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
2019-08-08 09:34:33	ga_s2bm_ard_3-2-1_56JLQ_2019-08-08_final.stac-item
2019-08-08 09:34:36	ga_s2bm_ard_3-2-1_56JKQ_2019-08-08_final.stac-item
2019-08-08 09:34:44	ga_s2bm_ard_3-2-1_56JMP_2019-08-08_final.stac-item
2019-08-08 09:34:48	ga_s2bm_ard_3-2-1_56JLP_2019-08-08_final.stac-item
2019-08-08 09:34:51	ga_s2bm_ard_3-2-1_56JNN_2019-08-08_final.stac-item
2019-08-08 09:34:51	ga_s2bm_ard_3-2-1_56JKP_2019-08-08_final.stac-item
2019-08-08 09:34:57	ga_s2bm_ard_3-2-1_55JGJ_2019-08-08_final.stac-item
2019-08-08 09:34:59	ga_s2bm_ard_3-2-1_56JMN_2019-08-08_final.stac-item
2019-08-08 09:35:02	ga_s2bm_ard_3-2-1_56JLN_2019-08-08_final.stac-item
2019-08-08 09:35:06	ga_s2bm_ard_3-2-1_56JKN_2019-08-08_final.stac-item
2019-08-08 09:35:09	ga_s2bm_ard_3-2-1_55JGH_2019-08-08_final.stac-item
2019-08-08 09:35:13	ga_s2bm_ard_3-2-1_56JMM_2019-08-08_final.stac-item
2019-08-08 09:35:17	ga_s2bm_ard_3-2-1_56JLM_2019-08-08_final.stac-item
2019-08-08 09:35:20	ga_s2bm_ard_3-2-1_56JKM_2019-08-08_final.stac-item
2019-08-08 09:35:22	ga_s2bm_ard_3-2-1_55JGG_2019-08-08_final.stac-item
2019-08-08 09:35:28	ga_s2bm_ard_3-2-1_56JML_2019-08-08_final.stac-item
2019-08-08 09:35:31	ga_s2bm_ard_3-2-1_56JLL_2019-08-08_final.stac-item
2019-08-08 09:35:35	ga_s2bm_ard_3-2-1_56JKL_2019-08-08_final.stac-item
2019-08-08 09:35:37	ga_s2bm_ard_3-2-1_55JGF_2019-08-08_final.stac-item
2019-08-08 09:35:42	ga_s2bm_ard_3-2-1_56HMK_2019-08-08_final.stac-item
2019-08-08 09:35:46	ga_s2bm_ard_3-2-1_56HLK_2019-08-08_final.stac-item
2019-08-08 09:35:49	ga_s2bm_ard_3-2-1_56HKK_2019-08-08_final.stac-item
2019-08-08 09:35:52	ga_s2bm_ard_3-2-1_55HGE_2019-08-08_final.stac-item
2019-08-08 09:35:55	ga_s2bm_ard_3-2-1_56HMJ_2019-08-08_final.stac-item
2019-08-08 09:35:57	ga_s2bm_ard_3-2-1_55HFE_2019-08-08_final.stac-item
2019-08-08 09:36:00	ga_s2bm_ard_3-2-1_56HLJ_2019-08-08_final.stac-item
2019-08-08 09:36:04	ga_s2bm_ard_3-2-1_56HKJ_2019-08-08_final.stac-item
2019-08-08 09:36:06	ga_s2bm_ard_3-2-1_55HGD_2019-08-08_final.stac-item
2019-08-08 09:36:09	ga_s2bm_ard_3-2-1_55HFD_2019-08-08_final.stac-item
2019-08-08 09:36:19	ga_s2bm_ard_3-2-1_56HKH_2019-08-08_final.stac-item
2019-08-08 09:36:20	ga_s2bm_ard_3-2-1_55HGC_2019-08-08_final.stac-item
2019-08-08 09:36:24	ga_s2bm_ard_3-2-1_55HFC_2019-08-08_final.stac-item
2019-08-08 09:36:33	ga_s2bm_ard_3-2-1_56HKG_2019-08-08_final.stac-item
2019-08-08 09:36:35	ga_s2bm_ard_3-2-1_55HGB_2019-08-08_final.stac-item
2019-08-08 09:36:39	ga_s2bm_ard_3-2-1_55HFB_2019-08-08_final.stac-item
2019-08-08 09:36:48	ga_s2bm_ard_3-2-1_56HKF_2019-08-08_final.stac-item
2019-08-08 09:36:49	ga_s2bm_ard_3-2-1_55HGA_2019-08-08_final.stac-item
2019-08-08 09:36:53	ga_s2bm_ard_3-2-1_55HFA_2019-08-08_final.stac-item
2019-08-08 09:36:58	ga_s2bm_ard_3-2-1_55HEA_2019-08-08_final.stac-item
2019-08-08 09:37:03	ga_s2bm_ard_3-2-1_55HGV_2019-08-08_final.stac-item
2019-08-08 09:37:07	ga_s2bm_ard_3-2-1_55HFV_2019-08-08_final.stac-item
2019-08-08 09:37:11	ga_s2bm_ard_3-2-1_55HEV_2019-08-08_final.stac-item
2019-08-08 09:37:26	ga_s2bm_ard_3-2-1_55HEU_2019-08-08_final.stac-item
2019-08-08 09:37:40	ga_s2bm_ard_3-2-1_55HET_2019-08-08_final.stac-item
2019-08-08 09:37:47	ga_s2bm_ard_3-2-1_55HDT_2019-08-08_final.stac-item
2019-08-08 09:37:53	ga_s2bm_ard_3-2-1_55HES_2019-08-08_final.stac-item
2019-08-08 09:37:56	ga_s2bm_ard_3-2-1_55HDS_2019-08-08_final.stac-item
2019-08-08 09:37:58	ga_s2bm_ard_3-2-1_55GFR_2019-08-08_final.stac-item
2019-08-08 09:38:00	ga_s2bm_ard_3-2-1_55GER_2019-08-08_final.stac-item
2019-08-08 09:38:00	ga_s2bm_ard_3-2-1_55HES_2019-08-08_final.stac-item
2019-08-08 09:38:02	ga_s2bm_ard_3-2-1_55HDS_2019-08-08_final.stac-item
2019-08-08 09:38:06	ga_s2bm_ard_3-2-1_55GFR_2019-08-08_final.stac-item
2019-08-08 09:38:09	ga_s2bm_ard_3-2-1_55GER_2019-08-08_final.stac-item
2019-08-08 09:38:12	ga_s2bm_ard_3-2-1_55GDR_2019-08-08_final.stac-item
2019-08-08 09:38:19	ga_s2bm_ard_3-2-1_55GFQ_2019-08-08_final.stac-item
2019-08-08 09:38:23	ga_s2bm_ard_3-2-1_55GEQ_2019-08-08_final.stac-item
2019-08-08 09:38:27	ga_s2bm_ard_3-2-1_55GDQ_2019-08-08_final.stac-item
2019-08-08 09:38:34	ga_s2bm_ard_3-2-1_55GFP_2019-08-08_final.stac-item
2019-08-08 09:38:38	ga_s2bm_ard_3-2-1_55GEP_2019-08-08_final.stac-item
2019-08-08 09:38:42	ga_s2bm_ard_3-2-1_55GDP_2019-08-08_final.stac-item
2019-08-08 09:38:47	ga_s2bm_ard_3-2-1_55GCP_2019-08-08_final.stac-item
2019-08-08 09:38:48	ga_s2bm_ard_3-2-1_55GFN_2019-08-08_final.stac-item
2019-08-08 09:38:52	ga_s2bm_ard_3-2-1_55GEN_2019-08-08_final.stac-item
2019-08-08 09:38:56	ga_s2bm_ard_3-2-1_55GDN_2019-08-08_final.stac-item
2019-08-08 09:39:00	ga_s2bm_ard_3-2-1_55GCN_2019-08-08_final.stac-item
2019-08-08 11:12:06	ga_s2bm_ard_3-2-1_52KFG_2019-08-08_final.stac-item
2019-08-08 11:12:10	ga_s2bm_ard_3-2-1_52KEG_2019-08-08_final.stac-item
2019-08-08 11:12:13	ga_s2bm_ard_3-2-1_52KDG_2019-08-08_final.stac-item
2019-08-08 11:12:18	ga_s2bm_ard_3-2-1_52KCG_2019-08-08_final.stac-item
2019-08-08 11:12:21	ga_s2bm_ard_3-2-1_52KFF_2019-08-08_final.stac-item
2019-08-08 11:12:24	ga_s2bm_ard_3-2-1_52KEF_2019-08-08_final.stac-item
2019-08-08 11:12:28	ga_s2bm_ard_3-2-1_52KDF_2019-08-08_final.stac-item
2019-08-08 11:12:31	ga_s2bm_ard_3-2-1_52KCF_2019-08-08_final.stac-item
2019-08-08 11:12:36	ga_s2bm_ard_3-2-1_52KFE_2019-08-08_final.stac-item
2019-08-08 11:12:39	ga_s2bm_ard_3-2-1_52KEE_2019-08-08_final.stac-item
2019-08-08 11:12:42	ga_s2bm_ard_3-2-1_52KDE_2019-08-08_final.stac-item
2019-08-08 11:12:45	ga_s2bm_ard_3-2-1_52KCE_2019-08-08_final.stac-item
2019-08-08 11:12:49	ga_s2bm_ard_3-2-1_52KFD_2019-08-08_final.stac-item
2019-08-08 11:12:53	ga_s2bm_ard_3-2-1_52KED_2019-08-08_final.stac-item
2019-08-08 11:12:57	ga_s2bm_ard_3-2-1_52KDD_2019-08-08_final.stac-item
2019-08-08 11:13:00	ga_s2bm_ard_3-2-1_52KCD_2019-08-08_final.stac-item
2019-08-08 11:13:01	ga_s2bm_ard_3-2-1_52KFC_2019-08-08_final.stac-item
2019-08-08 11:13:08	ga_s2bm_ard_3-2-1_52KEC_2019-08-08_final.stac-item
2019-08-08 11:13:11	ga_s2bm_ard_3-2-1_52KDC_2019-08-08_final.stac-item
2019-08-08 11:13:15	ga_s2bm_ard_3-2-1_52KCC_2019-08-08_final.stac-item
2019-08-08 11:13:21	ga_s2bm_ard_3-2-1_52KBC_2019-08-08_final.stac-item
2019-08-08 11:13:22	ga_s2bm_ard_3-2-1_52KEB_2019-08-08_final.stac-item
2019-08-08 11:13:26	ga_s2bm_ard_3-2-1_52KDB_2019-08-08_final.stac-item
2019-08-08 11:13:29	ga_s2bm_ard_3-2-1_52KCB_2019-08-08_final.stac-item
2019-08-08 11:13:33	ga_s2bm_ard_3-2-1_52KBB_2019-08-08_final.stac-item
2019-08-08 11:13:36	ga_s2bm_ard_3-2-1_52KEA_2019-08-08_final.stac-item
2019-08-08 11:13:37	ga_s2bm_ard_3-2-1_52KDA_2019-08-08_final.stac-item
2019-08-08 11:13:39	ga_s2bm_ard_3-2-1_52KCA_2019-08-08_final.stac-item
2019-08-08 11:13:40	ga_s2bm_ard_3-2-1_52KBA_2019-08-08_final.stac-item
2019-08-08 11:13:43	ga_s2bm_ard_3-2-1_52KEA_2019-08-08_final.stac-item
2019-08-08 11:13:44	ga_s2bm_ard_3-2-1_52KDA_2019-08-08_final.stac-item
2019-08-08 11:13:46	ga_s2bm_ard_3-2-1_52KCA_2019-08-08_final.stac-item
2019-08-08 11:13:47	ga_s2bm_ard_3-2-1_52KBA_2019-08-08_final.stac-item
2019-08-08 11:13:51	ga_s2bm_ard_3-2-1_52KEV_2019-08-08_final.stac-item
2019-08-08 11:13:55	ga_s2bm_ard_3-2-1_52KDV_2019-08-08_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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