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
2019-07-04 12:04:30	ga_s2bm_ard_3-2-1_50KMU_2019-07-04_final.stac-item
2019-07-04 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2019-07-04_final.stac-item
2019-07-04 12:04:37	ga_s2bm_ard_3-2-1_50KKU_2019-07-04_final.stac-item
2019-07-04 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-07-04_final.stac-item
2019-07-04 12:04:48	ga_s2bm_ard_3-2-1_50JLT_2019-07-04_final.stac-item
2019-07-04 12:04:51	ga_s2bm_ard_3-2-1_49JHN_2019-07-04_final.stac-item
2019-07-04 12:04:51	ga_s2bm_ard_3-2-1_50JKT_2019-07-04_final.stac-item
2019-07-04 12:04:55	ga_s2bm_ard_3-2-1_49JGN_2019-07-04_final.stac-item
2019-07-08 11:44:22	ga_s2bm_ard_3-2-1_51KUP_2019-07-08_final.stac-item
2019-07-08 11:44:25	ga_s2bm_ard_3-2-1_51KTP_2019-07-08_final.stac-item
2019-07-08 11:44:28	ga_s2bm_ard_3-2-1_50KQU_2019-07-08_final.stac-item
2019-07-08 11:44:32	ga_s2bm_ard_3-2-1_50KPU_2019-07-08_final.stac-item
2019-07-08 11:44:36	ga_s2bm_ard_3-2-1_51JUN_2019-07-08_final.stac-item
2019-07-08 11:44:39	ga_s2bm_ard_3-2-1_50JRT_2019-07-08_final.stac-item
2019-07-08 11:44:40	ga_s2bm_ard_3-2-1_51JTN_2019-07-08_final.stac-item
2019-07-08 11:44:43	ga_s2bm_ard_3-2-1_50JQT_2019-07-08_final.stac-item
2019-07-08 11:44:46	ga_s2bm_ard_3-2-1_50JPT_2019-07-08_final.stac-item
2019-07-09 11:14:18	ga_s2bm_ard_3-2-1_52KBU_2019-07-09_final.stac-item
2019-07-09 11:14:25	ga_s2bm_ard_3-2-1_52JDT_2019-07-09_final.stac-item
2019-07-09 11:14:29	ga_s2bm_ard_3-2-1_52JCT_2019-07-09_final.stac-item
2019-07-09 11:14:32	ga_s2bm_ard_3-2-1_51JZN_2019-07-09_final.stac-item
2019-07-09 11:14:32	ga_s2bm_ard_3-2-1_52JBT_2019-07-09_final.stac-item
2019-07-09 11:14:38	ga_s2bm_ard_3-2-1_51JYN_2019-07-09_final.stac-item
2019-07-16 09:23:48	ga_s2bm_ard_3-2-1_56JNT_2019-07-15_final.stac-item
2019-07-19 09:33:33	ga_s2bm_ard_3-2-1_56KMU_2019-07-19_final.stac-item
2019-07-19 09:33:36	ga_s2bm_ard_3-2-1_56KLU_2019-07-19_final.stac-item
2019-07-19 09:33:44	ga_s2bm_ard_3-2-1_56JNT_2019-07-19_final.stac-item
2019-07-19 09:33:48	ga_s2bm_ard_3-2-1_56JMT_2019-07-19_final.stac-item
2019-07-19 09:33:51	ga_s2bm_ard_3-2-1_56JLT_2019-07-19_final.stac-item
2019-07-22 09:43:32	ga_s2bm_ard_3-2-1_56KLU_2019-07-22_final.stac-item
2019-07-22 09:43:35	ga_s2bm_ard_3-2-1_56KKU_2019-07-22_final.stac-item
2019-07-22 09:43:39	ga_s2bm_ard_3-2-1_55KGP_2019-07-22_final.stac-item
2019-07-22 09:43:43	ga_s2bm_ard_3-2-1_55KFP_2019-07-22_final.stac-item
2019-07-22 09:43:46	ga_s2bm_ard_3-2-1_56JLT_2019-07-22_final.stac-item
2019-07-22 09:43:49	ga_s2bm_ard_3-2-1_55JHN_2019-07-22_final.stac-item
2019-07-22 09:43:50	ga_s2bm_ard_3-2-1_56JKT_2019-07-22_final.stac-item
2019-07-22 09:43:53	ga_s2bm_ard_3-2-1_55JGN_2019-07-22_final.stac-item
2019-07-22 09:43:56	ga_s2bm_ard_3-2-1_55JFN_2019-07-22_final.stac-item
2019-07-24 12:04:30	ga_s2bm_ard_3-2-1_50KMU_2019-07-24_final.stac-item
2019-07-24 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2019-07-24_final.stac-item
2019-07-24 12:04:36	ga_s2bm_ard_3-2-1_50KKU_2019-07-24_final.stac-item
2019-07-24 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-07-24_final.stac-item
2019-07-24 12:04:48	ga_s2bm_ard_3-2-1_50JLT_2019-07-24_final.stac-item
2019-07-24 12:04:51	ga_s2bm_ard_3-2-1_49JHN_2019-07-24_final.stac-item
2019-07-24 12:04:51	ga_s2bm_ard_3-2-1_50JKT_2019-07-24_final.stac-item
2019-07-24 12:04:54	ga_s2bm_ard_3-2-1_49JGN_2019-07-24_final.stac-item
2019-09-28 10:43:48	ga_s2bm_ard_3-2-1_53KPP_2019-09-28_final.stac-item
2019-09-28 10:43:52	ga_s2bm_ard_3-2-1_53KNP_2019-09-28_final.stac-item
2019-09-28 10:43:55	ga_s2bm_ard_3-2-1_53KMP_2019-09-28_final.stac-item
2019-09-28 10:43:58	ga_s2bm_ard_3-2-1_53KLP_2019-09-28_final.stac-item
2019-09-28 10:44:03	ga_s2bm_ard_3-2-1_53JPN_2019-09-28_final.stac-item
2019-09-28 10:44:06	ga_s2bm_ard_3-2-1_53JNN_2019-09-28_final.stac-item
2019-09-28 10:44:10	ga_s2bm_ard_3-2-1_53JMN_2019-09-28_final.stac-item
2019-09-28 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2019-09-28_final.stac-item
2019-10-03 09:53:51	ga_s2bm_ard_3-2-1_55JDN_2019-10-03_final.stac-item
2019-10-12 10:23:41	ga_s2bm_ard_3-2-1_54KWU_2019-10-12_final.stac-item
2019-10-12 10:23:45	ga_s2bm_ard_3-2-1_54KVU_2019-10-12_final.stac-item
2019-10-12 10:23:48	ga_s2bm_ard_3-2-1_54KUU_2019-10-12_final.stac-item
2019-10-12 10:23:51	ga_s2bm_ard_3-2-1_54KTU_2019-10-12_final.stac-item
2019-10-12 10:23:56	ga_s2bm_ard_3-2-1_54JWT_2019-10-12_final.stac-item
2019-10-12 10:23:59	ga_s2bm_ard_3-2-1_54JVT_2019-10-12_final.stac-item
2019-10-12 10:24:02	ga_s2bm_ard_3-2-1_54JUT_2019-10-12_final.stac-item
2019-10-12 10:24:05	ga_s2bm_ard_3-2-1_53JRN_2019-10-12_final.stac-item
2019-10-12 10:24:05	ga_s2bm_ard_3-2-1_54JTT_2019-10-12_final.stac-item
2019-12-04 10:33:35	ga_s2bm_ard_3-2-1_54KUU_2019-12-04_final.stac-item
2019-12-04 10:33:39	ga_s2bm_ard_3-2-1_54KTU_2019-12-04_final.stac-item
2019-12-04 10:33:43	ga_s2bm_ard_3-2-1_53KQP_2019-12-04_final.stac-item
2019-12-04 10:33:46	ga_s2bm_ard_3-2-1_54JUT_2019-12-04_final.stac-item
2019-12-04 10:33:47	ga_s2bm_ard_3-2-1_53KPP_2019-12-04_final.stac-item
2019-12-04 10:33:54	ga_s2bm_ard_3-2-1_53JRN_2019-12-04_final.stac-item
2019-12-04 10:33:54	ga_s2bm_ard_3-2-1_54JTT_2019-12-04_final.stac-item
2019-12-08 10:13:46	ga_s2bm_ard_3-2-1_54JYT_2019-12-08_final.stac-item
2019-12-08 10:13:50	ga_s2bm_ard_3-2-1_54JXT_2019-12-08_final.stac-item
2019-12-08 10:13:53	ga_s2bm_ard_3-2-1_54JWT_2019-12-08_final.stac-item
2019-12-18 10:13:32	ga_s2bm_ard_3-2-1_54KYU_2019-12-18_final.stac-item
2019-12-18 10:13:36	ga_s2bm_ard_3-2-1_54KXU_2019-12-18_final.stac-item
2019-12-18 10:13:39	ga_s2bm_ard_3-2-1_55JBN_2019-12-18_final.stac-item
2019-12-18 10:13:39	ga_s2bm_ard_3-2-1_54KWU_2019-12-18_final.stac-item
2019-12-18 10:13:40	ga_s2bm_ard_3-2-1_54JZT_2019-12-18_final.stac-item
2019-12-18 10:13:46	ga_s2bm_ard_3-2-1_54JYT_2019-12-18_final.stac-item
2019-12-18 10:13:50	ga_s2bm_ard_3-2-1_54JXT_2019-12-18_final.stac-item
2019-12-18 10:13:54	ga_s2bm_ard_3-2-1_54JWT_2019-12-18_final.stac-item
2019-12-20 10:53:44	ga_s2bm_ard_3-2-1_53KMP_2019-12-20_final.stac-item
2019-12-20 10:53:49	ga_s2bm_ard_3-2-1_53KLP_2019-12-20_final.stac-item
2019-12-20 10:53:52	ga_s2bm_ard_3-2-1_53KKP_2019-12-20_final.stac-item
2019-12-20 10:53:55	ga_s2bm_ard_3-2-1_53JMN_2019-12-20_final.stac-item
2019-12-20 10:54:03	ga_s2bm_ard_3-2-1_53JLN_2019-12-20_final.stac-item
2019-12-20 10:54:06	ga_s2bm_ard_3-2-1_52JHT_2019-12-20_final.stac-item
2019-12-20 10:54:07	ga_s2bm_ard_3-2-1_53JKN_2019-12-20_final.stac-item
2019-12-20 10:54:10	ga_s2bm_ard_3-2-1_52JGT_2019-12-20_final.stac-item
2019-12-24 12:14:22	ga_s2bm_ard_3-2-1_49KGP_2019-12-24_final.stac-item
2019-12-24 12:14:36	ga_s2bm_ard_3-2-1_49JGN_2019-12-24_final.stac-item
2019-12-24 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2019-12-24_final.stac-item
2019-12-25 10:03:26	ga_s2bm_ard_3-2-1_55KDP_2019-12-25_final.stac-item
2019-12-25 10:03:30	ga_s2bm_ard_3-2-1_55KCP_2019-12-25_final.stac-item
2019-12-25 10:03:33	ga_s2bm_ard_3-2-1_55KBP_2019-12-25_final.stac-item
2019-12-25 10:03:41	ga_s2bm_ard_3-2-1_55JDN_2019-12-25_final.stac-item
2019-12-25 10:03:45	ga_s2bm_ard_3-2-1_55JCN_2019-12-25_final.stac-item
2019-12-25 10:03:48	ga_s2bm_ard_3-2-1_54JZT_2019-12-25_final.stac-item
2019-12-25 10:03:48	ga_s2bm_ard_3-2-1_55JBN_2019-12-25_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