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
2018-09-12 09:37:59	ga_s2bm_ard_3-2-1_55GEN_2018-09-12_final.stac-item
2018-09-12 09:37:59	ga_s2bm_ard_3-2-1_55GEP_2018-09-12_final.stac-item
2018-09-12 09:37:59	ga_s2bm_ard_3-2-1_55GEQ_2018-09-12_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55HEA_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55HEB_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55HEC_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55HED_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55HEE_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JEF_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JEG_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JEH_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JEJ_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JEK_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JEL_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JFK_2018-09-15_final.stac-item
2018-09-15 09:41:00	ga_s2bm_ard_3-2-1_55JFL_2018-09-15_final.stac-item
2018-09-15 09:46:25	ga_s2bm_ard_3-2-1_55HEA_2018-09-15_final.stac-item
2018-09-15 09:46:25	ga_s2bm_ard_3-2-1_55HEB_2018-09-15_final.stac-item
2018-09-15 09:46:25	ga_s2bm_ard_3-2-1_55HET_2018-09-15_final.stac-item
2018-09-15 09:46:25	ga_s2bm_ard_3-2-1_55HEU_2018-09-15_final.stac-item
2018-09-15 09:46:25	ga_s2bm_ard_3-2-1_55HEV_2018-09-15_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JEH_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JEJ_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JEK_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JEL_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JEM_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JEN_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JFK_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JFL_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JFM_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55JFN_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KEP_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KEQ_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KER_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KES_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KET_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KEU_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KEV_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFA_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFP_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFQ_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFR_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFS_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFT_2018-09-18_final.stac-item
2018-09-18 09:50:46	ga_s2bm_ard_3-2-1_55KFU_2018-09-18_final.stac-item
2018-09-21 09:57:00	ga_s2bm_ard_3-2-1_55KEB_2018-09-21_final.stac-item
2018-09-21 09:57:00	ga_s2bm_ard_3-2-1_55KEV_2018-09-21_final.stac-item
2018-09-21 09:57:00	ga_s2bm_ard_3-2-1_55KFA_2018-09-21_final.stac-item
2018-09-21 09:57:00	ga_s2bm_ard_3-2-1_55KFB_2018-09-21_final.stac-item
2018-09-21 09:57:00	ga_s2bm_ard_3-2-1_55LEC_2018-09-21_final.stac-item
2018-09-21 09:57:00	ga_s2bm_ard_3-2-1_55LFC_2018-09-21_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55GEQ_2018-09-22_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55GER_2018-09-22_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55HEA_2018-09-22_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55HES_2018-09-22_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55HET_2018-09-22_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55HEU_2018-09-22_final.stac-item
2018-09-22 09:32:33	ga_s2bm_ard_3-2-1_55HEV_2018-09-22_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KER_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KES_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KET_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KEU_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KEV_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KFA_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KFR_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KFS_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KFT_2018-09-28_final.stac-item
2018-09-28 09:50:48	ga_s2bm_ard_3-2-1_55KFU_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JEK_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JEL_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JEM_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JEN_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JFK_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JFL_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JFM_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55JFN_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KEP_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KEQ_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KER_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KES_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KFP_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KFQ_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KFR_2018-09-28_final.stac-item
2018-09-28 09:52:43	ga_s2bm_ard_3-2-1_55KFS_2018-09-28_final.stac-item
2018-10-18 09:50:51	ga_s2bm_ard_3-2-1_55JEJ_2018-10-18_final.stac-item
2018-10-18 09:50:51	ga_s2bm_ard_3-2-1_55JEK_2018-10-18_final.stac-item
2018-10-18 09:54:31	ga_s2bm_ard_3-2-1_55JEJ_2018-10-18_final.stac-item
2019-06-08 10:01:22	ga_s2bm_ard_3-2-1_55LFC_2019-06-08_final.stac-item
2019-06-08 10:01:25	ga_s2bm_ard_3-2-1_55LEC_2019-06-08_final.stac-item
2019-06-08 10:01:36	ga_s2bm_ard_3-2-1_55KFB_2019-06-08_final.stac-item
2019-06-08 10:01:40	ga_s2bm_ard_3-2-1_55KEB_2019-06-08_final.stac-item
2019-06-08 10:01:50	ga_s2bm_ard_3-2-1_55KFA_2019-06-08_final.stac-item
2019-06-08 10:02:02	ga_s2bm_ard_3-2-1_55KEV_2019-06-08_final.stac-item
2019-06-08 10:02:09	ga_s2bm_ard_3-2-1_55KEV_2019-06-08_final.stac-item
2019-06-18 10:01:21	ga_s2bm_ard_3-2-1_55LFC_2019-06-18_final.stac-item
2019-06-18 10:01:25	ga_s2bm_ard_3-2-1_55LEC_2019-06-18_final.stac-item
2019-06-18 10:01:36	ga_s2bm_ard_3-2-1_55KFB_2019-06-18_final.stac-item
2019-06-18 10:01:40	ga_s2bm_ard_3-2-1_55KEB_2019-06-18_final.stac-item
2019-06-18 10:01:50	ga_s2bm_ard_3-2-1_55KFA_2019-06-18_final.stac-item
2019-06-18 10:02:02	ga_s2bm_ard_3-2-1_55KEV_2019-06-18_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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