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
2019-10-19 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2019-10-19_final.stac-item
2019-10-20 09:41:43	ga_s2bm_ard_3-2-1_56KLF_2019-10-20_final.stac-item
2019-10-20 09:41:46	ga_s2bm_ard_3-2-1_56KKF_2019-10-20_final.stac-item
2019-10-20 09:41:57	ga_s2bm_ard_3-2-1_56KLE_2019-10-20_final.stac-item
2019-10-20 09:42:12	ga_s2bm_ard_3-2-1_56KLD_2019-10-20_final.stac-item
2019-10-20 09:42:34	ga_s2bm_ard_3-2-1_55KGT_2019-10-20_final.stac-item
2019-10-20 09:42:41	ga_s2bm_ard_3-2-1_56KLB_2019-10-20_final.stac-item
2019-10-20 09:42:44	ga_s2bm_ard_3-2-1_56KKB_2019-10-20_final.stac-item
2019-10-20 09:42:44	ga_s2bm_ard_3-2-1_55KHS_2019-10-20_final.stac-item
2019-10-20 09:42:48	ga_s2bm_ard_3-2-1_55KGS_2019-10-20_final.stac-item
2019-10-20 09:42:51	ga_s2bm_ard_3-2-1_56KMA_2019-10-20_final.stac-item
2019-10-20 09:42:55	ga_s2bm_ard_3-2-1_56KLA_2019-10-20_final.stac-item
2019-10-20 09:42:58	ga_s2bm_ard_3-2-1_56KKA_2019-10-20_final.stac-item
2019-10-20 09:42:59	ga_s2bm_ard_3-2-1_55KHR_2019-10-20_final.stac-item
2019-10-20 09:43:02	ga_s2bm_ard_3-2-1_55KGR_2019-10-20_final.stac-item
2019-10-20 09:43:10	ga_s2bm_ard_3-2-1_56KLV_2019-10-20_final.stac-item
2019-10-20 09:43:13	ga_s2bm_ard_3-2-1_56KKV_2019-10-20_final.stac-item
2019-10-20 09:43:13	ga_s2bm_ard_3-2-1_55KHQ_2019-10-20_final.stac-item
2019-10-20 09:43:17	ga_s2bm_ard_3-2-1_55KGQ_2019-10-20_final.stac-item
2019-10-20 09:43:24	ga_s2bm_ard_3-2-1_56KLU_2019-10-20_final.stac-item
2019-10-20 09:43:28	ga_s2bm_ard_3-2-1_56KKU_2019-10-20_final.stac-item
2019-10-20 09:43:28	ga_s2bm_ard_3-2-1_55KHP_2019-10-20_final.stac-item
2019-10-20 09:43:31	ga_s2bm_ard_3-2-1_55KGP_2019-10-20_final.stac-item
2019-10-20 09:43:36	ga_s2bm_ard_3-2-1_55KFP_2019-10-20_final.stac-item
2019-10-20 09:43:39	ga_s2bm_ard_3-2-1_56JLT_2019-10-20_final.stac-item
2019-10-20 09:43:42	ga_s2bm_ard_3-2-1_55JHN_2019-10-20_final.stac-item
2019-10-20 09:43:42	ga_s2bm_ard_3-2-1_56JKT_2019-10-20_final.stac-item
2019-10-20 09:43:46	ga_s2bm_ard_3-2-1_55JGN_2019-10-20_final.stac-item
2019-10-20 09:43:49	ga_s2bm_ard_3-2-1_55JFN_2019-10-20_final.stac-item
2019-10-20 09:43:53	ga_s2bm_ard_3-2-1_56JLS_2019-10-20_final.stac-item
2019-10-20 09:43:57	ga_s2bm_ard_3-2-1_55JHM_2019-10-20_final.stac-item
2019-10-20 09:43:57	ga_s2bm_ard_3-2-1_56JKS_2019-10-20_final.stac-item
2019-10-20 09:44:00	ga_s2bm_ard_3-2-1_55JGM_2019-10-20_final.stac-item
2019-10-20 09:44:04	ga_s2bm_ard_3-2-1_55JFM_2019-10-20_final.stac-item
2019-10-20 09:44:07	ga_s2bm_ard_3-2-1_56JLR_2019-10-20_final.stac-item
2019-10-20 09:44:11	ga_s2bm_ard_3-2-1_56JKR_2019-10-20_final.stac-item
2019-10-20 09:44:15	ga_s2bm_ard_3-2-1_55JGL_2019-10-20_final.stac-item
2019-10-20 09:44:17	ga_s2bm_ard_3-2-1_56JLQ_2019-10-20_final.stac-item
2019-10-20 09:44:18	ga_s2bm_ard_3-2-1_55JFL_2019-10-20_final.stac-item
2019-10-20 09:44:26	ga_s2bm_ard_3-2-1_56JKQ_2019-10-20_final.stac-item
2019-10-20 09:44:26	ga_s2bm_ard_3-2-1_55JEL_2019-10-20_final.stac-item
2019-10-20 09:44:29	ga_s2bm_ard_3-2-1_55JGK_2019-10-20_final.stac-item
2019-10-20 09:44:33	ga_s2bm_ard_3-2-1_55JFK_2019-10-20_final.stac-item
2019-10-20 09:44:37	ga_s2bm_ard_3-2-1_55JEK_2019-10-20_final.stac-item
2019-10-20 09:44:40	ga_s2bm_ard_3-2-1_56JKP_2019-10-20_final.stac-item
2019-10-20 09:44:44	ga_s2bm_ard_3-2-1_55JGJ_2019-10-20_final.stac-item
2019-10-20 09:44:47	ga_s2bm_ard_3-2-1_55JFJ_2019-10-20_final.stac-item
2019-10-20 09:44:50	ga_s2bm_ard_3-2-1_55JEJ_2019-10-20_final.stac-item
2019-10-20 09:44:55	ga_s2bm_ard_3-2-1_56JKN_2019-10-20_final.stac-item
2019-10-20 09:44:58	ga_s2bm_ard_3-2-1_55JGH_2019-10-20_final.stac-item
2019-10-20 09:45:02	ga_s2bm_ard_3-2-1_55JFH_2019-10-20_final.stac-item
2019-10-20 09:45:05	ga_s2bm_ard_3-2-1_55JEH_2019-10-20_final.stac-item
2019-10-20 09:45:10	ga_s2bm_ard_3-2-1_56JKM_2019-10-20_final.stac-item
2019-10-20 09:45:12	ga_s2bm_ard_3-2-1_55JGG_2019-10-20_final.stac-item
2019-10-20 09:45:16	ga_s2bm_ard_3-2-1_55JFG_2019-10-20_final.stac-item
2019-10-20 09:45:20	ga_s2bm_ard_3-2-1_55JEG_2019-10-20_final.stac-item
2019-10-20 09:45:23	ga_s2bm_ard_3-2-1_56JKL_2019-10-20_final.stac-item
2019-10-20 09:45:27	ga_s2bm_ard_3-2-1_55JGF_2019-10-20_final.stac-item
2019-10-20 09:45:27	ga_s2bm_ard_3-2-1_55JDG_2019-10-20_final.stac-item
2019-10-20 09:45:31	ga_s2bm_ard_3-2-1_55JFF_2019-10-20_final.stac-item
2019-10-20 09:45:34	ga_s2bm_ard_3-2-1_56HKK_2019-10-20_final.stac-item
2019-10-20 09:45:34	ga_s2bm_ard_3-2-1_55JEF_2019-10-20_final.stac-item
2019-10-20 09:45:38	ga_s2bm_ard_3-2-1_55JDF_2019-10-20_final.stac-item
2019-10-20 09:45:41	ga_s2bm_ard_3-2-1_55HGE_2019-10-20_final.stac-item
2019-10-20 09:45:45	ga_s2bm_ard_3-2-1_55HFE_2019-10-20_final.stac-item
2019-10-20 09:45:49	ga_s2bm_ard_3-2-1_55HEE_2019-10-20_final.stac-item
2019-10-20 09:45:52	ga_s2bm_ard_3-2-1_55HDE_2019-10-20_final.stac-item
2019-10-20 09:45:56	ga_s2bm_ard_3-2-1_55HGD_2019-10-20_final.stac-item
2019-10-20 09:46:00	ga_s2bm_ard_3-2-1_55HFD_2019-10-20_final.stac-item
2019-10-20 09:46:03	ga_s2bm_ard_3-2-1_55HED_2019-10-20_final.stac-item
2019-10-20 09:46:07	ga_s2bm_ard_3-2-1_55HDD_2019-10-20_final.stac-item
2019-10-20 09:46:08	ga_s2bm_ard_3-2-1_55HGC_2019-10-20_final.stac-item
2019-10-20 09:46:14	ga_s2bm_ard_3-2-1_55HFC_2019-10-20_final.stac-item
2019-10-20 09:46:18	ga_s2bm_ard_3-2-1_55HEC_2019-10-20_final.stac-item
2019-10-20 09:46:18	ga_s2bm_ard_3-2-1_55HGB_2019-10-20_final.stac-item
2019-10-20 09:46:21	ga_s2bm_ard_3-2-1_55HDC_2019-10-20_final.stac-item
2019-10-20 09:46:28	ga_s2bm_ard_3-2-1_55HFB_2019-10-20_final.stac-item
2019-10-20 11:22:02	ga_s2bm_ard_3-2-1_52KDG_2019-10-20_final.stac-item
2019-10-20 11:22:06	ga_s2bm_ard_3-2-1_52KCG_2019-10-20_final.stac-item
2019-10-20 11:22:09	ga_s2bm_ard_3-2-1_52KBG_2019-10-20_final.stac-item
2019-10-20 11:22:14	ga_s2bm_ard_3-2-1_52KDF_2019-10-20_final.stac-item
2019-10-20 11:22:20	ga_s2bm_ard_3-2-1_52KCF_2019-10-20_final.stac-item
2019-10-20 11:22:24	ga_s2bm_ard_3-2-1_52KBF_2019-10-20_final.stac-item
2019-10-20 11:22:35	ga_s2bm_ard_3-2-1_52KCE_2019-10-20_final.stac-item
2019-10-20 11:22:38	ga_s2bm_ard_3-2-1_52KBE_2019-10-20_final.stac-item
2019-10-20 11:22:49	ga_s2bm_ard_3-2-1_52KCD_2019-10-20_final.stac-item
2019-10-20 11:22:53	ga_s2bm_ard_3-2-1_52KBD_2019-10-20_final.stac-item
2019-10-20 11:23:04	ga_s2bm_ard_3-2-1_52KCC_2019-10-20_final.stac-item
2019-10-20 11:23:07	ga_s2bm_ard_3-2-1_52KBC_2019-10-20_final.stac-item
2019-10-20 11:23:17	ga_s2bm_ard_3-2-1_52KCB_2019-10-20_final.stac-item
2019-10-20 11:23:22	ga_s2bm_ard_3-2-1_52KBB_2019-10-20_final.stac-item
2019-10-20 11:23:29	ga_s2bm_ard_3-2-1_52KCA_2019-10-20_final.stac-item
2019-10-20 11:23:36	ga_s2bm_ard_3-2-1_52KBA_2019-10-20_final.stac-item
2019-10-20 11:23:51	ga_s2bm_ard_3-2-1_52KBV_2019-10-20_final.stac-item
2019-10-20 11:24:03	ga_s2bm_ard_3-2-1_51KWQ_2019-10-20_final.stac-item
2019-10-20 11:24:05	ga_s2bm_ard_3-2-1_52KBU_2019-10-20_final.stac-item
2019-10-20 11:24:13	ga_s2bm_ard_3-2-1_51KXP_2019-10-20_final.stac-item
2019-10-20 11:24:16	ga_s2bm_ard_3-2-1_51KWP_2019-10-20_final.stac-item
2019-10-20 11:24:20	ga_s2bm_ard_3-2-1_51JZN_2019-10-20_final.stac-item
2019-10-20 11:24:20	ga_s2bm_ard_3-2-1_52JBT_2019-10-20_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

All years