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
2017-08-15 09:22:42	ga_s2bm_ard_3-2-1_55GEN_2017-08-14_final.stac-item
2017-08-15 09:22:42	ga_s2bm_ard_3-2-1_55GFN_2017-08-14_final.stac-item
2017-08-18 09:34:03	ga_s2bm_ard_3-2-1_55GCN_2017-08-18_final.stac-item
2017-08-18 09:34:03	ga_s2bm_ard_3-2-1_55GDN_2017-08-18_final.stac-item
2017-08-18 09:34:03	ga_s2bm_ard_3-2-1_55GDP_2017-08-18_final.stac-item
2017-08-18 09:34:03	ga_s2bm_ard_3-2-1_55GEN_2017-08-18_final.stac-item
2017-08-18 09:34:03	ga_s2bm_ard_3-2-1_55GEP_2017-08-18_final.stac-item
2017-08-18 09:34:03	ga_s2bm_ard_3-2-1_55GFN_2017-08-18_final.stac-item
2017-12-29 09:43:43	ga_s2bm_ard_3-2-1_55GCN_2017-12-29_final.stac-item
2017-12-29 09:43:43	ga_s2bm_ard_3-2-1_55GDN_2017-12-29_final.stac-item
2018-01-02 09:23:47	ga_s2bm_ard_3-2-1_55GEN_2018-01-01_final.stac-item
2018-01-02 09:23:47	ga_s2bm_ard_3-2-1_55GFN_2018-01-01_final.stac-item
2018-01-05 09:32:32	ga_s2bm_ard_3-2-1_55GCN_2018-01-05_final.stac-item
2018-01-05 09:32:32	ga_s2bm_ard_3-2-1_55GDN_2018-01-05_final.stac-item
2018-01-05 09:32:32	ga_s2bm_ard_3-2-1_55GDP_2018-01-05_final.stac-item
2018-01-05 09:32:32	ga_s2bm_ard_3-2-1_55GEN_2018-01-05_final.stac-item
2018-01-08 09:42:19	ga_s2bm_ard_3-2-1_55GCN_2018-01-08_final.stac-item
2018-01-08 09:42:19	ga_s2bm_ard_3-2-1_55GDN_2018-01-08_final.stac-item
2018-01-15 09:32:53	ga_s2bm_ard_3-2-1_55GCN_2018-01-15_final.stac-item
2018-01-15 09:32:53	ga_s2bm_ard_3-2-1_55GDN_2018-01-15_final.stac-item
2018-01-15 09:32:53	ga_s2bm_ard_3-2-1_55GDP_2018-01-15_final.stac-item
2018-01-15 09:32:53	ga_s2bm_ard_3-2-1_55GEN_2018-01-15_final.stac-item
2018-01-15 09:32:53	ga_s2bm_ard_3-2-1_55GEP_2018-01-15_final.stac-item
2018-01-15 09:32:53	ga_s2bm_ard_3-2-1_55GFN_2018-01-15_final.stac-item
2018-06-24 09:32:39	ga_s2bm_ard_3-2-1_55GCN_2018-06-24_final.stac-item
2018-06-24 09:32:39	ga_s2bm_ard_3-2-1_55GDN_2018-06-24_final.stac-item
2018-06-24 09:32:39	ga_s2bm_ard_3-2-1_55GDP_2018-06-24_final.stac-item
2018-06-24 09:32:39	ga_s2bm_ard_3-2-1_55GEN_2018-06-24_final.stac-item
2018-06-24 09:32:39	ga_s2bm_ard_3-2-1_55GEP_2018-06-24_final.stac-item
2018-06-24 09:32:39	ga_s2bm_ard_3-2-1_55GFN_2018-06-24_final.stac-item
2018-06-27 09:41:07	ga_s2bm_ard_3-2-1_55GCN_2018-06-27_final.stac-item
2018-06-27 09:41:07	ga_s2bm_ard_3-2-1_55GDN_2018-06-27_final.stac-item
2018-07-01 09:25:58	ga_s2bm_ard_3-2-1_55GEN_2018-06-30_final.stac-item
2018-07-01 09:25:58	ga_s2bm_ard_3-2-1_55GFN_2018-06-30_final.stac-item
2018-07-04 09:36:08	ga_s2bm_ard_3-2-1_55GCN_2018-07-04_final.stac-item
2018-07-04 09:36:08	ga_s2bm_ard_3-2-1_55GDN_2018-07-04_final.stac-item
2018-07-04 09:36:08	ga_s2bm_ard_3-2-1_55GDP_2018-07-04_final.stac-item
2018-07-04 09:36:08	ga_s2bm_ard_3-2-1_55GEN_2018-07-04_final.stac-item
2018-07-04 09:36:08	ga_s2bm_ard_3-2-1_55GEP_2018-07-04_final.stac-item
2018-07-04 09:36:08	ga_s2bm_ard_3-2-1_55GFN_2018-07-04_final.stac-item
2018-07-07 09:42:12	ga_s2bm_ard_3-2-1_55GCN_2018-07-07_final.stac-item
2018-07-07 09:42:12	ga_s2bm_ard_3-2-1_55GDN_2018-07-07_final.stac-item
2018-07-11 09:25:54	ga_s2bm_ard_3-2-1_55GEN_2018-07-10_final.stac-item
2018-07-11 09:25:54	ga_s2bm_ard_3-2-1_55GFN_2018-07-10_final.stac-item
2018-07-14 09:37:45	ga_s2bm_ard_3-2-1_55GCN_2018-07-14_final.stac-item
2018-07-14 09:37:45	ga_s2bm_ard_3-2-1_55GDN_2018-07-14_final.stac-item
2018-07-14 09:37:45	ga_s2bm_ard_3-2-1_55GDP_2018-07-14_final.stac-item
2018-07-14 09:37:45	ga_s2bm_ard_3-2-1_55GEN_2018-07-14_final.stac-item
2018-07-14 09:37:45	ga_s2bm_ard_3-2-1_55GEP_2018-07-14_final.stac-item
2018-07-14 09:37:45	ga_s2bm_ard_3-2-1_55GFN_2018-07-14_final.stac-item
2019-09-20 09:48:44	ga_s2bm_ard_3-2-1_55GDN_2019-09-20_final.stac-item
2019-09-20 09:48:48	ga_s2bm_ard_3-2-1_55GCN_2019-09-20_final.stac-item
2019-09-30 09:48:45	ga_s2bm_ard_3-2-1_55GDN_2019-09-30_final.stac-item
2019-09-30 09:48:49	ga_s2bm_ard_3-2-1_55GCN_2019-09-30_final.stac-item
2019-10-04 09:28:45	ga_s2bm_ard_3-2-1_55GFN_2019-10-03_final.stac-item
2019-10-04 09:28:50	ga_s2bm_ard_3-2-1_55GEN_2019-10-03_final.stac-item
2019-10-07 09:38:46	ga_s2bm_ard_3-2-1_55GEN_2019-10-07_final.stac-item
2019-10-07 09:38:50	ga_s2bm_ard_3-2-1_55GDN_2019-10-07_final.stac-item
2019-10-07 09:38:53	ga_s2bm_ard_3-2-1_55GCN_2019-10-07_final.stac-item
2019-10-14 09:28:46	ga_s2bm_ard_3-2-1_55GFN_2019-10-13_final.stac-item
2019-10-14 09:28:50	ga_s2bm_ard_3-2-1_55GEN_2019-10-13_final.stac-item
2019-10-17 09:38:32	ga_s2bm_ard_3-2-1_55GEP_2019-10-17_final.stac-item
2019-10-17 09:38:36	ga_s2bm_ard_3-2-1_55GDP_2019-10-17_final.stac-item
2019-10-17 09:38:42	ga_s2bm_ard_3-2-1_55GFN_2019-10-17_final.stac-item
2019-10-17 09:38:46	ga_s2bm_ard_3-2-1_55GEN_2019-10-17_final.stac-item
2019-10-17 09:38:50	ga_s2bm_ard_3-2-1_55GDN_2019-10-17_final.stac-item
2019-10-17 09:38:54	ga_s2bm_ard_3-2-1_55GCN_2019-10-17_final.stac-item
2019-10-20 09:48:46	ga_s2bm_ard_3-2-1_55GDN_2019-10-20_final.stac-item
2019-10-20 09:48:50	ga_s2bm_ard_3-2-1_55GCN_2019-10-20_final.stac-item
2019-10-27 09:38:32	ga_s2bm_ard_3-2-1_55GEP_2019-10-27_final.stac-item
2019-10-27 09:38:35	ga_s2bm_ard_3-2-1_55GDP_2019-10-27_final.stac-item
2019-10-27 09:38:42	ga_s2bm_ard_3-2-1_55GFN_2019-10-27_final.stac-item
2019-10-27 09:38:46	ga_s2bm_ard_3-2-1_55GEN_2019-10-27_final.stac-item
2019-10-27 09:38:50	ga_s2bm_ard_3-2-1_55GDN_2019-10-27_final.stac-item
2019-10-27 09:38:53	ga_s2bm_ard_3-2-1_55GCN_2019-10-27_final.stac-item
2019-10-30 09:48:46	ga_s2bm_ard_3-2-1_55GDN_2019-10-30_final.stac-item
2019-10-30 09:48:50	ga_s2bm_ard_3-2-1_55GCN_2019-10-30_final.stac-item
2019-11-03 09:28:45	ga_s2bm_ard_3-2-1_55GFN_2019-11-02_final.stac-item
2019-11-03 09:28:49	ga_s2bm_ard_3-2-1_55GEN_2019-11-02_final.stac-item
2019-12-03 09:28:39	ga_s2bm_ard_3-2-1_55GFN_2019-12-02_final.stac-item
2019-12-03 09:28:43	ga_s2bm_ard_3-2-1_55GEN_2019-12-02_final.stac-item
2019-12-06 09:38:25	ga_s2bm_ard_3-2-1_55GEP_2019-12-06_final.stac-item
2019-12-06 09:38:28	ga_s2bm_ard_3-2-1_55GDP_2019-12-06_final.stac-item
2019-12-06 09:38:35	ga_s2bm_ard_3-2-1_55GFN_2019-12-06_final.stac-item
2019-12-06 09:38:39	ga_s2bm_ard_3-2-1_55GEN_2019-12-06_final.stac-item
2019-12-06 09:38:43	ga_s2bm_ard_3-2-1_55GDN_2019-12-06_final.stac-item
2019-12-06 09:38:46	ga_s2bm_ard_3-2-1_55GCN_2019-12-06_final.stac-item
2019-12-09 09:48:39	ga_s2bm_ard_3-2-1_55GDN_2019-12-09_final.stac-item
2019-12-09 09:48:43	ga_s2bm_ard_3-2-1_55GCN_2019-12-09_final.stac-item
2019-12-13 09:28:39	ga_s2bm_ard_3-2-1_55GFN_2019-12-12_final.stac-item
2019-12-13 09:28:43	ga_s2bm_ard_3-2-1_55GEN_2019-12-12_final.stac-item
2019-12-16 09:38:25	ga_s2bm_ard_3-2-1_55GEP_2019-12-16_final.stac-item
2019-12-16 09:38:29	ga_s2bm_ard_3-2-1_55GDP_2019-12-16_final.stac-item
2019-12-16 09:38:35	ga_s2bm_ard_3-2-1_55GFN_2019-12-16_final.stac-item
2019-12-16 09:38:40	ga_s2bm_ard_3-2-1_55GEN_2019-12-16_final.stac-item
2019-12-16 09:38:43	ga_s2bm_ard_3-2-1_55GDN_2019-12-16_final.stac-item
2019-12-16 09:38:47	ga_s2bm_ard_3-2-1_55GCN_2019-12-16_final.stac-item
2019-12-19 09:48:40	ga_s2bm_ard_3-2-1_55GDN_2019-12-19_final.stac-item
2019-12-19 09:48:44	ga_s2bm_ard_3-2-1_55GCN_2019-12-19_final.stac-item
2019-12-23 09:28:40	ga_s2bm_ard_3-2-1_55GFN_2019-12-22_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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