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
2019-07-29 09:35:29	ga_s2bm_ard_3-2-1_56JML_2019-07-29_final.stac-item
2019-07-29 09:35:32	ga_s2bm_ard_3-2-1_56JLL_2019-07-29_final.stac-item
2019-07-29 09:35:36	ga_s2bm_ard_3-2-1_56JKL_2019-07-29_final.stac-item
2019-07-29 09:35:38	ga_s2bm_ard_3-2-1_55JGF_2019-07-29_final.stac-item
2019-07-29 09:35:43	ga_s2bm_ard_3-2-1_56HMK_2019-07-29_final.stac-item
2019-07-29 09:35:47	ga_s2bm_ard_3-2-1_56HLK_2019-07-29_final.stac-item
2019-07-29 09:35:50	ga_s2bm_ard_3-2-1_56HKK_2019-07-29_final.stac-item
2019-07-29 09:35:52	ga_s2bm_ard_3-2-1_55HGE_2019-07-29_final.stac-item
2019-08-07 11:46:23	ga_s2bm_ard_3-2-1_50JQL_2019-08-07_final.stac-item
2019-08-07 11:46:26	ga_s2bm_ard_3-2-1_50JPL_2019-08-07_final.stac-item
2019-08-07 11:46:30	ga_s2bm_ard_3-2-1_50JNL_2019-08-07_final.stac-item
2019-08-07 11:46:33	ga_s2bm_ard_3-2-1_50JML_2019-08-07_final.stac-item
2019-08-07 11:46:37	ga_s2bm_ard_3-2-1_50HQK_2019-08-07_final.stac-item
2019-08-07 11:46:41	ga_s2bm_ard_3-2-1_50HPK_2019-08-07_final.stac-item
2019-08-07 11:46:45	ga_s2bm_ard_3-2-1_50HNK_2019-08-07_final.stac-item
2019-08-07 11:46:48	ga_s2bm_ard_3-2-1_50HMK_2019-08-07_final.stac-item
2019-08-11 09:45:29	ga_s2bm_ard_3-2-1_56JKL_2019-08-11_final.stac-item
2019-08-11 09:45:32	ga_s2bm_ard_3-2-1_55JGF_2019-08-11_final.stac-item
2019-08-11 09:45:36	ga_s2bm_ard_3-2-1_55JFF_2019-08-11_final.stac-item
2019-08-11 09:45:39	ga_s2bm_ard_3-2-1_56HKK_2019-08-11_final.stac-item
2019-08-11 09:45:40	ga_s2bm_ard_3-2-1_55JEF_2019-08-11_final.stac-item
2019-08-11 09:45:44	ga_s2bm_ard_3-2-1_55JDF_2019-08-11_final.stac-item
2019-08-11 09:45:47	ga_s2bm_ard_3-2-1_55HGE_2019-08-11_final.stac-item
2019-08-11 09:45:51	ga_s2bm_ard_3-2-1_55HFE_2019-08-11_final.stac-item
2019-08-11 09:45:54	ga_s2bm_ard_3-2-1_55HEE_2019-08-11_final.stac-item
2019-08-11 09:45:58	ga_s2bm_ard_3-2-1_55HDE_2019-08-11_final.stac-item
2019-08-15 11:06:06	ga_s2bm_ard_3-2-1_52JEL_2019-08-15_final.stac-item
2019-08-15 11:06:09	ga_s2bm_ard_3-2-1_52JDL_2019-08-15_final.stac-item
2019-08-15 11:06:13	ga_s2bm_ard_3-2-1_52JCL_2019-08-15_final.stac-item
2019-08-15 11:06:16	ga_s2bm_ard_3-2-1_52JBL_2019-08-15_final.stac-item
2019-08-15 11:06:30	ga_s2bm_ard_3-2-1_52HBK_2019-08-15_final.stac-item
2019-08-16 10:35:51	ga_s2bm_ard_3-2-1_53JQF_2019-08-16_final.stac-item
2019-08-16 10:35:55	ga_s2bm_ard_3-2-1_53JPF_2019-08-16_final.stac-item
2019-08-16 10:35:58	ga_s2bm_ard_3-2-1_53JNF_2019-08-16_final.stac-item
2019-08-16 10:36:02	ga_s2bm_ard_3-2-1_53JMF_2019-08-16_final.stac-item
2019-08-16 10:36:03	ga_s2bm_ard_3-2-1_53HQE_2019-08-16_final.stac-item
2019-08-16 10:36:09	ga_s2bm_ard_3-2-1_53HPE_2019-08-16_final.stac-item
2019-08-16 10:36:13	ga_s2bm_ard_3-2-1_53HNE_2019-08-16_final.stac-item
2019-08-16 10:36:16	ga_s2bm_ard_3-2-1_53HME_2019-08-16_final.stac-item
2019-08-23 10:25:48	ga_s2bm_ard_3-2-1_54JUL_2019-08-23_final.stac-item
2019-08-23 10:25:52	ga_s2bm_ard_3-2-1_54JTL_2019-08-23_final.stac-item
2019-08-23 10:25:54	ga_s2bm_ard_3-2-1_53JQF_2019-08-23_final.stac-item
2019-08-23 10:25:57	ga_s2bm_ard_3-2-1_53JPF_2019-08-23_final.stac-item
2019-08-23 10:26:03	ga_s2bm_ard_3-2-1_54HUK_2019-08-23_final.stac-item
2019-08-23 10:26:06	ga_s2bm_ard_3-2-1_54HTK_2019-08-23_final.stac-item
2022-06-19 09:55:40	ga_s2bm_ard_3-2-1_55JCF_2022-06-19_final.stac-item
2022-06-19 09:55:43	ga_s2bm_ard_3-2-1_55JBF_2022-06-19_final.stac-item
2022-06-19 09:55:47	ga_s2bm_ard_3-2-1_55HEE_2022-06-19_final.stac-item
2022-06-19 09:55:51	ga_s2bm_ard_3-2-1_55HDE_2022-06-19_final.stac-item
2022-06-19 09:55:55	ga_s2bm_ard_3-2-1_55HCE_2022-06-19_final.stac-item
2022-06-19 09:55:58	ga_s2bm_ard_3-2-1_55HBE_2022-06-19_final.stac-item
2022-06-19 09:56:01	ga_s2bm_ard_3-2-1_54HYK_2022-06-19_final.stac-item
2022-06-29 09:55:38	ga_s2bm_ard_3-2-1_55JDF_2022-06-29_final.stac-item
2022-06-29 09:55:41	ga_s2bm_ard_3-2-1_55JCF_2022-06-29_final.stac-item
2022-06-29 09:55:44	ga_s2bm_ard_3-2-1_55JBF_2022-06-29_final.stac-item
2022-06-29 09:55:48	ga_s2bm_ard_3-2-1_55HEE_2022-06-29_final.stac-item
2022-06-29 09:55:52	ga_s2bm_ard_3-2-1_55HDE_2022-06-29_final.stac-item
2022-06-29 09:55:55	ga_s2bm_ard_3-2-1_55HCE_2022-06-29_final.stac-item
2022-06-29 09:55:59	ga_s2bm_ard_3-2-1_55HBE_2022-06-29_final.stac-item
2022-06-29 09:56:02	ga_s2bm_ard_3-2-1_54HYK_2022-06-29_final.stac-item
2022-07-09 09:55:34	ga_s2bm_ard_3-2-1_55JEF_2022-07-09_final.stac-item
2022-10-17 11:36:09	ga_s2bm_ard_3-2-1_51JVF_2022-10-17_final.stac-item
2022-10-17 11:36:13	ga_s2bm_ard_3-2-1_51JUF_2022-10-17_final.stac-item
2022-10-17 11:36:16	ga_s2bm_ard_3-2-1_51JTF_2022-10-17_final.stac-item
2022-10-17 11:36:19	ga_s2bm_ard_3-2-1_50JQL_2022-10-17_final.stac-item
2022-10-17 11:36:23	ga_s2bm_ard_3-2-1_51HVE_2022-10-17_final.stac-item
2022-10-17 11:36:26	ga_s2bm_ard_3-2-1_50JPL_2022-10-17_final.stac-item
2022-10-17 11:36:28	ga_s2bm_ard_3-2-1_51HUE_2022-10-17_final.stac-item
2022-10-17 11:36:31	ga_s2bm_ard_3-2-1_51HTE_2022-10-17_final.stac-item
2022-10-17 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2022-10-17_final.stac-item
2022-10-17 11:36:37	ga_s2bm_ard_3-2-1_50HPK_2022-10-17_final.stac-item
2022-10-18 11:05:59	ga_s2bm_ard_3-2-1_52JEL_2022-10-18_final.stac-item
2022-10-18 11:06:02	ga_s2bm_ard_3-2-1_52JDL_2022-10-18_final.stac-item
2022-10-18 11:06:06	ga_s2bm_ard_3-2-1_52JCL_2022-10-18_final.stac-item
2022-10-18 11:06:09	ga_s2bm_ard_3-2-1_52JBL_2022-10-18_final.stac-item
2022-10-18 11:06:23	ga_s2bm_ard_3-2-1_52HBK_2022-10-18_final.stac-item
2022-10-19 08:55:20	ga_s2bm_ard_3-2-1_57JWF_2022-10-18_interim
2022-10-19 08:55:26	ga_s2bm_ard_3-2-1_57HWE_2022-10-18_interim
2022-10-19 10:35:44	ga_s2bm_ard_3-2-1_53JQF_2022-10-19_final.stac-item
2022-10-19 10:35:48	ga_s2bm_ard_3-2-1_53JPF_2022-10-19_final.stac-item
2022-10-19 10:35:52	ga_s2bm_ard_3-2-1_53JNF_2022-10-19_final.stac-item
2022-10-19 10:35:55	ga_s2bm_ard_3-2-1_53JMF_2022-10-19_final.stac-item
2022-10-19 10:35:56	ga_s2bm_ard_3-2-1_53HQE_2022-10-19_final.stac-item
2022-10-19 10:36:02	ga_s2bm_ard_3-2-1_53HPE_2022-10-19_final.stac-item
2022-10-19 10:36:06	ga_s2bm_ard_3-2-1_53HNE_2022-10-19_final.stac-item
2022-10-19 10:36:10	ga_s2bm_ard_3-2-1_53HME_2022-10-19_final.stac-item
2022-10-23 11:56:36	ga_s2bm_ard_3-2-1_50HMK_2022-10-23_final.stac-item
2022-10-23 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2022-10-23_final.stac-item
2022-10-24 09:45:21	ga_s2bm_ard_3-2-1_56JKL_2022-10-24_final.stac-item
2022-10-24 09:45:32	ga_s2bm_ard_3-2-1_56HKK_2022-10-24_final.stac-item
2022-10-24 09:45:36	ga_s2bm_ard_3-2-1_55JDF_2022-10-24_final.stac-item
2022-10-24 09:45:39	ga_s2bm_ard_3-2-1_55HGE_2022-10-24_final.stac-item
2022-10-24 09:45:43	ga_s2bm_ard_3-2-1_55HFE_2022-10-24_final.stac-item
2022-10-24 09:45:47	ga_s2bm_ard_3-2-1_55HEE_2022-10-24_final.stac-item
2022-10-24 09:45:50	ga_s2bm_ard_3-2-1_55HDE_2022-10-24_final.stac-item
2022-11-01 10:45:49	ga_s2bm_ard_3-2-1_53JMF_2022-11-01_final.stac-item
2022-11-01 10:45:53	ga_s2bm_ard_3-2-1_53JLF_2022-11-01_final.stac-item
2022-11-01 10:45:56	ga_s2bm_ard_3-2-1_53JKF_2022-11-01_final.stac-item
2022-11-01 10:45:58	ga_s2bm_ard_3-2-1_52JGL_2022-11-01_final.stac-item
2022-11-01 10:46:04	ga_s2bm_ard_3-2-1_53HME_2022-11-01_final.stac-item

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

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