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
2018-08-05 10:07:00	ga_s2bm_ard_3-2-1_55JBN_2018-08-05_final.stac-item
2018-08-05 10:07:00	ga_s2bm_ard_3-2-1_54JXT_2018-08-05_final.stac-item
2018-08-05 10:07:00	ga_s2bm_ard_3-2-1_54JYT_2018-08-05_final.stac-item
2018-08-05 10:07:00	ga_s2bm_ard_3-2-1_54JZT_2018-08-05_final.stac-item
2018-08-05 10:13:40	ga_s2bm_ard_3-2-1_54JWT_2018-08-05_final.stac-item
2018-08-05 10:13:40	ga_s2bm_ard_3-2-1_54JXT_2018-08-05_final.stac-item
2018-08-05 10:13:40	ga_s2bm_ard_3-2-1_54JYT_2018-08-05_final.stac-item
2018-08-08 12:02:45	ga_s2bm_ard_3-2-1_49JHN_2018-08-08_final.stac-item
2018-08-08 12:02:45	ga_s2bm_ard_3-2-1_50JKT_2018-08-08_final.stac-item
2018-08-08 12:02:45	ga_s2bm_ard_3-2-1_50JLT_2018-08-08_final.stac-item
2018-08-08 12:02:45	ga_s2bm_ard_3-2-1_50JMT_2018-08-08_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_49JGN_2018-08-08_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_49JHN_2018-08-08_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JKT_2018-08-08_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_51JTN_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_51JUN_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_51JVN_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_51JWN_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50JRT_2018-08-09_final.stac-item
2018-08-10 09:22:40	ga_s2bm_ard_3-2-1_56JNT_2018-08-09_final.stac-item
2018-08-10 09:23:23	ga_s2bm_ard_3-2-1_56JNT_2018-08-09_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_51JTN_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_51JUN_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JPT_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQT_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JRT_2018-08-12_final.stac-item
2018-08-15 10:06:58	ga_s2bm_ard_3-2-1_55JBN_2018-08-15_final.stac-item
2018-08-15 10:06:58	ga_s2bm_ard_3-2-1_54JXT_2018-08-15_final.stac-item
2018-08-15 10:06:58	ga_s2bm_ard_3-2-1_54JYT_2018-08-15_final.stac-item
2018-08-15 10:06:58	ga_s2bm_ard_3-2-1_54JZT_2018-08-15_final.stac-item
2018-08-15 10:13:38	ga_s2bm_ard_3-2-1_54JWT_2018-08-15_final.stac-item
2018-08-15 10:13:38	ga_s2bm_ard_3-2-1_54JXT_2018-08-15_final.stac-item
2018-08-15 10:13:38	ga_s2bm_ard_3-2-1_54JYT_2018-08-15_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_49JGN_2018-08-18_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_49JHN_2018-08-18_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_50JKT_2018-08-18_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_50JLT_2018-08-18_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_50JMT_2018-08-18_final.stac-item
2018-08-21 10:30:58	ga_s2bm_ard_3-2-1_53JNN_2018-08-21_final.stac-item
2018-08-21 10:30:58	ga_s2bm_ard_3-2-1_53JPN_2018-08-21_final.stac-item
2018-08-21 10:30:58	ga_s2bm_ard_3-2-1_54JTT_2018-08-21_final.stac-item
2018-08-21 10:30:58	ga_s2bm_ard_3-2-1_53JQN_2018-08-21_final.stac-item
2018-08-21 10:30:58	ga_s2bm_ard_3-2-1_54JUT_2018-08-21_final.stac-item
2018-08-21 10:30:58	ga_s2bm_ard_3-2-1_53JRN_2018-08-21_final.stac-item
2018-08-21 12:13:39	ga_s2bm_ard_3-2-1_49JFN_2018-08-21_final.stac-item
2018-08-21 12:13:39	ga_s2bm_ard_3-2-1_49JGN_2018-08-21_final.stac-item
2018-08-23 09:32:32	ga_s2bm_ard_3-2-1_56JLT_2018-08-23_final.stac-item
2018-08-23 09:32:32	ga_s2bm_ard_3-2-1_56JMT_2018-08-23_final.stac-item
2018-08-23 09:32:32	ga_s2bm_ard_3-2-1_56JNT_2018-08-23_final.stac-item
2019-02-10 10:44:03	ga_s2bm_ard_3-2-1_53JPN_2019-02-10_final.stac-item
2019-02-10 10:44:06	ga_s2bm_ard_3-2-1_53JNN_2019-02-10_final.stac-item
2019-02-10 10:44:10	ga_s2bm_ard_3-2-1_53JMN_2019-02-10_final.stac-item
2019-02-10 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2019-02-10_final.stac-item
2019-02-11 10:13:44	ga_s2bm_ard_3-2-1_55JBN_2019-02-11_final.stac-item
2019-02-11 10:13:45	ga_s2bm_ard_3-2-1_54JZT_2019-02-11_final.stac-item
2019-02-11 10:13:52	ga_s2bm_ard_3-2-1_54JYT_2019-02-11_final.stac-item
2019-02-11 10:13:56	ga_s2bm_ard_3-2-1_54JXT_2019-02-11_final.stac-item
2019-02-11 10:13:59	ga_s2bm_ard_3-2-1_54JWT_2019-02-11_final.stac-item
2019-02-11 10:14:06	ga_s2bm_ard_3-2-1_54JVT_2019-02-11_final.stac-item
2019-02-16 11:04:11	ga_s2bm_ard_3-2-1_52JGT_2019-02-16_final.stac-item
2019-02-16 11:04:14	ga_s2bm_ard_3-2-1_52JFT_2019-02-16_final.stac-item
2019-02-16 11:04:18	ga_s2bm_ard_3-2-1_52JET_2019-02-16_final.stac-item
2019-02-16 11:04:21	ga_s2bm_ard_3-2-1_52JDT_2019-02-16_final.stac-item
2019-02-17 10:34:13	ga_s2bm_ard_3-2-1_53JNN_2019-02-17_final.stac-item
2019-02-21 10:13:43	ga_s2bm_ard_3-2-1_55JBN_2019-02-21_final.stac-item
2019-02-21 10:13:45	ga_s2bm_ard_3-2-1_54JZT_2019-02-21_final.stac-item
2019-02-21 10:13:51	ga_s2bm_ard_3-2-1_54JYT_2019-02-21_final.stac-item
2019-02-21 10:13:55	ga_s2bm_ard_3-2-1_54JXT_2019-02-21_final.stac-item
2019-02-21 10:13:58	ga_s2bm_ard_3-2-1_54JWT_2019-02-21_final.stac-item
2019-02-25 11:34:24	ga_s2bm_ard_3-2-1_51JWN_2019-02-25_final.stac-item
2019-02-25 11:34:28	ga_s2bm_ard_3-2-1_51JVN_2019-02-25_final.stac-item
2019-02-25 11:34:31	ga_s2bm_ard_3-2-1_51JUN_2019-02-25_final.stac-item
2019-02-25 11:34:35	ga_s2bm_ard_3-2-1_51JTN_2019-02-25_final.stac-item
2019-02-25 11:34:36	ga_s2bm_ard_3-2-1_50JRT_2019-02-25_final.stac-item
2019-02-27 10:33:51	ga_s2bm_ard_3-2-1_54JUT_2019-02-27_final.stac-item
2019-02-27 10:33:58	ga_s2bm_ard_3-2-1_53JRN_2019-02-27_final.stac-item
2019-02-27 10:33:58	ga_s2bm_ard_3-2-1_54JTT_2019-02-27_final.stac-item
2019-02-27 10:34:02	ga_s2bm_ard_3-2-1_53JQN_2019-02-27_final.stac-item
2019-02-27 10:34:06	ga_s2bm_ard_3-2-1_53JPN_2019-02-27_final.stac-item
2019-02-27 10:34:12	ga_s2bm_ard_3-2-1_53JNN_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
2019-06-04 12:04:44	ga_s2bm_ard_3-2-1_50JMT_2019-06-04_final.stac-item
2019-06-04 12:04:47	ga_s2bm_ard_3-2-1_50JLT_2019-06-04_final.stac-item
2019-06-04 12:04:50	ga_s2bm_ard_3-2-1_49JHN_2019-06-04_final.stac-item
2019-06-15 11:34:32	ga_s2bm_ard_3-2-1_51JWN_2019-06-15_final.stac-item
2019-06-15 11:34:36	ga_s2bm_ard_3-2-1_51JVN_2019-06-15_final.stac-item
2019-06-15 11:34:39	ga_s2bm_ard_3-2-1_51JUN_2019-06-15_final.stac-item
2019-06-15 11:34:43	ga_s2bm_ard_3-2-1_51JTN_2019-06-15_final.stac-item
2019-06-15 11:34:44	ga_s2bm_ard_3-2-1_50JRT_2019-06-15_final.stac-item
2019-06-25 11:34:33	ga_s2bm_ard_3-2-1_51JWN_2019-06-25_final.stac-item
2019-06-25 11:34:37	ga_s2bm_ard_3-2-1_51JVN_2019-06-25_final.stac-item
2019-06-25 11:34:40	ga_s2bm_ard_3-2-1_51JUN_2019-06-25_final.stac-item
2019-06-25 11:34:44	ga_s2bm_ard_3-2-1_51JTN_2019-06-25_final.stac-item
2019-06-25 11:34:45	ga_s2bm_ard_3-2-1_50JRT_2019-06-25_final.stac-item
2020-04-14 11:14:04	ga_s2bm_ard_3-2-1_52JET_2020-04-14_final.stac-item
2020-04-14 11:14:12	ga_s2bm_ard_3-2-1_52JDT_2020-04-14_final.stac-item
2020-04-14 11:14:16	ga_s2bm_ard_3-2-1_52JCT_2020-04-14_final.stac-item
2020-04-14 11:14:19	ga_s2bm_ard_3-2-1_51JZN_2020-04-14_final.stac-item
2020-04-14 11:14:19	ga_s2bm_ard_3-2-1_52JBT_2020-04-14_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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