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
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JLL_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JML_2017-10-19_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JNL_2017-10-19_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_50HQK_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_51JTF_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_51JUF_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_51JVF_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_50JPL_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_50JQL_2017-11-12_final.stac-item
2017-11-13 09:23:11	ga_s2bm_ard_3-2-1_56JLL_2017-11-12_final.stac-item
2017-11-13 09:23:11	ga_s2bm_ard_3-2-1_56JML_2017-11-12_final.stac-item
2017-11-13 09:23:11	ga_s2bm_ard_3-2-1_56JNL_2017-11-12_final.stac-item
2018-05-28 09:41:05	ga_s2bm_ard_3-2-1_56JKL_2018-05-28_final.stac-item
2018-05-28 09:41:05	ga_s2bm_ard_3-2-1_55JDF_2018-05-28_final.stac-item
2018-05-28 09:41:05	ga_s2bm_ard_3-2-1_55JEF_2018-05-28_final.stac-item
2018-05-28 09:41:05	ga_s2bm_ard_3-2-1_55JFF_2018-05-28_final.stac-item
2018-05-28 09:41:05	ga_s2bm_ard_3-2-1_55JGF_2018-05-28_final.stac-item
2018-05-28 11:21:19	ga_s2bm_ard_3-2-1_51JUF_2018-05-28_final.stac-item
2018-05-28 11:21:19	ga_s2bm_ard_3-2-1_51JVF_2018-05-28_final.stac-item
2018-05-28 11:21:19	ga_s2bm_ard_3-2-1_51JWF_2018-05-28_final.stac-item
2018-05-28 11:21:19	ga_s2bm_ard_3-2-1_51JXF_2018-05-28_final.stac-item
2019-07-06 11:06:08	ga_s2bm_ard_3-2-1_52JEL_2019-07-06_final.stac-item
2019-07-06 11:06:12	ga_s2bm_ard_3-2-1_52JDL_2019-07-06_final.stac-item
2019-07-06 11:06:15	ga_s2bm_ard_3-2-1_52JCL_2019-07-06_final.stac-item
2019-07-06 11:06:19	ga_s2bm_ard_3-2-1_52JBL_2019-07-06_final.stac-item
2019-07-23 10:56:02	ga_s2bm_ard_3-2-1_53JKF_2019-07-23_final.stac-item
2019-07-23 10:56:05	ga_s2bm_ard_3-2-1_52JGL_2019-07-23_final.stac-item
2019-07-23 10:56:09	ga_s2bm_ard_3-2-1_52JFL_2019-07-23_final.stac-item
2019-07-23 10:56:12	ga_s2bm_ard_3-2-1_52JEL_2019-07-23_final.stac-item
2019-07-24 10:25:51	ga_s2bm_ard_3-2-1_54JUL_2019-07-24_final.stac-item
2019-07-24 10:25:55	ga_s2bm_ard_3-2-1_54JTL_2019-07-24_final.stac-item
2019-07-24 10:25:57	ga_s2bm_ard_3-2-1_53JQF_2019-07-24_final.stac-item
2019-07-24 10:26:01	ga_s2bm_ard_3-2-1_53JPF_2019-07-24_final.stac-item
2019-07-24 10:26:12	ga_s2bm_ard_3-2-1_53HQE_2019-07-24_final.stac-item
2019-07-26 09:25:30	ga_s2bm_ard_3-2-1_56JNL_2019-07-25_final.stac-item
2019-07-26 09:25:33	ga_s2bm_ard_3-2-1_56JML_2019-07-25_final.stac-item
2019-07-26 09:25:38	ga_s2bm_ard_3-2-1_56JLL_2019-07-25_final.stac-item
2019-08-01 11:26:15	ga_s2bm_ard_3-2-1_51JXF_2019-08-01_final.stac-item
2019-08-01 11:26:19	ga_s2bm_ard_3-2-1_51JWF_2019-08-01_final.stac-item
2019-08-01 11:26:22	ga_s2bm_ard_3-2-1_51JVF_2019-08-01_final.stac-item
2019-08-01 11:26:26	ga_s2bm_ard_3-2-1_51JUF_2019-08-01_final.stac-item
2019-08-09 10:45:58	ga_s2bm_ard_3-2-1_53JMF_2019-08-09_final.stac-item
2019-08-09 10:46:02	ga_s2bm_ard_3-2-1_53JLF_2019-08-09_final.stac-item
2019-08-09 10:46:05	ga_s2bm_ard_3-2-1_53JKF_2019-08-09_final.stac-item
2019-08-18 11:16:11	ga_s2bm_ard_3-2-1_52JCL_2019-08-18_final.stac-item
2019-08-18 11:16:13	ga_s2bm_ard_3-2-1_52JBL_2019-08-18_final.stac-item
2019-08-18 11:16:14	ga_s2bm_ard_3-2-1_51JYF_2019-08-18_final.stac-item
2019-08-18 11:16:18	ga_s2bm_ard_3-2-1_51JXF_2019-08-18_final.stac-item
2019-08-18 11:16:26	ga_s2bm_ard_3-2-1_51JWF_2019-08-18_final.stac-item
2019-08-18 11:16:28	ga_s2bm_ard_3-2-1_51HYE_2019-08-18_final.stac-item
2019-08-20 11:56:24	ga_s2bm_ard_3-2-1_50JNL_2019-08-20_final.stac-item
2019-08-20 11:56:28	ga_s2bm_ard_3-2-1_50JML_2019-08-20_final.stac-item
2019-08-20 11:56:31	ga_s2bm_ard_3-2-1_50JLL_2019-08-20_final.stac-item
2019-10-18 10:46:01	ga_s2bm_ard_3-2-1_52JGL_2019-10-18_final.stac-item
2019-10-19 10:15:38	ga_s2bm_ard_3-2-1_54JXL_2019-10-19_final.stac-item
2019-10-19 10:15:42	ga_s2bm_ard_3-2-1_54JWL_2019-10-19_final.stac-item
2019-10-19 10:15:45	ga_s2bm_ard_3-2-1_54JVL_2019-10-19_final.stac-item
2019-10-19 10:15:49	ga_s2bm_ard_3-2-1_54JUL_2019-10-19_final.stac-item
2019-10-21 10:55:55	ga_s2bm_ard_3-2-1_53JKF_2019-10-21_final.stac-item
2019-10-21 10:55:57	ga_s2bm_ard_3-2-1_52JGL_2019-10-21_final.stac-item
2019-10-21 10:56:01	ga_s2bm_ard_3-2-1_52JFL_2019-10-21_final.stac-item
2019-10-21 10:56:05	ga_s2bm_ard_3-2-1_52JEL_2019-10-21_final.stac-item
2019-10-22 10:25:44	ga_s2bm_ard_3-2-1_54JUL_2019-10-22_final.stac-item
2019-10-22 10:25:48	ga_s2bm_ard_3-2-1_54JTL_2019-10-22_final.stac-item
2019-10-22 10:25:50	ga_s2bm_ard_3-2-1_53JQF_2019-10-22_final.stac-item
2019-10-22 10:25:53	ga_s2bm_ard_3-2-1_53JPF_2019-10-22_final.stac-item
2019-10-28 10:45:52	ga_s2bm_ard_3-2-1_53JMF_2019-10-28_final.stac-item
2019-10-28 10:45:56	ga_s2bm_ard_3-2-1_53JLF_2019-10-28_final.stac-item
2019-10-28 10:45:59	ga_s2bm_ard_3-2-1_53JKF_2019-10-28_final.stac-item
2019-10-28 10:46:01	ga_s2bm_ard_3-2-1_52JGL_2019-10-28_final.stac-item
2019-10-29 10:15:38	ga_s2bm_ard_3-2-1_54JXL_2019-10-29_final.stac-item
2019-10-29 10:15:41	ga_s2bm_ard_3-2-1_54JWL_2019-10-29_final.stac-item
2019-10-29 10:15:45	ga_s2bm_ard_3-2-1_54JVL_2019-10-29_final.stac-item
2019-10-29 10:15:48	ga_s2bm_ard_3-2-1_54JUL_2019-10-29_final.stac-item
2019-10-31 10:55:54	ga_s2bm_ard_3-2-1_53JKF_2019-10-31_final.stac-item
2019-10-31 10:55:57	ga_s2bm_ard_3-2-1_52JGL_2019-10-31_final.stac-item
2019-10-31 10:56:01	ga_s2bm_ard_3-2-1_52JFL_2019-10-31_final.stac-item
2019-10-31 10:56:04	ga_s2bm_ard_3-2-1_52JEL_2019-10-31_final.stac-item
2019-11-02 09:55:29	ga_s2bm_ard_3-2-1_55JEF_2019-11-02_final.stac-item
2019-11-02 09:55:33	ga_s2bm_ard_3-2-1_55JDF_2019-11-02_final.stac-item
2019-11-02 09:55:36	ga_s2bm_ard_3-2-1_55JCF_2019-11-02_final.stac-item
2019-11-02 09:55:39	ga_s2bm_ard_3-2-1_55JBF_2019-11-02_final.stac-item
2019-11-02 09:55:57	ga_s2bm_ard_3-2-1_54HYK_2019-11-02_final.stac-item
2020-04-25 10:45:46	ga_s2bm_ard_3-2-1_53JMF_2020-04-25_final.stac-item
2020-04-25 10:45:50	ga_s2bm_ard_3-2-1_53JLF_2020-04-25_final.stac-item
2020-04-25 10:45:53	ga_s2bm_ard_3-2-1_53JKF_2020-04-25_final.stac-item
2020-04-25 10:45:55	ga_s2bm_ard_3-2-1_52JGL_2020-04-25_final.stac-item
2020-04-27 11:26:02	ga_s2bm_ard_3-2-1_51JXF_2020-04-27_final.stac-item
2020-04-27 11:26:06	ga_s2bm_ard_3-2-1_51JWF_2020-04-27_final.stac-item
2020-04-27 11:26:10	ga_s2bm_ard_3-2-1_51JVF_2020-04-27_final.stac-item
2020-04-27 11:26:13	ga_s2bm_ard_3-2-1_51JUF_2020-04-27_final.stac-item
2020-05-03 10:05:26	ga_s2bm_ard_3-2-1_55JCF_2020-05-03_final.stac-item
2020-05-03 10:05:31	ga_s2bm_ard_3-2-1_55JBF_2020-05-03_final.stac-item
2020-05-03 10:05:34	ga_s2bm_ard_3-2-1_54JYL_2020-05-03_final.stac-item
2020-05-03 10:05:38	ga_s2bm_ard_3-2-1_54JXL_2020-05-03_final.stac-item
2020-05-03 10:05:42	ga_s2bm_ard_3-2-1_54JWL_2020-05-03_final.stac-item
2020-05-03 10:05:48	ga_s2bm_ard_3-2-1_54HYK_2020-05-03_final.stac-item
2020-05-12 10:35:43	ga_s2bm_ard_3-2-1_53JQF_2020-05-12_final.stac-item
2020-05-12 10:35:47	ga_s2bm_ard_3-2-1_53JPF_2020-05-12_final.stac-item
2020-05-12 10:35:51	ga_s2bm_ard_3-2-1_53JNF_2020-05-12_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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