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
2019-04-30 11:11:09	ga_s2bm_ard_3-2-1_52LFL_2019-04-30_final.stac-item
2019-04-30 11:11:23	ga_s2bm_ard_3-2-1_52LFK_2019-04-30_final.stac-item
2019-04-30 11:11:38	ga_s2bm_ard_3-2-1_52LFJ_2019-04-30_final.stac-item
2019-04-30 11:11:41	ga_s2bm_ard_3-2-1_52LEJ_2019-04-30_final.stac-item
2019-04-30 11:11:52	ga_s2bm_ard_3-2-1_52LFH_2019-04-30_final.stac-item
2019-04-30 11:11:56	ga_s2bm_ard_3-2-1_52LEH_2019-04-30_final.stac-item
2019-04-30 11:12:06	ga_s2bm_ard_3-2-1_52KFG_2019-04-30_final.stac-item
2019-04-30 11:12:10	ga_s2bm_ard_3-2-1_52KEG_2019-04-30_final.stac-item
2019-04-30 11:12:21	ga_s2bm_ard_3-2-1_52KFF_2019-04-30_final.stac-item
2019-04-30 11:12:25	ga_s2bm_ard_3-2-1_52KEF_2019-04-30_final.stac-item
2019-04-30 11:12:36	ga_s2bm_ard_3-2-1_52KFE_2019-04-30_final.stac-item
2019-04-30 11:12:39	ga_s2bm_ard_3-2-1_52KEE_2019-04-30_final.stac-item
2019-04-30 11:12:49	ga_s2bm_ard_3-2-1_52KFD_2019-04-30_final.stac-item
2019-04-30 11:12:54	ga_s2bm_ard_3-2-1_52KED_2019-04-30_final.stac-item
2019-04-30 11:13:01	ga_s2bm_ard_3-2-1_52KFC_2019-04-30_final.stac-item
2019-04-30 11:13:08	ga_s2bm_ard_3-2-1_52KEC_2019-04-30_final.stac-item
2019-05-07 11:02:41	ga_s2bm_ard_3-2-1_52KFE_2019-05-07_final.stac-item
2019-05-07 11:02:56	ga_s2bm_ard_3-2-1_52KFD_2019-05-07_final.stac-item
2019-05-07 11:03:00	ga_s2bm_ard_3-2-1_52KED_2019-05-07_final.stac-item
2019-05-07 11:03:10	ga_s2bm_ard_3-2-1_52KFC_2019-05-07_final.stac-item
2019-05-07 11:03:13	ga_s2bm_ard_3-2-1_52KEC_2019-05-07_final.stac-item
2019-05-07 11:03:25	ga_s2bm_ard_3-2-1_52KFB_2019-05-07_final.stac-item
2019-05-07 11:03:28	ga_s2bm_ard_3-2-1_52KEB_2019-05-07_final.stac-item
2019-05-07 11:03:39	ga_s2bm_ard_3-2-1_52KFA_2019-05-07_final.stac-item
2019-05-07 11:03:43	ga_s2bm_ard_3-2-1_52KEA_2019-05-07_final.stac-item
2019-05-07 11:03:57	ga_s2bm_ard_3-2-1_52KEV_2019-05-07_final.stac-item
2019-05-07 11:04:11	ga_s2bm_ard_3-2-1_52KEU_2019-05-07_final.stac-item
2019-05-07 11:04:26	ga_s2bm_ard_3-2-1_52JET_2019-05-07_final.stac-item
2019-05-07 11:04:41	ga_s2bm_ard_3-2-1_52JES_2019-05-07_final.stac-item
2019-05-07 11:04:55	ga_s2bm_ard_3-2-1_52JER_2019-05-07_final.stac-item
2019-05-07 11:05:10	ga_s2bm_ard_3-2-1_52JEQ_2019-05-07_final.stac-item
2019-05-10 11:11:10	ga_s2bm_ard_3-2-1_52LFL_2019-05-10_final.stac-item
2019-05-10 11:11:24	ga_s2bm_ard_3-2-1_52LFK_2019-05-10_final.stac-item
2019-05-10 11:11:39	ga_s2bm_ard_3-2-1_52LFJ_2019-05-10_final.stac-item
2019-05-10 11:11:42	ga_s2bm_ard_3-2-1_52LEJ_2019-05-10_final.stac-item
2019-05-10 11:11:53	ga_s2bm_ard_3-2-1_52LFH_2019-05-10_final.stac-item
2019-05-10 11:11:57	ga_s2bm_ard_3-2-1_52LEH_2019-05-10_final.stac-item
2019-05-10 11:12:07	ga_s2bm_ard_3-2-1_52KFG_2019-05-10_final.stac-item
2019-05-10 11:12:11	ga_s2bm_ard_3-2-1_52KEG_2019-05-10_final.stac-item
2019-05-10 11:12:22	ga_s2bm_ard_3-2-1_52KFF_2019-05-10_final.stac-item
2019-05-10 11:12:26	ga_s2bm_ard_3-2-1_52KEF_2019-05-10_final.stac-item
2019-05-10 11:12:37	ga_s2bm_ard_3-2-1_52KFE_2019-05-10_final.stac-item
2019-05-10 11:12:40	ga_s2bm_ard_3-2-1_52KEE_2019-05-10_final.stac-item
2019-05-10 11:12:50	ga_s2bm_ard_3-2-1_52KFD_2019-05-10_final.stac-item
2019-05-10 11:12:55	ga_s2bm_ard_3-2-1_52KED_2019-05-10_final.stac-item
2019-05-10 11:13:02	ga_s2bm_ard_3-2-1_52KFC_2019-05-10_final.stac-item
2019-05-10 11:13:09	ga_s2bm_ard_3-2-1_52KEC_2019-05-10_final.stac-item
2019-11-06 11:11:01	ga_s2bm_ard_3-2-1_52LFL_2019-11-06_final.stac-item
2019-11-06 11:11:16	ga_s2bm_ard_3-2-1_52LFK_2019-11-06_final.stac-item
2019-11-06 11:11:30	ga_s2bm_ard_3-2-1_52LFJ_2019-11-06_final.stac-item
2019-11-06 11:11:34	ga_s2bm_ard_3-2-1_52LEJ_2019-11-06_final.stac-item
2019-11-06 11:11:45	ga_s2bm_ard_3-2-1_52LFH_2019-11-06_final.stac-item
2019-11-06 11:11:48	ga_s2bm_ard_3-2-1_52LEH_2019-11-06_final.stac-item
2019-11-06 11:11:59	ga_s2bm_ard_3-2-1_52KFG_2019-11-06_final.stac-item
2019-11-06 11:12:03	ga_s2bm_ard_3-2-1_52KEG_2019-11-06_final.stac-item
2019-11-06 11:12:14	ga_s2bm_ard_3-2-1_52KFF_2019-11-06_final.stac-item
2019-11-06 11:12:17	ga_s2bm_ard_3-2-1_52KEF_2019-11-06_final.stac-item
2019-11-06 11:12:28	ga_s2bm_ard_3-2-1_52KFE_2019-11-06_final.stac-item
2019-11-06 11:12:32	ga_s2bm_ard_3-2-1_52KEE_2019-11-06_final.stac-item
2019-11-06 11:12:42	ga_s2bm_ard_3-2-1_52KFD_2019-11-06_final.stac-item
2019-11-06 11:12:46	ga_s2bm_ard_3-2-1_52KED_2019-11-06_final.stac-item
2019-11-06 11:12:54	ga_s2bm_ard_3-2-1_52KFC_2019-11-06_final.stac-item
2019-11-06 11:13:01	ga_s2bm_ard_3-2-1_52KEC_2019-11-06_final.stac-item
2019-11-10 10:55:22	ga_s2bm_ard_3-2-1_52JEP_2019-11-10_final.stac-item
2019-11-10 10:55:34	ga_s2bm_ard_3-2-1_52JEN_2019-11-10_final.stac-item
2019-11-10 10:55:48	ga_s2bm_ard_3-2-1_52JEM_2019-11-10_final.stac-item
2019-11-10 10:56:03	ga_s2bm_ard_3-2-1_52JEL_2019-11-10_final.stac-item
2019-11-13 11:02:32	ga_s2bm_ard_3-2-1_52KFE_2019-11-13_final.stac-item
2019-11-13 11:02:46	ga_s2bm_ard_3-2-1_52KFD_2019-11-13_final.stac-item
2019-11-13 11:02:51	ga_s2bm_ard_3-2-1_52KED_2019-11-13_final.stac-item
2019-11-13 11:03:00	ga_s2bm_ard_3-2-1_52KFC_2019-11-13_final.stac-item
2019-11-13 11:03:02	ga_s2bm_ard_3-2-1_52KEC_2019-11-13_final.stac-item
2019-11-13 11:03:07	ga_s2bm_ard_3-2-1_52KFC_2019-11-13_final.stac-item
2019-11-13 11:03:08	ga_s2bm_ard_3-2-1_52KEC_2019-11-13_final.stac-item
2019-11-13 11:03:16	ga_s2bm_ard_3-2-1_52KFB_2019-11-13_final.stac-item
2019-11-13 11:03:19	ga_s2bm_ard_3-2-1_52KEB_2019-11-13_final.stac-item
2019-11-13 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2019-11-13_final.stac-item
2019-11-13 11:03:33	ga_s2bm_ard_3-2-1_52KEA_2019-11-13_final.stac-item
2019-11-13 11:03:48	ga_s2bm_ard_3-2-1_52KEV_2019-11-13_final.stac-item
2019-11-13 11:04:02	ga_s2bm_ard_3-2-1_52KEU_2019-11-13_final.stac-item
2019-11-13 11:04:17	ga_s2bm_ard_3-2-1_52JET_2019-11-13_final.stac-item
2019-11-13 11:04:31	ga_s2bm_ard_3-2-1_52JES_2019-11-13_final.stac-item
2019-11-13 11:04:46	ga_s2bm_ard_3-2-1_52JER_2019-11-13_final.stac-item
2019-11-13 11:05:00	ga_s2bm_ard_3-2-1_52JEQ_2019-11-13_final.stac-item
2019-11-13 11:05:15	ga_s2bm_ard_3-2-1_52JEP_2019-11-13_final.stac-item
2019-11-13 11:05:29	ga_s2bm_ard_3-2-1_52JEN_2019-11-13_final.stac-item
2019-11-13 11:05:44	ga_s2bm_ard_3-2-1_52JEM_2019-11-13_final.stac-item
2019-11-13 11:05:58	ga_s2bm_ard_3-2-1_52JEL_2019-11-13_final.stac-item
2019-11-16 11:12:01	ga_s2bm_ard_3-2-1_52KEG_2019-11-16_final.stac-item
2019-11-16 11:12:16	ga_s2bm_ard_3-2-1_52KEF_2019-11-16_final.stac-item
2019-11-16 11:12:30	ga_s2bm_ard_3-2-1_52KEE_2019-11-16_final.stac-item
2019-11-16 11:12:45	ga_s2bm_ard_3-2-1_52KED_2019-11-16_final.stac-item
2019-11-16 11:12:59	ga_s2bm_ard_3-2-1_52KEC_2019-11-16_final.stac-item
2019-11-23 11:05:13	ga_s2bm_ard_3-2-1_52JEP_2019-11-23_final.stac-item
2019-11-23 11:05:27	ga_s2bm_ard_3-2-1_52JEN_2019-11-23_final.stac-item
2019-11-23 11:05:42	ga_s2bm_ard_3-2-1_52JEM_2019-11-23_final.stac-item
2019-11-23 11:05:56	ga_s2bm_ard_3-2-1_52JEL_2019-11-23_final.stac-item
2019-11-30 10:55:18	ga_s2bm_ard_3-2-1_52JEP_2019-11-30_final.stac-item
2019-11-30 10:55:30	ga_s2bm_ard_3-2-1_52JEN_2019-11-30_final.stac-item
2019-11-30 10:55:44	ga_s2bm_ard_3-2-1_52JEM_2019-11-30_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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