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
2019-06-04 12:04:21	ga_s2bm_ard_3-2-1_50KKV_2019-06-04_final.stac-item
2019-06-04 12:04:22	ga_s2bm_ard_3-2-1_49KHQ_2019-06-04_final.stac-item
2019-06-04 12:04:26	ga_s2bm_ard_3-2-1_49KGQ_2019-06-04_final.stac-item
2019-06-04 12:04:36	ga_s2bm_ard_3-2-1_49KHP_2019-06-04_final.stac-item
2019-06-05 09:53:19	ga_s2bm_ard_3-2-1_55KGQ_2019-06-05_final.stac-item
2019-06-05 09:53:23	ga_s2bm_ard_3-2-1_55KFQ_2019-06-05_final.stac-item
2019-06-05 09:53:26	ga_s2bm_ard_3-2-1_55KEQ_2019-06-05_final.stac-item
2019-06-05 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-06-05_final.stac-item
2019-06-05 11:34:04	ga_s2bm_ard_3-2-1_51KWQ_2019-06-05_final.stac-item
2019-06-05 11:34:08	ga_s2bm_ard_3-2-1_51KVQ_2019-06-05_final.stac-item
2019-06-05 11:34:11	ga_s2bm_ard_3-2-1_51KUQ_2019-06-05_final.stac-item
2019-06-15 09:53:19	ga_s2bm_ard_3-2-1_55KGQ_2019-06-15_final.stac-item
2019-06-15 09:53:22	ga_s2bm_ard_3-2-1_55KFQ_2019-06-15_final.stac-item
2019-06-15 09:53:26	ga_s2bm_ard_3-2-1_55KEQ_2019-06-15_final.stac-item
2019-06-15 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-06-15_final.stac-item
2019-06-23 10:53:44	ga_s2bm_ard_3-2-1_53KMQ_2019-06-23_final.stac-item
2019-07-05 09:53:20	ga_s2bm_ard_3-2-1_55KGQ_2019-07-05_final.stac-item
2019-07-05 09:53:24	ga_s2bm_ard_3-2-1_55KFQ_2019-07-05_final.stac-item
2019-07-05 09:53:27	ga_s2bm_ard_3-2-1_55KEQ_2019-07-05_final.stac-item
2019-07-05 09:53:30	ga_s2bm_ard_3-2-1_55KDQ_2019-07-05_final.stac-item
2019-07-05 11:34:01	ga_s2bm_ard_3-2-1_51KXQ_2019-07-05_final.stac-item
2019-07-05 11:34:05	ga_s2bm_ard_3-2-1_51KWQ_2019-07-05_final.stac-item
2019-07-05 11:34:08	ga_s2bm_ard_3-2-1_51KVQ_2019-07-05_final.stac-item
2019-07-05 11:34:11	ga_s2bm_ard_3-2-1_51KUQ_2019-07-05_final.stac-item
2019-07-08 10:03:26	ga_s2bm_ard_3-2-1_55KDQ_2019-07-08_final.stac-item
2019-07-08 10:03:29	ga_s2bm_ard_3-2-1_55KCQ_2019-07-08_final.stac-item
2019-07-08 10:03:32	ga_s2bm_ard_3-2-1_55KBQ_2019-07-08_final.stac-item
2019-07-08 10:03:33	ga_s2bm_ard_3-2-1_54KZV_2019-07-08_final.stac-item
2019-07-08 10:03:41	ga_s2bm_ard_3-2-1_54KYV_2019-07-08_final.stac-item
2019-07-08 10:03:47	ga_s2bm_ard_3-2-1_54KZU_2019-07-08_final.stac-item
2019-07-13 10:53:45	ga_s2bm_ard_3-2-1_53KMQ_2019-07-13_final.stac-item
2019-07-13 10:53:48	ga_s2bm_ard_3-2-1_53KLQ_2019-07-13_final.stac-item
2019-07-13 10:53:51	ga_s2bm_ard_3-2-1_53KKQ_2019-07-13_final.stac-item
2019-07-13 10:53:51	ga_s2bm_ard_3-2-1_52KHV_2019-07-13_final.stac-item
2019-07-13 10:53:55	ga_s2bm_ard_3-2-1_52KGV_2019-07-13_final.stac-item
2019-07-13 10:54:06	ga_s2bm_ard_3-2-1_52KHU_2019-07-13_final.stac-item
2019-07-14 10:23:34	ga_s2bm_ard_3-2-1_54KWV_2019-07-14_final.stac-item
2019-07-14 10:23:38	ga_s2bm_ard_3-2-1_54KVV_2019-07-14_final.stac-item
2019-07-14 10:23:41	ga_s2bm_ard_3-2-1_54KUV_2019-07-14_final.stac-item
2019-07-14 10:23:46	ga_s2bm_ard_3-2-1_54KTV_2019-07-14_final.stac-item
2019-07-14 10:23:48	ga_s2bm_ard_3-2-1_53KRQ_2019-07-14_final.stac-item
2019-07-14 10:23:59	ga_s2bm_ard_3-2-1_53KRP_2019-07-14_final.stac-item
2019-07-15 11:34:01	ga_s2bm_ard_3-2-1_51KXQ_2019-07-15_final.stac-item
2019-07-15 11:34:04	ga_s2bm_ard_3-2-1_51KWQ_2019-07-15_final.stac-item
2019-07-15 11:34:08	ga_s2bm_ard_3-2-1_51KXQ_2019-07-15_final.stac-item
2019-07-15 11:34:10	ga_s2bm_ard_3-2-1_51KWQ_2019-07-15_final.stac-item
2019-07-15 11:34:12	ga_s2bm_ard_3-2-1_51KVQ_2019-07-15_final.stac-item
2019-07-15 11:34:14	ga_s2bm_ard_3-2-1_51KUQ_2019-07-15_final.stac-item
2019-08-04 11:34:00	ga_s2bm_ard_3-2-1_51KXQ_2019-08-04_final.stac-item
2019-08-04 11:34:04	ga_s2bm_ard_3-2-1_51KWQ_2019-08-04_final.stac-item
2019-08-04 11:34:07	ga_s2bm_ard_3-2-1_51KVQ_2019-08-04_final.stac-item
2019-08-04 11:34:10	ga_s2bm_ard_3-2-1_51KUQ_2019-08-04_final.stac-item
2019-08-11 11:23:56	ga_s2bm_ard_3-2-1_52KBV_2019-08-11_final.stac-item
2019-08-11 11:23:56	ga_s2bm_ard_3-2-1_51KZQ_2019-08-11_final.stac-item
2019-08-11 11:24:01	ga_s2bm_ard_3-2-1_51KYQ_2019-08-11_final.stac-item
2019-08-11 11:24:04	ga_s2bm_ard_3-2-1_51KXQ_2019-08-11_final.stac-item
2019-08-11 11:24:09	ga_s2bm_ard_3-2-1_51KWQ_2019-08-11_final.stac-item
2019-08-21 11:23:55	ga_s2bm_ard_3-2-1_52KBV_2019-08-21_final.stac-item
2019-08-21 11:23:55	ga_s2bm_ard_3-2-1_51KZQ_2019-08-21_final.stac-item
2019-08-21 11:23:59	ga_s2bm_ard_3-2-1_51KYQ_2019-08-21_final.stac-item
2019-08-21 11:24:03	ga_s2bm_ard_3-2-1_51KXQ_2019-08-21_final.stac-item
2019-08-21 11:24:07	ga_s2bm_ard_3-2-1_51KWQ_2019-08-21_final.stac-item
2019-09-23 09:53:11	ga_s2bm_ard_3-2-1_55KGQ_2019-09-23_final.stac-item
2019-09-23 09:53:14	ga_s2bm_ard_3-2-1_55KFQ_2019-09-23_final.stac-item
2019-09-23 09:53:18	ga_s2bm_ard_3-2-1_55KEQ_2019-09-23_final.stac-item
2019-09-23 09:53:21	ga_s2bm_ard_3-2-1_55KDQ_2019-09-23_final.stac-item
2019-09-27 11:13:44	ga_s2bm_ard_3-2-1_52KEV_2019-09-27_final.stac-item
2019-09-27 11:13:48	ga_s2bm_ard_3-2-1_52KDV_2019-09-27_final.stac-item
2019-09-27 11:13:51	ga_s2bm_ard_3-2-1_52KCV_2019-09-27_final.stac-item
2019-09-27 11:13:54	ga_s2bm_ard_3-2-1_51KZQ_2019-09-27_final.stac-item
2019-09-27 11:13:54	ga_s2bm_ard_3-2-1_52KBV_2019-09-27_final.stac-item
2019-10-03 11:33:53	ga_s2bm_ard_3-2-1_51KXQ_2019-10-03_final.stac-item
2019-10-03 11:33:57	ga_s2bm_ard_3-2-1_51KWQ_2019-10-03_final.stac-item
2019-10-03 11:34:00	ga_s2bm_ard_3-2-1_51KVQ_2019-10-03_final.stac-item
2019-10-03 11:34:03	ga_s2bm_ard_3-2-1_51KUQ_2019-10-03_final.stac-item
2019-10-08 10:43:34	ga_s2bm_ard_3-2-1_53KPQ_2019-10-08_final.stac-item
2019-10-08 10:43:38	ga_s2bm_ard_3-2-1_53KNQ_2019-10-08_final.stac-item
2019-10-08 10:43:41	ga_s2bm_ard_3-2-1_53KMQ_2019-10-08_final.stac-item
2019-10-08 10:43:46	ga_s2bm_ard_3-2-1_53KLQ_2019-10-08_final.stac-item
2019-10-10 11:23:51	ga_s2bm_ard_3-2-1_52KBV_2019-10-10_final.stac-item
2019-10-10 11:23:51	ga_s2bm_ard_3-2-1_51KZQ_2019-10-10_final.stac-item
2019-10-10 11:23:55	ga_s2bm_ard_3-2-1_51KYQ_2019-10-10_final.stac-item
2019-10-10 11:23:58	ga_s2bm_ard_3-2-1_51KXQ_2019-10-10_final.stac-item
2019-10-10 11:24:03	ga_s2bm_ard_3-2-1_51KWQ_2019-10-10_final.stac-item
2019-11-07 10:43:33	ga_s2bm_ard_3-2-1_53KPQ_2019-11-07_final.stac-item
2019-11-07 10:43:35	ga_s2bm_ard_3-2-1_53KNQ_2019-11-07_final.stac-item
2019-11-07 10:43:40	ga_s2bm_ard_3-2-1_53KPQ_2019-11-07_final.stac-item
2019-11-07 10:43:42	ga_s2bm_ard_3-2-1_53KNQ_2019-11-07_final.stac-item
2019-11-07 10:43:44	ga_s2bm_ard_3-2-1_53KMQ_2019-11-07_final.stac-item
2019-11-07 10:43:46	ga_s2bm_ard_3-2-1_53KLQ_2019-11-07_final.stac-item
2019-11-30 10:53:31	ga_s2bm_ard_3-2-1_53KMQ_2019-11-30_final.stac-item
2019-11-30 10:53:35	ga_s2bm_ard_3-2-1_53KLQ_2019-11-30_final.stac-item
2019-11-30 10:53:38	ga_s2bm_ard_3-2-1_53KKQ_2019-11-30_final.stac-item
2019-11-30 10:53:38	ga_s2bm_ard_3-2-1_52KHV_2019-11-30_final.stac-item
2019-11-30 10:53:41	ga_s2bm_ard_3-2-1_52KGV_2019-11-30_final.stac-item
2019-11-30 10:53:52	ga_s2bm_ard_3-2-1_52KHU_2019-11-30_final.stac-item
2019-12-01 10:23:20	ga_s2bm_ard_3-2-1_54KWV_2019-12-01_final.stac-item
2019-12-01 10:23:24	ga_s2bm_ard_3-2-1_54KVV_2019-12-01_final.stac-item
2019-12-01 10:23:27	ga_s2bm_ard_3-2-1_54KUV_2019-12-01_final.stac-item
2019-12-01 10:23:32	ga_s2bm_ard_3-2-1_54KTV_2019-12-01_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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