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
2023-02-01 11:21:29	ga_s2bm_ard_3-2-1_52LDJ_2023-02-01_final
2023-02-01 11:22:06	ga_s2bm_ard_3-2-1_51KZB_2023-02-01_final
2023-02-01 11:23:51	ga_s2bm_ard_3-2-1_51KYQ_2023-02-01_final
2023-02-01 11:26:37	ga_s2bm_ard_3-2-1_51HWD_2023-02-01_final
2023-02-02 10:52:41	ga_s2bm_ard_3-2-1_52KHD_2023-02-02_final
2023-02-02 10:54:55	ga_s2bm_ard_3-2-1_52JGQ_2023-02-02_final
2023-02-02 10:55:10	ga_s2bm_ard_3-2-1_52JGP_2023-02-02_final
2023-02-02 10:55:14	ga_s2bm_ard_3-2-1_52JFP_2023-02-02_final
2023-02-02 10:55:26	ga_s2bm_ard_3-2-1_52JFN_2023-02-02_final
2023-02-02 10:55:28	ga_s2bm_ard_3-2-1_52JEN_2023-02-02_final
2023-02-02 10:55:34	ga_s2bm_ard_3-2-1_52JEN_2023-02-02_final
2023-02-02 10:55:46	ga_s2bm_ard_3-2-1_52JEM_2023-02-02_final
2023-02-05 11:02:45	ga_s2bm_ard_3-2-1_52KFD_2023-02-05_final
2023-02-05 11:04:53	ga_s2bm_ard_3-2-1_52JCR_2023-02-05_final
2023-02-05 11:05:10	ga_s2bm_ard_3-2-1_52JFP_2023-02-05_final
2023-02-05 11:05:17	ga_s2bm_ard_3-2-1_52JDP_2023-02-05_final
2023-02-05 11:05:31	ga_s2bm_ard_3-2-1_52JDN_2023-02-05_final
2023-02-05 11:05:42	ga_s2bm_ard_3-2-1_52JEM_2023-02-05_final
2023-02-05 11:05:46	ga_s2bm_ard_3-2-1_52JDM_2023-02-05_final
2023-02-05 11:06:21	ga_s2bm_ard_3-2-1_52HBK_2023-02-05_final
2023-02-05 11:06:34	ga_s2bm_ard_3-2-1_51HYD_2023-02-05_final
2023-02-06 12:13:37	ga_s2bm_ard_3-2-1_50KKB_2023-02-06_final
2023-02-06 12:14:05	ga_s2bm_ard_3-2-1_50KKV_2023-02-06_final
2023-02-06 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2023-02-06_final
2023-02-06 12:14:10	ga_s2bm_ard_3-2-1_49KGQ_2023-02-06_final
2023-02-06 12:14:17	ga_s2bm_ard_3-2-1_50KKU_2023-02-06_final
2023-02-06 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2023-02-06_final
2023-02-06 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2023-02-06_final
2023-02-06 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2023-02-06_final
2023-02-06 12:14:57	ga_s2bm_ard_3-2-1_49JFM_2023-02-06_final
2023-02-06 12:15:18	ga_s2bm_ard_3-2-1_49JGK_2023-02-06_final
2023-02-07 11:41:31	ga_s2bm_ard_3-2-1_51LUE_2023-02-07_final
2023-02-07 11:42:07	ga_s2bm_ard_3-2-1_51KWB_2023-02-07_final
2023-02-07 11:42:19	ga_s2bm_ard_3-2-1_51KWA_2023-02-07_final
2023-02-07 11:43:01	ga_s2bm_ard_3-2-1_51KTU_2023-02-07_final
2023-02-07 11:43:27	ga_s2bm_ard_3-2-1_51KUS_2023-02-07_final
2023-02-07 11:43:34	ga_s2bm_ard_3-2-1_51KVR_2023-02-07_final
2023-02-07 11:43:45	ga_s2bm_ard_3-2-1_50KRA_2023-02-07_final
2023-02-07 11:43:49	ga_s2bm_ard_3-2-1_50KQA_2023-02-07_final
2023-02-07 11:44:21	ga_s2bm_ard_3-2-1_50KPU_2023-02-07_final
2023-02-07 11:44:29	ga_s2bm_ard_3-2-1_51JTN_2023-02-07_final
2023-02-07 11:44:32	ga_s2bm_ard_3-2-1_50JQT_2023-02-07_final
2023-02-07 11:44:36	ga_s2bm_ard_3-2-1_50JPT_2023-02-07_final
2023-02-07 11:44:43	ga_s2bm_ard_3-2-1_50JRS_2023-02-07_final
2023-02-07 11:44:47	ga_s2bm_ard_3-2-1_50JQS_2023-02-07_final
2023-02-07 11:44:50	ga_s2bm_ard_3-2-1_50JPS_2023-02-07_final
2023-02-07 11:44:58	ga_s2bm_ard_3-2-1_51JTL_2023-02-07_final
2023-02-07 11:45:16	ga_s2bm_ard_3-2-1_50JQQ_2023-02-07_final
2023-02-07 11:45:22	ga_s2bm_ard_3-2-1_50JNQ_2023-02-07_final
2023-02-07 11:45:34	ga_s2bm_ard_3-2-1_50JPP_2023-02-07_final
2023-02-07 11:45:41	ga_s2bm_ard_3-2-1_51JTH_2023-02-07_final
2023-02-07 11:45:52	ga_s2bm_ard_3-2-1_50JNN_2023-02-07_final
2023-02-07 11:45:55	ga_s2bm_ard_3-2-1_51JTG_2023-02-07_final
2023-02-07 11:45:59	ga_s2bm_ard_3-2-1_50JQM_2023-02-07_final
2023-02-07 11:46:03	ga_s2bm_ard_3-2-1_50JPM_2023-02-07_final
2023-02-07 11:46:06	ga_s2bm_ard_3-2-1_50JNM_2023-02-07_final
2023-02-07 11:46:13	ga_s2bm_ard_3-2-1_50JQL_2023-02-07_final
2023-02-07 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2023-02-07_final
2023-02-07 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2023-02-07_final
2023-02-07 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2023-02-07_final
2023-02-07 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2023-02-07_final
2023-02-07 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2023-02-07_final
2023-02-08 11:11:35	ga_s2bm_ard_3-2-1_52LDJ_2023-02-08_final
2023-02-08 11:11:43	ga_s2bm_ard_3-2-1_52LFH_2023-02-08_final
2023-02-08 11:12:27	ga_s2bm_ard_3-2-1_52KFE_2023-02-08_final
2023-02-08 11:12:36	ga_s2bm_ard_3-2-1_52KCE_2023-02-08_final
2023-02-08 11:12:40	ga_s2bm_ard_3-2-1_52KFD_2023-02-08_final
2023-02-08 11:12:46	ga_s2bm_ard_3-2-1_52KDD_2023-02-08_final
2023-02-08 11:12:47	ga_s2bm_ard_3-2-1_52KCD_2023-02-08_final
2023-02-08 11:12:54	ga_s2bm_ard_3-2-1_52KCD_2023-02-08_final
2023-02-08 11:13:12	ga_s2bm_ard_3-2-1_52KBC_2023-02-08_final
2023-02-08 11:13:17	ga_s2bm_ard_3-2-1_52KDB_2023-02-08_final
2023-02-08 11:13:24	ga_s2bm_ard_3-2-1_52KBB_2023-02-08_final
2023-02-08 11:14:07	ga_s2bm_ard_3-2-1_51KZP_2023-02-08_final
2023-02-08 11:14:21	ga_s2bm_ard_3-2-1_51JZN_2023-02-08_final
2023-02-08 11:14:27	ga_s2bm_ard_3-2-1_51JYN_2023-02-08_final
2023-02-08 11:14:36	ga_s2bm_ard_3-2-1_51JZM_2023-02-08_final
2023-02-08 11:14:48	ga_s2bm_ard_3-2-1_52JCR_2023-02-08_final
2023-02-08 11:15:02	ga_s2bm_ard_3-2-1_52JCQ_2023-02-08_final
2023-02-08 11:15:10	ga_s2bm_ard_3-2-1_52JDP_2023-02-08_final
2023-02-08 11:15:20	ga_s2bm_ard_3-2-1_52JBP_2023-02-08_final
2023-02-08 11:15:23	ga_s2bm_ard_3-2-1_51JYJ_2023-02-08_final
2023-02-08 11:15:28	ga_s2bm_ard_3-2-1_51JXJ_2023-02-08_final
2023-02-08 11:15:35	ga_s2bm_ard_3-2-1_52JBN_2023-02-08_final
2023-02-08 11:15:37	ga_s2bm_ard_3-2-1_51JYH_2023-02-08_final
2023-02-08 11:16:10	ga_s2bm_ard_3-2-1_51JXF_2023-02-08_final
2023-02-08 11:16:18	ga_s2bm_ard_3-2-1_52HBK_2023-02-08_final
2023-02-08 11:16:24	ga_s2bm_ard_3-2-1_51HXE_2023-02-08_final
2023-02-08 11:16:35	ga_s2bm_ard_3-2-1_51HYD_2023-02-08_final
2023-02-27 11:47:32	ga_s2bm_ard_3-2-1_50HNF_2023-02-27_nrt
2023-02-27 11:47:34	ga_s2bm_ard_3-2-1_50HMF_2023-02-27_nrt
2023-02-28 11:10:15	ga_s2bm_ard_3-2-1_52LGP_2023-02-28_nrt
2023-02-28 11:10:21	ga_s2bm_ard_3-2-1_52LEP_2023-02-28_nrt
2023-02-28 11:10:36	ga_s2bm_ard_3-2-1_52LEN_2023-02-28_nrt
2023-02-28 11:10:51	ga_s2bm_ard_3-2-1_52LEM_2023-02-28_nrt
2023-02-28 11:16:28	ga_s2bm_ard_3-2-1_52HCJ_2023-02-28_nrt
2023-02-28 11:16:35	ga_s2bm_ard_3-2-1_52HBJ_2023-02-28_nrt
2023-02-28 11:16:50	ga_s2bm_ard_3-2-1_52HBH_2023-02-28_nrt
2023-02-28 11:16:52	ga_s2bm_ard_3-2-1_51HYC_2023-02-28_nrt
2023-02-28 11:17:03	ga_s2bm_ard_3-2-1_52HBG_2023-02-28_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