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
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KCA_2018-06-03_final.stac-item
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KCB_2018-06-03_final.stac-item
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KDA_2018-06-03_final.stac-item
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KDB_2018-06-03_final.stac-item
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KEB_2018-06-03_final.stac-item
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KFA_2018-06-03_final.stac-item
2018-06-03 09:57:04	ga_s2bm_ard_3-2-1_55KFB_2018-06-03_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KCF_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KCG_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KDF_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KDG_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KEF_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KEG_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KFF_2018-06-04_final.stac-item
2018-06-04 11:07:09	ga_s2bm_ard_3-2-1_52KFG_2018-06-04_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KCA_2018-06-13_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KCB_2018-06-13_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KDA_2018-06-13_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KDB_2018-06-13_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KEB_2018-06-13_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KFA_2018-06-13_final.stac-item
2018-06-13 09:57:05	ga_s2bm_ard_3-2-1_55KFB_2018-06-13_final.stac-item
2018-06-13 11:37:58	ga_s2bm_ard_3-2-1_51KUA_2018-06-13_final.stac-item
2018-06-13 11:37:58	ga_s2bm_ard_3-2-1_51KVA_2018-06-13_final.stac-item
2018-06-13 11:37:58	ga_s2bm_ard_3-2-1_51KVB_2018-06-13_final.stac-item
2018-06-13 11:37:58	ga_s2bm_ard_3-2-1_51KWA_2018-06-13_final.stac-item
2018-06-13 11:37:58	ga_s2bm_ard_3-2-1_51KWB_2018-06-13_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_55KBA_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_55KBB_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_55KCA_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_55KCB_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_54KYF_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_54KYG_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_54KZF_2018-06-16_final.stac-item
2018-06-16 10:07:03	ga_s2bm_ard_3-2-1_54KZG_2018-06-16_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KVF_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KVG_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KWF_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KWG_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KXF_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KXG_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KYF_2018-06-19_final.stac-item
2018-06-19 10:17:04	ga_s2bm_ard_3-2-1_54KYG_2018-06-19_final.stac-item
2019-07-28 11:42:17	ga_s2bm_ard_3-2-1_51KWB_2019-07-28_final.stac-item
2019-07-28 11:42:21	ga_s2bm_ard_3-2-1_51KVB_2019-07-28_final.stac-item
2019-07-28 11:42:29	ga_s2bm_ard_3-2-1_51KWA_2019-07-28_final.stac-item
2019-07-28 11:42:36	ga_s2bm_ard_3-2-1_51KVA_2019-07-28_final.stac-item
2019-07-28 11:42:39	ga_s2bm_ard_3-2-1_51KUA_2019-07-28_final.stac-item
2019-08-06 10:31:50	ga_s2bm_ard_3-2-1_54KVG_2019-08-06_final.stac-item
2019-08-06 10:31:53	ga_s2bm_ard_3-2-1_54KUG_2019-08-06_final.stac-item
2019-08-06 10:31:56	ga_s2bm_ard_3-2-1_54KTG_2019-08-06_final.stac-item
2019-08-06 10:32:04	ga_s2bm_ard_3-2-1_54KVF_2019-08-06_final.stac-item
2019-08-06 10:32:08	ga_s2bm_ard_3-2-1_54KUF_2019-08-06_final.stac-item
2019-08-06 10:32:11	ga_s2bm_ard_3-2-1_54KTF_2019-08-06_final.stac-item
2019-08-06 10:32:12	ga_s2bm_ard_3-2-1_53KRA_2019-08-06_final.stac-item
2019-08-15 11:01:58	ga_s2bm_ard_3-2-1_53KLB_2019-08-15_final.stac-item
2019-08-15 11:02:02	ga_s2bm_ard_3-2-1_53KKB_2019-08-15_final.stac-item
2019-08-15 11:02:03	ga_s2bm_ard_3-2-1_52KHG_2019-08-15_final.stac-item
2019-08-15 11:02:07	ga_s2bm_ard_3-2-1_52KGG_2019-08-15_final.stac-item
2019-08-15 11:02:10	ga_s2bm_ard_3-2-1_53KLA_2019-08-15_final.stac-item
2019-08-15 11:02:10	ga_s2bm_ard_3-2-1_52KFG_2019-08-15_final.stac-item
2019-08-15 11:02:17	ga_s2bm_ard_3-2-1_53KKA_2019-08-15_final.stac-item
2019-08-15 11:02:18	ga_s2bm_ard_3-2-1_52KHF_2019-08-15_final.stac-item
2019-08-15 11:02:21	ga_s2bm_ard_3-2-1_52KGF_2019-08-15_final.stac-item
2019-08-15 11:02:25	ga_s2bm_ard_3-2-1_52KFF_2019-08-15_final.stac-item
2023-09-15 10:01:31	ga_s2bm_ard_3-2-1_55KFB_2023-09-15_final
2023-09-15 10:01:35	ga_s2bm_ard_3-2-1_55KEB_2023-09-15_final
2023-09-15 10:01:38	ga_s2bm_ard_3-2-1_55KDB_2023-09-15_final
2023-09-15 10:01:41	ga_s2bm_ard_3-2-1_55KCB_2023-09-15_final
2023-09-15 10:01:45	ga_s2bm_ard_3-2-1_55KFA_2023-09-15_final
2023-09-15 10:01:49	ga_s2bm_ard_3-2-1_55KEA_2023-09-15_nrt
2023-09-15 10:01:53	ga_s2bm_ard_3-2-1_55KDA_2023-09-15_final
2023-09-15 10:01:56	ga_s2bm_ard_3-2-1_55KCA_2023-09-15_final
2023-09-27 10:41:46	ga_s2bm_ard_3-2-1_54KTG_2023-09-27_final
2023-09-27 10:41:48	ga_s2bm_ard_3-2-1_53KRB_2023-09-27_final
2023-09-27 10:41:52	ga_s2bm_ard_3-2-1_53KQB_2023-09-27_final
2023-09-27 10:41:55	ga_s2bm_ard_3-2-1_53KPB_2023-09-27_final
2023-09-27 10:41:57	ga_s2bm_ard_3-2-1_54KTF_2023-09-27_final
2023-09-27 10:41:58	ga_s2bm_ard_3-2-1_53KNB_2023-09-27_final
2023-09-27 10:42:02	ga_s2bm_ard_3-2-1_53KRA_2023-09-27_final
2023-09-27 10:42:06	ga_s2bm_ard_3-2-1_53KQA_2023-09-27_final
2023-09-27 10:42:10	ga_s2bm_ard_3-2-1_53KPA_2023-09-27_final
2023-09-27 10:42:13	ga_s2bm_ard_3-2-1_53KNA_2023-09-27_final
2023-10-03 11:01:53	ga_s2bm_ard_3-2-1_53KLB_2023-10-03_final
2023-10-03 11:01:57	ga_s2bm_ard_3-2-1_53KKB_2023-10-03_final
2023-10-03 11:01:58	ga_s2bm_ard_3-2-1_52KHG_2023-10-03_final
2023-10-03 11:02:02	ga_s2bm_ard_3-2-1_52KGG_2023-10-03_final
2023-10-03 11:02:04	ga_s2bm_ard_3-2-1_53KLA_2023-10-03_final
2023-10-03 11:02:05	ga_s2bm_ard_3-2-1_52KFG_2023-10-03_final
2023-10-03 11:02:11	ga_s2bm_ard_3-2-1_53KKA_2023-10-03_final
2023-10-03 11:02:13	ga_s2bm_ard_3-2-1_52KHF_2023-10-03_final
2023-10-03 11:02:16	ga_s2bm_ard_3-2-1_52KGF_2023-10-03_final
2023-10-03 11:02:19	ga_s2bm_ard_3-2-1_52KFF_2023-10-03_final
2023-10-05 10:01:29	ga_s2bm_ard_3-2-1_55KFB_2023-10-05_final
2023-10-05 10:01:32	ga_s2bm_ard_3-2-1_55KEB_2023-10-05_final
2023-10-05 10:01:35	ga_s2bm_ard_3-2-1_55KDB_2023-10-05_final
2023-10-05 10:01:38	ga_s2bm_ard_3-2-1_55KCB_2023-10-05_final
2023-10-05 10:01:43	ga_s2bm_ard_3-2-1_55KFA_2023-10-05_final
2023-10-05 10:01:47	ga_s2bm_ard_3-2-1_55KEA_2023-10-05_nrt
2023-10-05 10:01:50	ga_s2bm_ard_3-2-1_55KDA_2023-10-05_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