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
2023-09-21 10:19:41	ga_s2bm_ard_3-2-1_54LZQ_2023-09-21_final
2023-09-21 10:20:02	ga_s2bm_ard_3-2-1_54LXP_2023-09-21_final
2023-09-21 10:20:17	ga_s2bm_ard_3-2-1_54LXN_2023-09-21_final
2023-09-21 10:20:28	ga_s2bm_ard_3-2-1_54LYM_2023-09-21_final
2023-09-21 10:20:43	ga_s2bm_ard_3-2-1_54LYL_2023-09-21_final
2023-09-21 10:21:04	ga_s2bm_ard_3-2-1_54LZJ_2023-09-21_final
2023-09-21 10:21:33	ga_s2bm_ard_3-2-1_54LWH_2023-09-21_final
2023-09-21 10:21:44	ga_s2bm_ard_3-2-1_54KXG_2023-09-21_final
2023-09-21 10:21:59	ga_s2bm_ard_3-2-1_54KXF_2023-09-21_final
2023-09-21 10:22:20	ga_s2bm_ard_3-2-1_54KVE_2023-09-21_final
2023-09-21 10:22:34	ga_s2bm_ard_3-2-1_54KVD_2023-09-21_final
2023-09-21 10:22:46	ga_s2bm_ard_3-2-1_54KWC_2023-09-21_final
2023-09-21 10:22:52	ga_s2bm_ard_3-2-1_54KUC_2023-09-21_final
2023-09-21 10:23:00	ga_s2bm_ard_3-2-1_54KWB_2023-09-21_final
2023-09-21 10:23:10	ga_s2bm_ard_3-2-1_54KXA_2023-09-21_final
2023-09-21 10:23:29	ga_s2bm_ard_3-2-1_54KWV_2023-09-21_final
2023-09-21 10:23:53	ga_s2bm_ard_3-2-1_54KTU_2023-09-21_final
2023-09-21 10:24:02	ga_s2bm_ard_3-2-1_54JVT_2023-09-21_final
2023-09-21 10:24:16	ga_s2bm_ard_3-2-1_54JVS_2023-09-21_final
2023-09-21 10:24:20	ga_s2bm_ard_3-2-1_54JWS_2023-09-21_final
2023-09-21 10:24:22	ga_s2bm_ard_3-2-1_54JVS_2023-09-21_final
2023-09-21 10:24:52	ga_s2bm_ard_3-2-1_54JTQ_2023-09-21_final
2023-09-21 10:25:18	ga_s2bm_ard_3-2-1_54JUN_2023-09-21_final
2023-09-21 10:25:32	ga_s2bm_ard_3-2-1_54JUM_2023-09-21_final
2023-09-21 10:25:38	ga_s2bm_ard_3-2-1_53JQG_2023-09-21_final
2023-09-21 10:25:52	ga_s2bm_ard_3-2-1_53JQF_2023-09-21_final
2023-09-21 10:26:16	ga_s2bm_ard_3-2-1_54HUJ_2023-09-21_final
2023-09-21 10:26:30	ga_s2bm_ard_3-2-1_54HUH_2023-09-21_final
2023-09-21 10:26:36	ga_s2bm_ard_3-2-1_53HQC_2023-09-21_final
2023-09-21 10:26:40	ga_s2bm_ard_3-2-1_53HPC_2023-09-21_final
2023-09-21 10:26:50	ga_s2bm_ard_3-2-1_53HQB_2023-09-21_final
2023-09-21 10:26:54	ga_s2bm_ard_3-2-1_53HPB_2023-09-21_final
2023-09-21 10:27:03	ga_s2bm_ard_3-2-1_54HTF_2023-09-21_final
2023-09-21 10:27:16	ga_s2bm_ard_3-2-1_54HTE_2023-09-21_final
2023-09-21 12:04:14	ga_s2bm_ard_3-2-1_50KLV_2023-09-21_final
2023-09-21 12:04:17	ga_s2bm_ard_3-2-1_49KHQ_2023-09-21_final
2023-09-21 12:04:24	ga_s2bm_ard_3-2-1_50KMU_2023-09-21_final
2023-09-21 12:04:31	ga_s2bm_ard_3-2-1_50KMU_2023-09-21_final
2023-09-21 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2023-09-21_final
2023-09-21 12:04:39	ga_s2bm_ard_3-2-1_50JMT_2023-09-21_final
2023-09-21 12:05:26	ga_s2bm_ard_3-2-1_50JLQ_2023-09-21_final
2023-09-21 12:05:41	ga_s2bm_ard_3-2-1_50JLP_2023-09-21_final
2023-09-21 12:05:44	ga_s2bm_ard_3-2-1_50JKP_2023-09-21_final
2023-09-21 12:05:47	ga_s2bm_ard_3-2-1_49JGJ_2023-09-21_final
2023-09-21 12:05:59	ga_s2bm_ard_3-2-1_50JKN_2023-09-21_final
2023-09-21 12:06:02	ga_s2bm_ard_3-2-1_49JGH_2023-09-21_final
2023-09-22 09:52:53	ga_s2bm_ard_3-2-1_55KES_2023-09-22_final
2023-09-22 09:53:11	ga_s2bm_ard_3-2-1_55KDR_2023-09-22_final
2023-09-22 09:54:01	ga_s2bm_ard_3-2-1_55JCN_2023-09-22_final
2023-09-22 09:54:13	ga_s2bm_ard_3-2-1_55JCM_2023-09-22_final
2023-09-22 09:54:16	ga_s2bm_ard_3-2-1_55JFL_2023-09-22_final
2023-09-22 09:54:23	ga_s2bm_ard_3-2-1_55JDL_2023-09-22_final
2023-09-22 09:54:35	ga_s2bm_ard_3-2-1_55JEK_2023-09-22_final
2023-09-22 09:54:49	ga_s2bm_ard_3-2-1_55JEJ_2023-09-22_final
2023-09-22 09:55:14	ga_s2bm_ard_3-2-1_55JBH_2023-09-22_final
2023-09-22 09:55:25	ga_s2bm_ard_3-2-1_55JCG_2023-09-22_final
2023-09-22 09:55:57	ga_s2bm_ard_3-2-1_55HBE_2023-09-22_final
2023-09-22 09:55:57	ga_s2bm_ard_3-2-1_55HED_2023-09-22_final
2023-09-22 09:56:00	ga_s2bm_ard_3-2-1_54HYK_2023-09-22_final
2023-09-22 09:56:38	ga_s2bm_ard_3-2-1_55HCB_2023-09-22_final
2023-09-22 09:57:11	ga_s2bm_ard_3-2-1_54HYE_2023-09-22_final
2023-09-22 09:57:30	ga_s2bm_ard_3-2-1_54HXD_2023-09-22_final
2023-09-22 09:57:36	ga_s2bm_ard_3-2-1_55HCT_2023-09-22_final
2023-09-22 09:58:04	ga_s2bm_ard_3-2-1_55GCR_2023-09-22_final
2023-09-22 09:58:17	ga_s2bm_ard_3-2-1_55GCQ_2023-09-22_final
2023-09-22 09:58:20	ga_s2bm_ard_3-2-1_55GBQ_2023-09-22_final
2023-09-22 09:58:23	ga_s2bm_ard_3-2-1_55GCQ_2023-09-22_final
2023-09-22 11:31:21	ga_s2bm_ard_3-2-1_52LBK_2023-09-22_final
2023-09-22 11:32:40	ga_s2bm_ard_3-2-1_51KYV_2023-09-22_final
2023-09-22 11:33:27	ga_s2bm_ard_3-2-1_51KXS_2023-09-22_final
2023-09-22 11:33:42	ga_s2bm_ard_3-2-1_51KXR_2023-09-22_final
2023-09-22 11:34:21	ga_s2bm_ard_3-2-1_51KUP_2023-09-22_final
2023-09-22 11:34:39	ga_s2bm_ard_3-2-1_51JTN_2023-09-22_final
2023-09-22 11:34:43	ga_s2bm_ard_3-2-1_51JWM_2023-09-22_final
2023-09-22 11:34:47	ga_s2bm_ard_3-2-1_51JVM_2023-09-22_final
2023-09-22 11:34:58	ga_s2bm_ard_3-2-1_51JWL_2023-09-22_final
2023-09-22 11:35:01	ga_s2bm_ard_3-2-1_51JVL_2023-09-22_final
2023-09-22 11:35:40	ga_s2bm_ard_3-2-1_50JQP_2023-09-22_final
2023-09-22 11:35:54	ga_s2bm_ard_3-2-1_50JQN_2023-09-22_final
2023-09-22 11:36:00	ga_s2bm_ard_3-2-1_51JVG_2023-09-22_final
2023-09-22 11:36:14	ga_s2bm_ard_3-2-1_51JVF_2023-09-22_final
2023-09-22 11:36:32	ga_s2bm_ard_3-2-1_51HUE_2023-09-22_final
2023-09-22 11:37:30	ga_s2bm_ard_3-2-1_50HNG_2023-09-22_final
2023-09-23 09:28:41	ga_s2bm_ard_3-2-1_55GEP_2023-09-22_final
2023-10-01 12:00:53	ga_s2bm_ard_3-2-1_50LPN_2023-10-01_nrt
2023-10-01 12:01:08	ga_s2bm_ard_3-2-1_50LPM_2023-10-01_nrt
2023-10-01 12:01:18	ga_s2bm_ard_3-2-1_50LQL_2023-10-01_nrt
2023-10-01 12:01:22	ga_s2bm_ard_3-2-1_50LPL_2023-10-01_nrt
2023-10-01 12:01:28	ga_s2bm_ard_3-2-1_50LQK_2023-10-01_nrt
2023-10-01 12:02:59	ga_s2bm_ard_3-2-1_50KME_2023-10-01_nrt
2023-10-01 12:03:00	ga_s2bm_ard_3-2-1_50KLE_2023-10-01_nrt
2023-10-01 12:05:21	ga_s2bm_ard_3-2-1_49JFL_2023-10-01_nrt
2023-10-01 12:05:34	ga_s2bm_ard_3-2-1_49JFK_2023-10-01_nrt
2023-10-01 12:05:49	ga_s2bm_ard_3-2-1_49JFJ_2023-10-01_nrt
2023-10-01 12:06:04	ga_s2bm_ard_3-2-1_49JFH_2023-10-01_nrt
2023-10-01 12:06:15	ga_s2bm_ard_3-2-1_49JGG_2023-10-01_nrt
2023-10-01 12:06:18	ga_s2bm_ard_3-2-1_49JFG_2023-10-01_nrt
2023-10-02 11:30:22	ga_s2bm_ard_3-2-1_52LBP_2023-10-02_nrt
2023-10-02 11:30:52	ga_s2bm_ard_3-2-1_52LBM_2023-10-02_nrt
2023-10-02 11:31:06	ga_s2bm_ard_3-2-1_52LBL_2023-10-02_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