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

First 100 results (query limit)

Time (local)	Label
2023-02-11 09:43:29	ga_s2bm_ard_3-2-1_55KGP_2023-02-11_final
2023-02-11 09:45:24	ga_s2bm_ard_3-2-1_55JGF_2023-02-11_final
2023-02-11 09:47:20	ga_s2bm_ard_3-2-1_55HCU_2023-02-11_final
2023-02-11 09:48:15	ga_s2bm_ard_3-2-1_55GDQ_2023-02-11_final
2023-02-11 11:23:41	ga_s2bm_ard_3-2-1_51KXR_2023-02-11_final
2023-02-11 11:26:04	ga_s2bm_ard_3-2-1_51JUG_2023-02-11_final
2023-02-12 10:52:29	ga_s2bm_ard_3-2-1_52KHE_2023-02-12_final
2023-02-12 10:52:57	ga_s2bm_ard_3-2-1_53KKT_2023-02-12_final
2023-02-12 10:53:56	ga_s2bm_ard_3-2-1_53KKP_2023-02-12_final
2023-02-12 10:54:38	ga_s2bm_ard_3-2-1_53JLL_2023-02-12_final
2023-02-13 10:25:19	ga_s2bm_ard_3-2-1_53JQH_2023-02-13_final
2023-02-13 10:26:34	ga_s2bm_ard_3-2-1_53HPC_2023-02-13_final
2023-02-13 12:03:33	ga_s2bm_ard_3-2-1_50KNB_2023-02-13_final
2023-02-13 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2023-02-13_final
2023-02-14 09:55:45	ga_s2bm_ard_3-2-1_55HDE_2023-02-14_final
2023-02-14 09:58:12	ga_s2bm_ard_3-2-1_55GCQ_2023-02-14_final
2023-02-14 11:31:29	ga_s2bm_ard_3-2-1_51LWE_2023-02-14_final
2023-02-14 11:33:14	ga_s2bm_ard_3-2-1_51KVT_2023-02-14_final
2023-02-14 11:33:55	ga_s2bm_ard_3-2-1_51KWQ_2023-02-14_final
2023-02-14 11:34:09	ga_s2bm_ard_3-2-1_51KWP_2023-02-14_final
2023-02-14 11:34:30	ga_s2bm_ard_3-2-1_51JUN_2023-02-14_final
2023-02-14 11:34:45	ga_s2bm_ard_3-2-1_51JUM_2023-02-14_final
2023-02-14 11:35:43	ga_s2bm_ard_3-2-1_51JUH_2023-02-14_final
2023-02-14 11:35:54	ga_s2bm_ard_3-2-1_51JVG_2023-02-14_final
2023-02-14 11:36:41	ga_s2bm_ard_3-2-1_51HUD_2023-02-14_final
2023-02-14 11:36:45	ga_s2bm_ard_3-2-1_51HTD_2023-02-14_final
2023-02-15 09:26:30	ga_s2bm_ard_3-2-1_56HKG_2023-02-14_final
2023-02-15 11:00:53	ga_s2bm_ard_3-2-1_53LLF_2023-02-15_final
2023-02-15 11:01:26	ga_s2bm_ard_3-2-1_52LHJ_2023-02-15_final
2023-02-15 11:03:12	ga_s2bm_ard_3-2-1_52KEB_2023-02-15_final
2023-02-15 11:04:02	ga_s2bm_ard_3-2-1_52KEU_2023-02-15_final
2023-02-15 11:04:31	ga_s2bm_ard_3-2-1_52JES_2023-02-15_final
2023-02-15 11:04:34	ga_s2bm_ard_3-2-1_52JGR_2023-02-15_final
2023-02-16 10:34:12	ga_s2bm_ard_3-2-1_54JTS_2023-02-16_final
2023-02-16 10:34:49	ga_s2bm_ard_3-2-1_53JPK_2023-02-16_final
2023-02-16 10:36:44	ga_s2bm_ard_3-2-1_53HPB_2023-02-16_final
2023-02-17 10:01:33	ga_s2bm_ard_3-2-1_55KDB_2023-02-17_final
2023-02-17 10:03:29	ga_s2bm_ard_3-2-1_55KDP_2023-02-17_final
2023-02-17 10:03:48	ga_s2bm_ard_3-2-1_55JCN_2023-02-17_final
2023-02-17 10:04:25	ga_s2bm_ard_3-2-1_54JYR_2023-02-17_final
2023-02-17 10:07:06	ga_s2bm_ard_3-2-1_54HXE_2023-02-17_final
2023-02-17 11:44:18	ga_s2bm_ard_3-2-1_50KQU_2023-02-17_final
2023-02-17 11:46:06	ga_s2bm_ard_3-2-1_50JNM_2023-02-17_final
2023-02-17 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2023-02-17_final
2023-02-18 09:32:45	ga_s2bm_ard_3-2-1_56KLB_2023-02-18_final
2023-02-18 09:33:59	ga_s2bm_ard_3-2-1_56JKS_2023-02-18_final
2023-02-18 11:13:13	ga_s2bm_ard_3-2-1_52KEB_2023-02-18_final
2023-02-18 11:13:53	ga_s2bm_ard_3-2-1_52KBV_2023-02-18_final
2023-02-18 11:15:02	ga_s2bm_ard_3-2-1_52JCQ_2023-02-18_final
2023-02-18 11:15:31	ga_s2bm_ard_3-2-1_52JCN_2023-02-18_final
2023-02-18 11:15:56	ga_s2bm_ard_3-2-1_51JXG_2023-02-18_final
2023-02-19 10:43:21	ga_s2bm_ard_3-2-1_53KNR_2023-02-19_final
2023-02-19 10:43:54	ga_s2bm_ard_3-2-1_53KMP_2023-02-19_final
2023-02-20 10:12:21	ga_s2bm_ard_3-2-1_54KZD_2023-02-20_final
2023-02-20 11:54:07	ga_s2bm_ard_3-2-1_50KNV_2023-02-20_final
2023-02-20 11:54:57	ga_s2bm_ard_3-2-1_50JLS_2023-02-20_final
2023-02-20 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2023-02-20_final
2023-02-20 11:55:48	ga_s2bm_ard_3-2-1_50JNN_2023-02-20_final
2023-02-20 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2023-02-20_final
2023-02-21 09:44:05	ga_s2bm_ard_3-2-1_56JLR_2023-02-21_final
2023-02-21 09:46:16	ga_s2bm_ard_3-2-1_55HEC_2023-02-21_final
2023-02-21 09:46:31	ga_s2bm_ard_3-2-1_55HEB_2023-02-21_final
2023-02-21 09:46:41	ga_s2bm_ard_3-2-1_55HFA_2023-02-21_final
2023-02-21 09:47:21	ga_s2bm_ard_3-2-1_55HCU_2023-02-21_final
2023-02-21 09:48:19	ga_s2bm_ard_3-2-1_55GCQ_2023-02-21_final
2023-02-21 11:22:11	ga_s2bm_ard_3-2-1_51KYB_2023-02-21_final
2023-02-21 11:23:21	ga_s2bm_ard_3-2-1_51KZS_2023-02-21_final
2023-02-21 11:23:27	ga_s2bm_ard_3-2-1_52KCA_2023-02-21_final
2023-02-21 11:23:27	ga_s2bm_ard_3-2-1_51KXS_2023-02-21_final
2023-02-21 11:23:35	ga_s2bm_ard_3-2-1_51KZR_2023-02-21_final
2023-02-21 11:24:18	ga_s2bm_ard_3-2-1_51JZN_2023-02-21_final
2023-02-21 11:25:20	ga_s2bm_ard_3-2-1_51JYJ_2023-02-21_final
2023-02-21 11:25:38	ga_s2bm_ard_3-2-1_51JXH_2023-02-21_final
2023-02-21 11:26:17	ga_s2bm_ard_3-2-1_51JUF_2023-02-21_final
2023-02-22 10:54:21	ga_s2bm_ard_3-2-1_52JFT_2023-02-22_final
2023-02-22 10:56:03	ga_s2bm_ard_3-2-1_52JEL_2023-02-22_final
2023-03-08 12:13:35	ga_s2bm_ard_3-2-1_49KGT_2023-03-08_nrt
2023-03-09 09:59:47	ga_s2bm_ard_3-2-1_55LGJ_2023-03-09_nrt
2023-03-09 10:00:02	ga_s2bm_ard_3-2-1_55LGH_2023-03-09_nrt
2023-03-09 10:00:09	ga_s2bm_ard_3-2-1_55LEH_2023-03-09_nrt
2023-03-09 10:00:16	ga_s2bm_ard_3-2-1_55LGG_2023-03-09_nrt
2023-03-09 10:00:23	ga_s2bm_ard_3-2-1_55LEG_2023-03-09_nrt
2023-03-09 10:00:31	ga_s2bm_ard_3-2-1_55LGF_2023-03-09_nrt
2023-03-09 10:00:38	ga_s2bm_ard_3-2-1_55LEF_2023-03-09_nrt
2023-03-09 10:00:44	ga_s2bm_ard_3-2-1_55LGE_2023-03-09_nrt
2023-03-09 10:00:52	ga_s2bm_ard_3-2-1_55LEE_2023-03-09_nrt
2023-03-09 10:01:07	ga_s2bm_ard_3-2-1_55LED_2023-03-09_nrt
2023-03-09 10:07:50	ga_s2bm_ard_3-2-1_54HUC_2023-03-09_nrt
2023-03-09 10:07:52	ga_s2bm_ard_3-2-1_54HXB_2023-03-09_nrt
2023-03-09 10:07:53	ga_s2bm_ard_3-2-1_54HWB_2023-03-09_nrt
2023-03-09 10:07:55	ga_s2bm_ard_3-2-1_54HVB_2023-03-09_nrt
2023-03-09 10:07:55	ga_s2bm_ard_3-2-1_54HUB_2023-03-09_nrt
2023-03-09 11:40:35	ga_s2bm_ard_3-2-1_51LVJ_2023-03-09_nrt
2023-03-09 11:40:50	ga_s2bm_ard_3-2-1_51LVH_2023-03-09_nrt
2023-03-09 11:41:15	ga_s2bm_ard_3-2-1_51LWF_2023-03-09_nrt
2023-03-09 11:42:11	ga_s2bm_ard_3-2-1_50LRH_2023-03-09_nrt
2023-03-09 11:42:24	ga_s2bm_ard_3-2-1_50KRG_2023-03-09_nrt
2023-03-09 11:42:52	ga_s2bm_ard_3-2-1_51KTV_2023-03-09_nrt
2023-03-09 11:42:53	ga_s2bm_ard_3-2-1_50KRE_2023-03-09_nrt
2023-03-09 11:47:34	ga_s2bm_ard_3-2-1_50HNF_2023-03-09_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