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
2019-01-06 11:31:55	ga_s2bm_ard_3-2-1_51LXC_2019-01-06_final.stac-item
2019-01-06 11:32:38	ga_s2bm_ard_3-2-1_51KXV_2019-01-06_final.stac-item
2019-01-06 11:32:45	ga_s2bm_ard_3-2-1_51KVV_2019-01-06_final.stac-item
2019-01-06 11:33:00	ga_s2bm_ard_3-2-1_51KVU_2019-01-06_final.stac-item
2019-01-09 11:41:57	ga_s2bm_ard_3-2-1_51LVC_2019-01-09_final.stac-item
2019-01-09 11:42:12	ga_s2bm_ard_3-2-1_51KVB_2019-01-09_final.stac-item
2019-01-09 11:42:41	ga_s2bm_ard_3-2-1_51KVV_2019-01-09_final.stac-item
2019-01-09 11:42:55	ga_s2bm_ard_3-2-1_51KVU_2019-01-09_final.stac-item
2019-01-13 11:21:31	ga_s2bm_ard_3-2-1_52LDJ_2019-01-13_final.stac-item
2019-01-16 11:32:40	ga_s2bm_ard_3-2-1_51KXV_2019-01-16_final.stac-item
2019-01-16 11:32:46	ga_s2bm_ard_3-2-1_51KVV_2019-01-16_final.stac-item
2019-01-16 11:33:01	ga_s2bm_ard_3-2-1_51KVU_2019-01-16_final.stac-item
2019-01-19 11:42:56	ga_s2bm_ard_3-2-1_51KVU_2019-01-19_final.stac-item
2019-01-26 11:31:57	ga_s2bm_ard_3-2-1_51LXC_2019-01-26_final.stac-item
2019-01-26 11:32:20	ga_s2bm_ard_3-2-1_51KVB_2019-01-26_final.stac-item
2019-01-26 11:32:40	ga_s2bm_ard_3-2-1_51KXV_2019-01-26_final.stac-item
2019-01-26 11:32:47	ga_s2bm_ard_3-2-1_51KVV_2019-01-26_final.stac-item
2019-01-29 11:41:59	ga_s2bm_ard_3-2-1_51LVC_2019-01-29_final.stac-item
2019-01-29 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2019-01-29_final.stac-item
2019-01-29 11:42:42	ga_s2bm_ard_3-2-1_51KVV_2019-01-29_final.stac-item
2019-01-29 11:42:57	ga_s2bm_ard_3-2-1_51KVU_2019-01-29_final.stac-item
2019-01-30 11:11:37	ga_s2bm_ard_3-2-1_52LDJ_2019-01-30_final.stac-item
2019-02-03 10:54:48	ga_s2bm_ard_3-2-1_52JFR_2019-02-03_final.stac-item
2019-02-03 10:54:59	ga_s2bm_ard_3-2-1_52JGQ_2019-02-03_final.stac-item
2019-02-03 10:55:03	ga_s2bm_ard_3-2-1_52JFQ_2019-02-03_final.stac-item
2019-02-03 10:55:13	ga_s2bm_ard_3-2-1_52JGP_2019-02-03_final.stac-item
2019-02-04 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2019-02-04_final.stac-item
2019-02-06 11:04:43	ga_s2bm_ard_3-2-1_52JFR_2019-02-06_final.stac-item
2019-02-07 12:13:58	ga_s2bm_ard_3-2-1_49KGR_2019-02-07_final.stac-item
2019-02-07 12:14:09	ga_s2bm_ard_3-2-1_49KHQ_2019-02-07_final.stac-item
2019-02-14 12:04:28	ga_s2bm_ard_3-2-1_49KHP_2019-02-14_final.stac-item
2019-02-14 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2019-02-14_final.stac-item
2019-02-17 12:13:58	ga_s2bm_ard_3-2-1_49KGR_2019-02-17_final.stac-item
2019-02-17 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2019-02-17_final.stac-item
2019-02-17 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-02-17_final.stac-item
2019-02-23 10:54:47	ga_s2bm_ard_3-2-1_52JFR_2019-02-23_final.stac-item
2019-02-23 10:55:27	ga_s2bm_ard_3-2-1_52JGN_2019-02-23_final.stac-item
2019-02-24 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2019-02-24_final.stac-item
2019-02-24 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2019-02-24_final.stac-item
2019-02-24 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2019-02-24_final.stac-item
2019-02-26 11:04:42	ga_s2bm_ard_3-2-1_52JFR_2019-02-26_final.stac-item
2019-02-27 12:14:07	ga_s2bm_ard_3-2-1_49KHQ_2019-02-27_final.stac-item
2019-02-27 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2019-02-27_final.stac-item
2019-02-27 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2019-02-27_final.stac-item
2019-02-27 12:14:44	ga_s2bm_ard_3-2-1_49JFN_2019-02-27_final.stac-item
2019-03-01 11:11:14	ga_s2bm_ard_3-2-1_52LFK_2019-03-01_final.stac-item
2019-03-01 11:13:17	ga_s2bm_ard_3-2-1_52KDB_2019-03-01_final.stac-item
2019-03-01 11:13:38	ga_s2bm_ard_3-2-1_52KBA_2019-03-01_final.stac-item
2019-03-03 11:56:06	ga_s2bm_ard_3-2-1_50JMM_2019-03-03_final.stac-item
2019-03-03 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2019-03-03_final.stac-item
2019-03-04 11:23:36	ga_s2bm_ard_3-2-1_52KBA_2019-03-04_final.stac-item
2019-03-04 11:23:36	ga_s2bm_ard_3-2-1_51KZR_2019-03-04_final.stac-item
2019-03-04 11:23:47	ga_s2bm_ard_3-2-1_51KZQ_2019-03-04_final.stac-item
2019-03-06 12:06:12	ga_s2bm_ard_3-2-1_50JLL_2019-03-06_final.stac-item
2019-03-08 11:00:46	ga_s2bm_ard_3-2-1_52LGM_2019-03-08_final.stac-item
2019-03-10 11:46:13	ga_s2bm_ard_3-2-1_50JQL_2019-03-10_final.stac-item
2019-03-10 11:46:27	ga_s2bm_ard_3-2-1_50HQK_2019-03-10_final.stac-item
2019-03-10 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2019-03-10_final.stac-item
2019-03-10 11:47:07	ga_s2bm_ard_3-2-1_50HMH_2019-03-10_final.stac-item
2019-03-11 11:13:07	ga_s2bm_ard_3-2-1_52KEB_2019-03-11_final.stac-item
2019-03-13 11:56:15	ga_s2bm_ard_3-2-1_50JNL_2019-03-13_final.stac-item
2019-03-13 11:56:23	ga_s2bm_ard_3-2-1_50JLL_2019-03-13_final.stac-item
2019-03-14 11:23:07	ga_s2bm_ard_3-2-1_51KYT_2019-03-14_final.stac-item
2019-03-17 11:36:18	ga_s2bm_ard_3-2-1_50JQL_2019-03-17_final.stac-item
2019-03-17 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2019-03-17_final.stac-item
2019-03-18 11:00:47	ga_s2bm_ard_3-2-1_52LGM_2019-03-18_final.stac-item
2019-03-18 11:03:18	ga_s2bm_ard_3-2-1_52KEB_2019-03-18_final.stac-item
2019-03-18 11:04:16	ga_s2bm_ard_3-2-1_52JET_2019-03-18_final.stac-item
2019-03-20 11:46:04	ga_s2bm_ard_3-2-1_50JPM_2019-03-20_final.stac-item
2019-03-20 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2019-03-20_final.stac-item
2019-03-20 11:46:50	ga_s2bm_ard_3-2-1_50HPJ_2019-03-20_final.stac-item
2019-03-20 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2019-03-20_final.stac-item
2019-03-21 11:11:15	ga_s2bm_ard_3-2-1_52LFK_2019-03-21_final.stac-item
2019-03-21 11:11:30	ga_s2bm_ard_3-2-1_52LFJ_2019-03-21_final.stac-item
2019-03-21 11:13:18	ga_s2bm_ard_3-2-1_52KDB_2019-03-21_final.stac-item
2019-03-21 11:13:40	ga_s2bm_ard_3-2-1_51KZR_2019-03-21_final.stac-item
2019-03-21 11:13:54	ga_s2bm_ard_3-2-1_51KZQ_2019-03-21_final.stac-item
2019-03-21 11:14:16	ga_s2bm_ard_3-2-1_52JDT_2019-03-21_final.stac-item
2019-03-23 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2019-03-23_final.stac-item
2019-03-23 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-03-23_final.stac-item
2019-03-26 12:06:15	ga_s2bm_ard_3-2-1_50JLL_2019-03-26_final.stac-item
2019-03-27 11:36:21	ga_s2bm_ard_3-2-1_50JQL_2019-03-27_final.stac-item
2019-03-27 11:36:53	ga_s2bm_ard_3-2-1_50HPJ_2019-03-27_final.stac-item
2019-03-27 11:37:04	ga_s2bm_ard_3-2-1_50HQH_2019-03-27_final.stac-item
2019-03-28 11:00:50	ga_s2bm_ard_3-2-1_52LGM_2019-03-28_final.stac-item
2019-03-30 11:46:07	ga_s2bm_ard_3-2-1_50JPM_2019-03-30_final.stac-item
2019-03-30 11:46:09	ga_s2bm_ard_3-2-1_51JTF_2019-03-30_final.stac-item
2019-03-30 11:46:25	ga_s2bm_ard_3-2-1_50JNL_2019-03-30_final.stac-item
2019-03-30 11:46:32	ga_s2bm_ard_3-2-1_50HQK_2019-03-30_final.stac-item
2019-03-30 11:46:55	ga_s2bm_ard_3-2-1_50HQH_2019-03-30_final.stac-item
2019-03-30 11:46:57	ga_s2bm_ard_3-2-1_50HMJ_2019-03-30_final.stac-item
2019-03-30 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2019-03-30_final.stac-item
2019-03-30 11:47:12	ga_s2bm_ard_3-2-1_50HMH_2019-03-30_final.stac-item
2019-03-31 11:10:45	ga_s2bm_ard_3-2-1_52LGM_2019-03-31_final.stac-item
2019-03-31 11:11:18	ga_s2bm_ard_3-2-1_52LFK_2019-03-31_final.stac-item
2019-03-31 11:13:21	ga_s2bm_ard_3-2-1_52KDB_2019-03-31_final.stac-item
2019-03-31 11:13:41	ga_s2bm_ard_3-2-1_52KBA_2019-03-31_final.stac-item
2019-03-31 11:14:22	ga_s2bm_ard_3-2-1_52JCT_2019-03-31_final.stac-item
2020-02-06 11:53:11	ga_s2bm_ard_3-2-1_50KQC_2020-02-06_final.stac-item
2020-02-06 11:53:18	ga_s2bm_ard_3-2-1_50KNC_2020-02-06_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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