-23 11:10:17	ga_s2bm_ard_3-2-1_52LFP_2024-04-23_nrt
2024-04-23 11:10:20	ga_s2bm_ard_3-2-1_52LEP_2024-04-23_nrt
2024-04-23 11:10:50	ga_s2bm_ard_3-2-1_52LEM_2024-04-23_nrt
2024-04-23 11:10:57	ga_s2bm_ard_3-2-1_52LDM_2024-04-23_nrt
2024-04-23 11:11:08	ga_s2bm_ard_3-2-1_52LDL_2024-04-23_nrt
2024-04-23 11:11:22	ga_s2bm_ard_3-2-1_52LDK_2024-04-23_nrt
2024-04-23 11:16:27	ga_s2bm_ard_3-2-1_52HCJ_2024-04-23_nrt
2024-04-23 11:16:51	ga_s2bm_ard_3-2-1_51HYC_2024-04-23_nrt
2024-04-23 11:17:01	ga_s2bm_ard_3-2-1_52HBG_2024-04-23_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