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
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KVB_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KWA_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KWB_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KXA_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KXB_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KYA_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KYB_2017-11-22_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KVB_2017-12-02_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KWA_2017-12-02_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KWB_2017-12-02_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KXA_2017-12-02_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KXB_2017-12-02_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KYA_2017-12-02_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KYB_2017-12-02_final.stac-item
2017-12-12 09:50:53	ga_s2bm_ard_3-2-1_56KKF_2017-12-12_final.stac-item
2017-12-12 09:50:53	ga_s2bm_ard_3-2-1_55KFA_2017-12-12_final.stac-item
2017-12-12 09:50:53	ga_s2bm_ard_3-2-1_55KFB_2017-12-12_final.stac-item
2017-12-12 09:50:53	ga_s2bm_ard_3-2-1_55KGB_2017-12-12_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_56KKF_2017-12-22_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_55KFA_2017-12-22_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_55KFB_2017-12-22_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_55KGB_2017-12-22_final.stac-item
2018-03-20 10:51:09	ga_s2bm_ard_3-2-1_53KKA_2018-03-20_final.stac-item
2018-03-20 10:51:09	ga_s2bm_ard_3-2-1_53KKB_2018-03-20_final.stac-item
2020-04-06 11:52:17	ga_s2bm_ard_3-2-1_50KQG_2020-04-06_final
2020-04-06 11:52:31	ga_s2bm_ard_3-2-1_50KQF_2020-04-06_final
2020-04-06 11:52:34	ga_s2bm_ard_3-2-1_50KPF_2020-04-06_final
2020-04-23 11:42:04	ga_s2bm_ard_3-2-1_51KWB_2020-04-23_final.stac-item
2020-04-23 11:42:07	ga_s2bm_ard_3-2-1_51KVB_2020-04-23_final.stac-item
2020-04-23 11:42:11	ga_s2bm_ard_3-2-1_51KUB_2020-04-23_final
2020-04-23 11:42:22	ga_s2bm_ard_3-2-1_51KVA_2020-04-23_final.stac-item
2020-04-23 11:42:25	ga_s2bm_ard_3-2-1_51KUA_2020-04-23_final.stac-item
2023-04-26 11:01:53	ga_s2bm_ard_3-2-1_53KLB_2023-04-26_final
2023-04-26 11:01:58	ga_s2bm_ard_3-2-1_53KKB_2023-04-26_final
2023-04-26 11:01:59	ga_s2bm_ard_3-2-1_52KHG_2023-04-26_final
2023-04-26 11:02:02	ga_s2bm_ard_3-2-1_52KGG_2023-04-26_final
2023-04-26 11:02:05	ga_s2bm_ard_3-2-1_53KLA_2023-04-26_final
2023-04-26 11:02:05	ga_s2bm_ard_3-2-1_52KFG_2023-04-26_final
2023-04-26 11:02:12	ga_s2bm_ard_3-2-1_53KKA_2023-04-26_final
2023-04-26 11:02:13	ga_s2bm_ard_3-2-1_52KHF_2023-04-26_final
2023-04-26 11:02:17	ga_s2bm_ard_3-2-1_52KGF_2023-04-26_final
2023-04-26 11:02:20	ga_s2bm_ard_3-2-1_52KFF_2023-04-26_final
2023-04-27 10:31:44	ga_s2bm_ard_3-2-1_54KVG_2023-04-27_final
2023-04-27 10:31:47	ga_s2bm_ard_3-2-1_54KUG_2023-04-27_final
2023-04-27 10:31:50	ga_s2bm_ard_3-2-1_54KTG_2023-04-27_final
2023-04-27 10:31:52	ga_s2bm_ard_3-2-1_53KRB_2023-04-27_final
2023-04-27 10:31:58	ga_s2bm_ard_3-2-1_54KVF_2023-04-27_final
2023-04-27 10:32:02	ga_s2bm_ard_3-2-1_54KUF_2023-04-27_final
2023-04-27 10:32:05	ga_s2bm_ard_3-2-1_54KTF_2023-04-27_final
2023-04-27 10:32:06	ga_s2bm_ard_3-2-1_53KRA_2023-04-27_final
2023-04-28 10:01:30	ga_s2bm_ard_3-2-1_55KFB_2023-04-28_final
2023-04-28 10:01:34	ga_s2bm_ard_3-2-1_55KEB_2023-04-28_final
2023-04-28 10:01:37	ga_s2bm_ard_3-2-1_55KDB_2023-04-28_final
2023-04-28 10:01:40	ga_s2bm_ard_3-2-1_55KCB_2023-04-28_final
2023-04-28 10:01:44	ga_s2bm_ard_3-2-1_55KFA_2023-04-28_final
2023-04-28 10:01:48	ga_s2bm_ard_3-2-1_55KEA_2023-04-28_nrt
2023-04-28 10:01:52	ga_s2bm_ard_3-2-1_55KDA_2023-04-28_final
2023-04-28 10:01:55	ga_s2bm_ard_3-2-1_55KCA_2023-04-28_final
2023-05-01 10:11:51	ga_s2bm_ard_3-2-1_55KCA_2023-05-01_final
2023-05-01 10:11:54	ga_s2bm_ard_3-2-1_55KBA_2023-05-01_final
2023-05-01 10:11:55	ga_s2bm_ard_3-2-1_54KZF_2023-05-01_final
2023-05-01 10:11:58	ga_s2bm_ard_3-2-1_54KYF_2023-05-01_final
2023-05-01 11:52:17	ga_s2bm_ard_3-2-1_51KTB_2023-05-01_nrt
2023-05-01 11:52:18	ga_s2bm_ard_3-2-1_50KRG_2023-05-01_nrt
2023-05-01 11:52:22	ga_s2bm_ard_3-2-1_50KQG_2023-05-01_final
2023-05-01 11:52:25	ga_s2bm_ard_3-2-1_50KPG_2023-05-01_nrt
2023-05-01 11:52:30	ga_s2bm_ard_3-2-1_50KNG_2023-05-01_nrt
2023-05-01 11:52:32	ga_s2bm_ard_3-2-1_51KTA_2023-05-01_nrt
2023-05-01 11:52:32	ga_s2bm_ard_3-2-1_50KRF_2023-05-01_nrt
2023-10-05 11:42:09	ga_s2bm_ard_3-2-1_51KWB_2023-10-05_final
2023-10-05 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2023-10-05_final
2023-10-05 11:42:16	ga_s2bm_ard_3-2-1_51KUB_2023-10-05_final
2023-10-05 11:42:20	ga_s2bm_ard_3-2-1_51KTB_2023-10-05_nrt
2023-10-05 11:42:20	ga_s2bm_ard_3-2-1_50KRG_2023-10-05_nrt
2023-10-05 11:42:27	ga_s2bm_ard_3-2-1_51KVA_2023-10-05_final
2023-10-05 11:42:31	ga_s2bm_ard_3-2-1_51KUA_2023-10-05_final
2023-10-05 11:42:34	ga_s2bm_ard_3-2-1_51KTA_2023-10-05_nrt
2023-10-05 11:42:35	ga_s2bm_ard_3-2-1_50KRF_2023-10-05_nrt
2023-10-06 11:11:59	ga_s2bm_ard_3-2-1_52KFG_2023-10-06_final
2023-10-06 11:12:03	ga_s2bm_ard_3-2-1_52KEG_2023-10-06_final
2023-10-06 11:12:06	ga_s2bm_ard_3-2-1_52KDG_2023-10-06_final
2023-10-06 11:12:10	ga_s2bm_ard_3-2-1_52KCG_2023-10-06_final
2023-10-08 11:52:16	ga_s2bm_ard_3-2-1_51KTB_2023-10-08_nrt
2023-10-08 11:52:16	ga_s2bm_ard_3-2-1_50KRG_2023-10-08_nrt
2023-10-08 11:52:20	ga_s2bm_ard_3-2-1_50KQG_2023-10-08_final
2023-10-08 11:52:24	ga_s2bm_ard_3-2-1_50KPG_2023-10-08_nrt
2023-10-08 11:52:29	ga_s2bm_ard_3-2-1_50KNG_2023-10-08_nrt
2023-10-08 11:52:30	ga_s2bm_ard_3-2-1_51KTA_2023-10-08_nrt
2023-10-08 11:52:31	ga_s2bm_ard_3-2-1_50KRF_2023-10-08_nrt
2023-10-08 11:52:35	ga_s2bm_ard_3-2-1_50KQF_2023-10-08_final
2023-10-08 11:52:38	ga_s2bm_ard_3-2-1_50KPF_2023-10-08_final
2023-10-08 11:52:42	ga_s2bm_ard_3-2-1_50KNF_2023-10-08_nrt
2023-10-09 09:41:22	ga_s2bm_ard_3-2-1_56KNG_2023-10-09_nrt
2023-10-09 09:41:25	ga_s2bm_ard_3-2-1_56KMG_2023-10-09_final
2023-10-09 09:41:28	ga_s2bm_ard_3-2-1_56KLG_2023-10-09_final
2023-10-09 09:41:31	ga_s2bm_ard_3-2-1_56KKG_2023-10-09_final
2023-10-09 09:41:33	ga_s2bm_ard_3-2-1_55KHB_2023-10-09_final
2023-10-09 09:41:39	ga_s2bm_ard_3-2-1_56KMF_2023-10-09_final
2023-10-09 09:41:42	ga_s2bm_ard_3-2-1_56KLF_2023-10-09_final
2023-10-09 09:41:46	ga_s2bm_ard_3-2-1_56KKF_2023-10-09_final

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