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
2019-06-04 12:05:16	ga_s2bm_ard_3-2-1_50JLR_2019-06-04_final.stac-item
2019-06-04 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-06-04_final.stac-item
2019-06-04 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-06-04_final.stac-item
2019-06-04 12:05:31	ga_s2bm_ard_3-2-1_50JLQ_2019-06-04_final.stac-item
2019-06-04 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-06-04_final.stac-item
2019-06-04 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-06-04_final.stac-item
2019-06-05 09:54:21	ga_s2bm_ard_3-2-1_55JFL_2019-06-05_final.stac-item
2019-06-05 09:54:24	ga_s2bm_ard_3-2-1_55JEL_2019-06-05_final.stac-item
2019-06-05 09:54:28	ga_s2bm_ard_3-2-1_55JDL_2019-06-05_final.stac-item
2019-06-05 09:54:31	ga_s2bm_ard_3-2-1_55JCL_2019-06-05_final.stac-item
2019-06-06 11:04:51	ga_s2bm_ard_3-2-1_52JFR_2019-06-06_final.stac-item
2019-06-06 11:04:55	ga_s2bm_ard_3-2-1_52JER_2019-06-06_final.stac-item
2019-06-06 11:04:58	ga_s2bm_ard_3-2-1_52JDR_2019-06-06_final.stac-item
2019-06-06 11:05:04	ga_s2bm_ard_3-2-1_52JCR_2019-06-06_final.stac-item
2019-06-12 11:24:58	ga_s2bm_ard_3-2-1_51JYL_2019-06-12_final.stac-item
2019-06-12 11:25:03	ga_s2bm_ard_3-2-1_51JXL_2019-06-12_final.stac-item
2019-06-12 11:25:06	ga_s2bm_ard_3-2-1_51JWL_2019-06-12_final.stac-item
2019-06-12 11:25:11	ga_s2bm_ard_3-2-1_51JVL_2019-06-12_final.stac-item
2019-06-12 11:25:13	ga_s2bm_ard_3-2-1_51JYK_2019-06-12_final.stac-item
2019-06-12 11:25:17	ga_s2bm_ard_3-2-1_51JXK_2019-06-12_final.stac-item
2019-06-14 12:05:15	ga_s2bm_ard_3-2-1_50JLR_2019-06-14_final.stac-item
2019-06-14 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-14 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2019-06-14_final.stac-item
2019-06-14 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2019-06-14_final.stac-item
2019-06-14 12:05:26	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-14 12:05:26	ga_s2bm_ard_3-2-1_50JKQ_2019-06-14_final.stac-item
2019-06-14 12:05:27	ga_s2bm_ard_3-2-1_49JGK_2019-06-14_final.stac-item
2019-06-14 12:05:27	ga_s2bm_ard_3-2-1_49JGL_2019-06-14_final.stac-item
2019-06-14 12:05:33	ga_s2bm_ard_3-2-1_50JKQ_2019-06-14_final.stac-item
2019-06-14 12:05:36	ga_s2bm_ard_3-2-1_49JGK_2019-06-14_final.stac-item
2019-06-15 09:54:20	ga_s2bm_ard_3-2-1_55JFL_2019-06-15_final.stac-item
2019-06-15 09:54:24	ga_s2bm_ard_3-2-1_55JEL_2019-06-15_final.stac-item
2019-06-15 09:54:27	ga_s2bm_ard_3-2-1_55JDL_2019-06-15_final.stac-item
2019-06-15 09:54:30	ga_s2bm_ard_3-2-1_55JCL_2019-06-15_final.stac-item
2019-06-15 11:35:02	ga_s2bm_ard_3-2-1_51JWL_2019-06-15_final.stac-item
2019-06-15 11:35:05	ga_s2bm_ard_3-2-1_51JVL_2019-06-15_final.stac-item
2019-06-15 11:35:08	ga_s2bm_ard_3-2-1_51JUL_2019-06-15_final.stac-item
2019-06-15 11:35:11	ga_s2bm_ard_3-2-1_51JTL_2019-06-15_final.stac-item
2019-06-15 11:35:23	ga_s2bm_ard_3-2-1_51JUK_2019-06-15_final.stac-item
2019-06-15 11:35:26	ga_s2bm_ard_3-2-1_51JTK_2019-06-15_final.stac-item
2019-06-20 10:44:43	ga_s2bm_ard_3-2-1_53JNL_2019-06-20_final.stac-item
2019-06-20 10:44:47	ga_s2bm_ard_3-2-1_53JML_2019-06-20_final.stac-item
2019-06-20 10:44:50	ga_s2bm_ard_3-2-1_53JLL_2019-06-20_final.stac-item
2019-06-20 10:44:56	ga_s2bm_ard_3-2-1_53JKL_2019-06-20_final.stac-item
2019-06-20 10:45:04	ga_s2bm_ard_3-2-1_53JLK_2019-06-20_final.stac-item
2019-06-20 10:45:08	ga_s2bm_ard_3-2-1_53JKK_2019-06-20_final.stac-item
2019-06-24 12:05:16	ga_s2bm_ard_3-2-1_50JLR_2019-06-24_final.stac-item
2019-06-24 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-06-24_final.stac-item
2019-06-24 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-06-24_final.stac-item
2019-06-24 12:05:31	ga_s2bm_ard_3-2-1_50JLQ_2019-06-24_final.stac-item
2019-06-24 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-06-24_final.stac-item
2019-06-24 12:05:37	ga_s2bm_ard_3-2-1_49JGK_2019-06-24_final.stac-item
2019-06-25 09:54:21	ga_s2bm_ard_3-2-1_55JFL_2019-06-25_final.stac-item
2019-06-25 09:54:25	ga_s2bm_ard_3-2-1_55JEL_2019-06-25_final.stac-item
2019-06-25 09:54:28	ga_s2bm_ard_3-2-1_55JDL_2019-06-25_final.stac-item
2019-06-25 09:54:31	ga_s2bm_ard_3-2-1_55JCL_2019-06-25_final.stac-item
2019-07-07 10:34:38	ga_s2bm_ard_3-2-1_54JTR_2019-07-07_final.stac-item
2019-07-07 10:34:41	ga_s2bm_ard_3-2-1_53JQL_2019-07-07_final.stac-item
2019-07-07 10:34:45	ga_s2bm_ard_3-2-1_53JPL_2019-07-07_final.stac-item
2019-07-07 10:34:48	ga_s2bm_ard_3-2-1_53JNL_2019-07-07_final.stac-item
2019-07-07 10:34:52	ga_s2bm_ard_3-2-1_54JTQ_2019-07-07_final.stac-item
2019-07-07 10:34:56	ga_s2bm_ard_3-2-1_53JQK_2019-07-07_final.stac-item
2019-07-07 10:34:59	ga_s2bm_ard_3-2-1_53JPK_2019-07-07_final.stac-item
2019-07-07 12:15:19	ga_s2bm_ard_3-2-1_49JGL_2019-07-07_final.stac-item
2019-07-07 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-07-07_final.stac-item
2019-07-08 10:04:22	ga_s2bm_ard_3-2-1_55JDL_2019-07-08_final.stac-item
2019-07-08 10:04:27	ga_s2bm_ard_3-2-1_55JCL_2019-07-08_final.stac-item
2019-07-08 10:04:31	ga_s2bm_ard_3-2-1_55JBL_2019-07-08_final.stac-item
2019-07-08 10:04:34	ga_s2bm_ard_3-2-1_54JYR_2019-07-08_final.stac-item
2019-07-08 10:04:41	ga_s2bm_ard_3-2-1_54JXR_2019-07-08_final.stac-item
2019-07-08 10:04:42	ga_s2bm_ard_3-2-1_55JCK_2019-07-08_final.stac-item
2019-07-08 10:04:45	ga_s2bm_ard_3-2-1_55JBK_2019-07-08_final.stac-item
2019-07-08 10:04:48	ga_s2bm_ard_3-2-1_54JYQ_2019-07-08_final.stac-item
2019-07-08 10:04:52	ga_s2bm_ard_3-2-1_54JXQ_2019-07-08_final.stac-item
2019-07-19 11:14:55	ga_s2bm_ard_3-2-1_52JDR_2019-07-19_final.stac-item
2019-07-19 11:14:58	ga_s2bm_ard_3-2-1_52JCR_2019-07-19_final.stac-item
2019-07-19 11:15:01	ga_s2bm_ard_3-2-1_52JBR_2019-07-19_final.stac-item
2019-07-19 11:15:13	ga_s2bm_ard_3-2-1_52JCQ_2019-07-19_final.stac-item
2019-07-19 11:15:16	ga_s2bm_ard_3-2-1_52JBQ_2019-07-19_final.stac-item
2019-07-24 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-07-24_final.stac-item
2019-07-24 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2019-07-24_final.stac-item
2019-07-24 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2019-07-24_final.stac-item
2019-07-24 12:05:31	ga_s2bm_ard_3-2-1_49JGL_2019-07-24_final.stac-item
2019-07-24 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2019-07-24_final.stac-item
2019-07-24 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-24_final.stac-item
2019-07-25 09:54:21	ga_s2bm_ard_3-2-1_55JFL_2019-07-25_final.stac-item
2019-07-25 09:54:25	ga_s2bm_ard_3-2-1_55JEL_2019-07-25_final.stac-item
2019-07-25 09:54:28	ga_s2bm_ard_3-2-1_55JDL_2019-07-25_final.stac-item
2019-07-25 09:54:31	ga_s2bm_ard_3-2-1_55JCL_2019-07-25_final.stac-item
2019-08-23 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2019-08-23_final.stac-item
2019-08-23 12:05:17	ga_s2bm_ard_3-2-1_50JKR_2019-08-23_final.stac-item
2019-08-23 12:05:20	ga_s2bm_ard_3-2-1_49JGL_2019-08-23_final.stac-item
2019-08-23 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2019-08-23_final.stac-item
2019-08-23 12:05:31	ga_s2bm_ard_3-2-1_50JKQ_2019-08-23_final.stac-item
2019-08-23 12:05:34	ga_s2bm_ard_3-2-1_49JGK_2019-08-23_final.stac-item
2019-09-12 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2019-09-12_final.stac-item
2019-09-12 12:05:12	ga_s2bm_ard_3-2-1_50JKR_2019-09-12_final.stac-item
2019-09-12 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2019-09-12_final.stac-item
2019-09-12 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2019-09-12_final.stac-item
2019-09-12 12:05:27	ga_s2bm_ard_3-2-1_50JKQ_2019-09-12_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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