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
2022-02-03 11:16:06	ga_s2bm_ard_3-2-1_51JXF_2022-02-03_final.stac-item
2022-02-05 11:56:08	ga_s2bm_ard_3-2-1_50JKM_2022-02-05_final.stac-item
2022-02-06 11:25:51	ga_s2bm_ard_3-2-1_51JWG_2022-02-06_final.stac-item
2022-02-06 11:26:00	ga_s2bm_ard_3-2-1_51JUG_2022-02-06_final.stac-item
2022-02-06 11:26:02	ga_s2bm_ard_3-2-1_51JXF_2022-02-06_final.stac-item
2022-02-06 11:26:05	ga_s2bm_ard_3-2-1_51JWF_2022-02-06_final.stac-item
2022-02-06 11:26:24	ga_s2bm_ard_3-2-1_51HVE_2022-02-06_final.stac-item
2022-02-06 11:26:27	ga_s2bm_ard_3-2-1_51HUE_2022-02-06_final.stac-item
2022-02-08 12:06:04	ga_s2bm_ard_3-2-1_50JKM_2022-02-08_final.stac-item
2022-02-09 11:35:54	ga_s2bm_ard_3-2-1_51JUG_2022-02-09_final.stac-item
2022-02-09 11:36:11	ga_s2bm_ard_3-2-1_51JTF_2022-02-09_final.stac-item
2022-02-09 11:36:18	ga_s2bm_ard_3-2-1_51HVE_2022-02-09_final.stac-item
2022-02-09 11:36:23	ga_s2bm_ard_3-2-1_51HUE_2022-02-09_final.stac-item
2022-02-13 11:16:06	ga_s2bm_ard_3-2-1_51JXF_2022-02-13_final.stac-item
2022-02-15 11:56:08	ga_s2bm_ard_3-2-1_50JKM_2022-02-15_final.stac-item
2022-02-16 11:25:50	ga_s2bm_ard_3-2-1_51JWG_2022-02-16_final.stac-item
2022-02-16 11:25:59	ga_s2bm_ard_3-2-1_51JUG_2022-02-16_final.stac-item
2022-02-16 11:26:01	ga_s2bm_ard_3-2-1_51JXF_2022-02-16_final.stac-item
2022-02-16 11:26:05	ga_s2bm_ard_3-2-1_51JWF_2022-02-16_final.stac-item
2022-02-16 11:26:23	ga_s2bm_ard_3-2-1_51HVE_2022-02-16_final.stac-item
2022-02-16 11:26:26	ga_s2bm_ard_3-2-1_51HUE_2022-02-16_final.stac-item
2022-02-18 12:06:03	ga_s2bm_ard_3-2-1_50JKM_2022-02-18_final.stac-item
2022-02-19 11:35:53	ga_s2bm_ard_3-2-1_51JUG_2022-02-19_final.stac-item
2022-02-19 11:36:11	ga_s2bm_ard_3-2-1_51JTF_2022-02-19_final.stac-item
2022-02-19 11:36:17	ga_s2bm_ard_3-2-1_51HVE_2022-02-19_final.stac-item
2022-02-19 11:36:22	ga_s2bm_ard_3-2-1_51HUE_2022-02-19_final.stac-item
2022-02-23 11:16:07	ga_s2bm_ard_3-2-1_51JXF_2022-02-23_final.stac-item
2022-02-23 11:16:15	ga_s2bm_ard_3-2-1_51JWF_2022-02-23_final.stac-item
2022-02-25 11:56:09	ga_s2bm_ard_3-2-1_50JKM_2022-02-25_final.stac-item
2022-02-26 11:25:52	ga_s2bm_ard_3-2-1_51JWG_2022-02-26_final.stac-item
2022-02-26 11:26:01	ga_s2bm_ard_3-2-1_51JUG_2022-02-26_final.stac-item
2022-02-26 11:26:03	ga_s2bm_ard_3-2-1_51JXF_2022-02-26_final.stac-item
2022-02-26 11:26:07	ga_s2bm_ard_3-2-1_51JWF_2022-02-26_final.stac-item
2022-02-26 11:26:25	ga_s2bm_ard_3-2-1_51HVE_2022-02-26_final.stac-item
2022-02-26 11:26:28	ga_s2bm_ard_3-2-1_51HUE_2022-02-26_final.stac-item
2022-02-28 12:06:06	ga_s2bm_ard_3-2-1_50JKM_2022-02-28_final.stac-item
2022-03-03 12:13:48	ga_s2bm_ard_3-2-1_50KKA_2022-03-03_final.stac-item
2022-03-03 12:13:50	ga_s2bm_ard_3-2-1_49KGR_2022-03-03_final.stac-item
2022-03-03 12:13:55	ga_s2bm_ard_3-2-1_50KKA_2022-03-03_final.stac-item
2022-03-03 12:13:57	ga_s2bm_ard_3-2-1_49KGR_2022-03-03_final.stac-item
2022-03-03 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2022-03-03_final.stac-item
2022-03-03 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2022-03-03_final.stac-item
2022-03-03 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2022-03-03_final.stac-item
2022-03-03 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2022-03-03_final.stac-item
2022-03-04 11:45:43	ga_s2bm_ard_3-2-1_50JQN_2022-03-04_final.stac-item
2022-03-05 11:14:53	ga_s2bm_ard_3-2-1_51JYL_2022-03-05_final.stac-item
2022-03-05 11:15:07	ga_s2bm_ard_3-2-1_51JYK_2022-03-05_final.stac-item
2022-03-08 11:24:49	ga_s2bm_ard_3-2-1_51JYL_2022-03-08_final.stac-item
2022-03-08 11:25:03	ga_s2bm_ard_3-2-1_51JYK_2022-03-08_final.stac-item
2022-03-08 11:25:42	ga_s2bm_ard_3-2-1_51JYG_2022-03-08_final.stac-item
2022-03-10 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2022-03-10_final.stac-item
2022-03-10 12:04:16	ga_s2bm_ard_3-2-1_49KGQ_2022-03-10_final.stac-item
2022-03-10 12:04:26	ga_s2bm_ard_3-2-1_49KHP_2022-03-10_final.stac-item
2022-03-10 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2022-03-10_final.stac-item
2022-03-13 12:13:52	ga_s2bm_ard_3-2-1_50KKA_2022-03-13_final.stac-item
2022-03-13 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2022-03-13_final.stac-item
2022-03-13 12:14:11	ga_s2bm_ard_3-2-1_49KGQ_2022-03-13_final.stac-item
2022-03-13 12:14:19	ga_s2bm_ard_3-2-1_49KHP_2022-03-13_final.stac-item
2022-03-13 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2022-03-13_final.stac-item
2022-03-13 12:14:39	ga_s2bm_ard_3-2-1_49JGN_2022-03-13_final.stac-item
2022-03-13 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2022-03-13_final.stac-item
2022-03-15 11:14:54	ga_s2bm_ard_3-2-1_51JYL_2022-03-15_final.stac-item
2022-03-15 11:15:08	ga_s2bm_ard_3-2-1_51JYK_2022-03-15_final.stac-item
2022-03-18 11:24:49	ga_s2bm_ard_3-2-1_51JYL_2022-03-18_final.stac-item
2022-03-18 11:25:04	ga_s2bm_ard_3-2-1_51JYK_2022-03-18_final.stac-item
2022-03-18 11:25:43	ga_s2bm_ard_3-2-1_51JYG_2022-03-18_final.stac-item
2022-03-20 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2022-03-20_final.stac-item
2022-03-20 12:04:16	ga_s2bm_ard_3-2-1_49KGQ_2022-03-20_final.stac-item
2022-03-20 12:04:26	ga_s2bm_ard_3-2-1_49KHP_2022-03-20_final.stac-item
2022-03-20 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2022-03-20_final.stac-item
2022-03-23 12:13:52	ga_s2bm_ard_3-2-1_50KKA_2022-03-23_final.stac-item
2022-03-23 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2022-03-23_final.stac-item
2022-03-23 12:14:19	ga_s2bm_ard_3-2-1_49KHP_2022-03-23_final.stac-item
2022-03-23 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2022-03-23_final.stac-item
2022-03-23 12:14:39	ga_s2bm_ard_3-2-1_49JGN_2022-03-23_final.stac-item
2022-03-23 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2022-03-23_final.stac-item
2022-03-25 11:14:53	ga_s2bm_ard_3-2-1_51JYL_2022-03-25_final.stac-item
2022-03-25 11:15:08	ga_s2bm_ard_3-2-1_51JYK_2022-03-25_final.stac-item
2022-03-27 11:52:51	ga_s2bm_ard_3-2-1_51KTU_2022-03-27_final.stac-item
2022-03-27 11:55:03	ga_s2bm_ard_3-2-1_50JNR_2022-03-27_final.stac-item
2022-03-28 11:24:48	ga_s2bm_ard_3-2-1_51JYL_2022-03-28_final.stac-item
2022-03-28 11:25:03	ga_s2bm_ard_3-2-1_51JYK_2022-03-28_final.stac-item
2022-03-30 12:03:55	ga_s2bm_ard_3-2-1_50KKA_2022-03-30_final.stac-item
2022-03-30 12:04:15	ga_s2bm_ard_3-2-1_49KGQ_2022-03-30_final.stac-item
2022-03-30 12:04:24	ga_s2bm_ard_3-2-1_49KHP_2022-03-30_final.stac-item
2022-03-30 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2022-03-30_final.stac-item
2022-03-30 12:04:38	ga_s2bm_ard_3-2-1_49JGN_2022-03-30_final.stac-item
2022-04-02 12:13:45	ga_s2bm_ard_3-2-1_50KKA_2022-04-02_final.stac-item
2022-04-02 12:14:09	ga_s2bm_ard_3-2-1_49KGQ_2022-04-02_final.stac-item
2022-04-02 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2022-04-02_final.stac-item
2022-04-02 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2022-04-02_final.stac-item
2022-04-09 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2022-04-09_final.stac-item
2022-04-12 12:13:46	ga_s2bm_ard_3-2-1_49KGR_2022-04-12_final.stac-item
2022-04-19 12:03:54	ga_s2bm_ard_3-2-1_50KKA_2022-04-19_final.stac-item
2022-04-19 12:04:14	ga_s2bm_ard_3-2-1_49KGQ_2022-04-19_final.stac-item
2022-04-19 12:04:23	ga_s2bm_ard_3-2-1_49KHP_2022-04-19_final.stac-item
2022-04-19 12:04:36	ga_s2bm_ard_3-2-1_49JGN_2022-04-19_final.stac-item
2022-04-22 12:13:49	ga_s2bm_ard_3-2-1_50KKA_2022-04-22_final.stac-item
2022-04-22 12:14:07	ga_s2bm_ard_3-2-1_49KGQ_2022-04-22_final.stac-item
2022-04-22 12:14:16	ga_s2bm_ard_3-2-1_49KHP_2022-04-22_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