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
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52LGH_2018-06-24_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52LGJ_2018-06-24_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52LGK_2018-06-24_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52LGL_2018-06-24_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52LGM_2018-06-24_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52LGN_2018-06-24_final.stac-item
2018-06-28 10:47:24	ga_s2bm_ard_3-2-1_52JFQ_2018-06-28_final.stac-item
2018-06-28 10:47:24	ga_s2bm_ard_3-2-1_52JFR_2018-06-28_final.stac-item
2018-06-28 10:54:55	ga_s2bm_ard_3-2-1_52JFL_2018-06-28_final.stac-item
2018-06-28 10:54:55	ga_s2bm_ard_3-2-1_52JFM_2018-06-28_final.stac-item
2018-06-28 10:54:55	ga_s2bm_ard_3-2-1_52JFN_2018-06-28_final.stac-item
2018-06-28 10:54:55	ga_s2bm_ard_3-2-1_52JFP_2018-06-28_final.stac-item
2018-06-28 10:54:55	ga_s2bm_ard_3-2-1_52JFQ_2018-06-28_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KFA_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KFB_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KFC_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KFD_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KFE_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGA_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGB_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGC_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGD_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGE_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGF_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KGG_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52LGH_2018-07-01_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52LGJ_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52JFR_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52JFS_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52JFT_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52JGS_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52JGT_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52KFA_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52KFU_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52KFV_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52KGA_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52KGU_2018-07-01_final.stac-item
2018-07-01 11:03:23	ga_s2bm_ard_3-2-1_52KGV_2018-07-01_final.stac-item
2018-07-04 11:07:15	ga_s2bm_ard_3-2-1_52LGH_2018-07-04_final.stac-item
2018-07-04 11:07:15	ga_s2bm_ard_3-2-1_52LGJ_2018-07-04_final.stac-item
2018-07-04 11:07:15	ga_s2bm_ard_3-2-1_52LGK_2018-07-04_final.stac-item
2018-07-04 11:07:15	ga_s2bm_ard_3-2-1_52LGL_2018-07-04_final.stac-item
2018-07-04 11:07:15	ga_s2bm_ard_3-2-1_52LGM_2018-07-04_final.stac-item
2018-07-04 11:07:15	ga_s2bm_ard_3-2-1_52LGN_2018-07-04_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JFR_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JFS_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JFT_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JGS_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52JGT_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52KFA_2018-07-11_final.stac-item
2018-07-11 11:03:18	ga_s2bm_ard_3-2-1_52KFU_2018-07-11_final.stac-item
2018-07-14 11:07:11	ga_s2bm_ard_3-2-1_52LGJ_2018-07-14_final.stac-item
2018-07-14 11:07:11	ga_s2bm_ard_3-2-1_52LGK_2018-07-14_final.stac-item
2018-07-14 11:07:11	ga_s2bm_ard_3-2-1_52LGL_2018-07-14_final.stac-item
2018-07-14 11:07:11	ga_s2bm_ard_3-2-1_52LGM_2018-07-14_final.stac-item
2018-07-14 11:07:11	ga_s2bm_ard_3-2-1_52LGN_2018-07-14_final.stac-item
2018-07-14 11:11:20	ga_s2bm_ard_3-2-1_52LGH_2018-07-14_final.stac-item
2018-07-14 11:11:20	ga_s2bm_ard_3-2-1_52LGJ_2018-07-14_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JFS_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JFT_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JGS_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JGT_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFA_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFB_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFC_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFD_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFE_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFU_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KFV_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGA_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGB_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGC_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGD_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGE_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGF_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGG_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGU_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52KGV_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52LGH_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52LGJ_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JFR_2018-10-19_final.stac-item
2019-06-03 10:54:23	ga_s2bm_ard_3-2-1_52JGT_2019-06-03_final.stac-item
2019-06-03 10:54:29	ga_s2bm_ard_3-2-1_52JFT_2019-06-03_final.stac-item
2019-06-03 10:54:38	ga_s2bm_ard_3-2-1_52JGS_2019-06-03_final.stac-item
2019-06-03 10:54:41	ga_s2bm_ard_3-2-1_52JFS_2019-06-03_final.stac-item
2019-06-03 10:54:56	ga_s2bm_ard_3-2-1_52JFR_2019-06-03_final.stac-item
2019-06-03 10:55:10	ga_s2bm_ard_3-2-1_52JFQ_2019-06-03_final.stac-item
2019-06-03 10:55:25	ga_s2bm_ard_3-2-1_52JFP_2019-06-03_final.stac-item
2019-06-03 10:55:39	ga_s2bm_ard_3-2-1_52JFN_2019-06-03_final.stac-item
2019-06-03 10:55:54	ga_s2bm_ard_3-2-1_52JFM_2019-06-03_final.stac-item
2019-06-03 10:56:08	ga_s2bm_ard_3-2-1_52JFL_2019-06-03_final.stac-item
2019-06-13 10:54:23	ga_s2bm_ard_3-2-1_52JGT_2019-06-13_final.stac-item
2019-06-13 10:54:28	ga_s2bm_ard_3-2-1_52JFT_2019-06-13_final.stac-item
2019-06-13 10:54:37	ga_s2bm_ard_3-2-1_52JGS_2019-06-13_final.stac-item
2019-06-13 10:54:40	ga_s2bm_ard_3-2-1_52JFS_2019-06-13_final.stac-item
2019-06-13 10:54:55	ga_s2bm_ard_3-2-1_52JFR_2019-06-13_final.stac-item
2019-06-13 10:55:09	ga_s2bm_ard_3-2-1_52JFQ_2019-06-13_final.stac-item
2019-06-13 10:55:24	ga_s2bm_ard_3-2-1_52JFP_2019-06-13_final.stac-item
2019-06-13 10:55:38	ga_s2bm_ard_3-2-1_52JFN_2019-06-13_final.stac-item
2019-06-13 10:55:53	ga_s2bm_ard_3-2-1_52JFM_2019-06-13_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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