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
2017-10-17 09:32:26	ga_s2bm_ard_3-2-1_56JKS_2017-10-17_final.stac-item
2017-10-17 09:32:26	ga_s2bm_ard_3-2-1_56JLS_2017-10-17_final.stac-item
2017-10-17 09:32:26	ga_s2bm_ard_3-2-1_56JMS_2017-10-17_final.stac-item
2017-10-17 09:32:26	ga_s2bm_ard_3-2-1_56JNS_2017-10-17_final.stac-item
2017-10-17 09:32:26	ga_s2bm_ard_3-2-1_55JHM_2017-10-17_final.stac-item
2017-10-27 09:32:47	ga_s2bm_ard_3-2-1_56JKS_2017-10-27_final.stac-item
2017-10-27 09:32:47	ga_s2bm_ard_3-2-1_56JLS_2017-10-27_final.stac-item
2017-10-27 09:32:47	ga_s2bm_ard_3-2-1_56JMS_2017-10-27_final.stac-item
2017-10-27 09:32:47	ga_s2bm_ard_3-2-1_56JNS_2017-10-27_final.stac-item
2017-10-27 09:32:47	ga_s2bm_ard_3-2-1_55JHM_2017-10-27_final.stac-item
2017-11-04 12:13:08	ga_s2bm_ard_3-2-1_49JFM_2017-11-04_final.stac-item
2017-11-04 12:13:08	ga_s2bm_ard_3-2-1_49JGM_2017-11-04_final.stac-item
2017-11-05 09:56:54	ga_s2bm_ard_3-2-1_55JCM_2017-11-05_final.stac-item
2017-11-05 09:56:54	ga_s2bm_ard_3-2-1_55JDM_2017-11-05_final.stac-item
2017-11-05 10:03:42	ga_s2bm_ard_3-2-1_55JBM_2017-11-05_final.stac-item
2017-11-05 10:03:42	ga_s2bm_ard_3-2-1_54JYS_2017-11-05_final.stac-item
2017-11-05 10:03:42	ga_s2bm_ard_3-2-1_55JCM_2017-11-05_final.stac-item
2017-11-05 10:03:42	ga_s2bm_ard_3-2-1_54JZS_2017-11-05_final.stac-item
2017-11-05 10:03:42	ga_s2bm_ard_3-2-1_55JDM_2017-11-05_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_49JGM_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_49JHM_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JKS_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JLS_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JMS_2017-11-11_final.stac-item
2018-05-09 10:47:23	ga_s2bm_ard_3-2-1_53JKM_2018-05-09_final.stac-item
2018-05-09 10:47:23	ga_s2bm_ard_3-2-1_53JLM_2018-05-09_final.stac-item
2018-05-09 10:47:23	ga_s2bm_ard_3-2-1_52JFS_2018-05-09_final.stac-item
2018-05-09 10:47:23	ga_s2bm_ard_3-2-1_52JGS_2018-05-09_final.stac-item
2018-05-09 10:47:23	ga_s2bm_ard_3-2-1_52JHS_2018-05-09_final.stac-item
2018-05-12 09:22:43	ga_s2bm_ard_3-2-1_56JNS_2018-05-11_final.stac-item
2018-05-12 11:01:55	ga_s2bm_ard_3-2-1_52JDS_2018-05-12_final.stac-item
2018-05-12 11:01:55	ga_s2bm_ard_3-2-1_52JES_2018-05-12_final.stac-item
2018-05-12 11:01:55	ga_s2bm_ard_3-2-1_52JFS_2018-05-12_final.stac-item
2018-05-12 11:01:55	ga_s2bm_ard_3-2-1_52JGS_2018-05-12_final.stac-item
2018-05-13 10:30:42	ga_s2bm_ard_3-2-1_53JNM_2018-05-13_final.stac-item
2018-05-13 10:30:42	ga_s2bm_ard_3-2-1_53JPM_2018-05-13_final.stac-item
2018-05-13 10:30:42	ga_s2bm_ard_3-2-1_54JTS_2018-05-13_final.stac-item
2018-05-13 10:30:42	ga_s2bm_ard_3-2-1_53JQM_2018-05-13_final.stac-item
2018-05-13 10:30:42	ga_s2bm_ard_3-2-1_53JRM_2018-05-13_final.stac-item
2018-05-15 09:32:38	ga_s2bm_ard_3-2-1_56JKS_2018-05-15_final.stac-item
2018-05-15 09:32:38	ga_s2bm_ard_3-2-1_56JLS_2018-05-15_final.stac-item
2018-05-15 09:32:38	ga_s2bm_ard_3-2-1_56JMS_2018-05-15_final.stac-item
2018-05-15 09:32:38	ga_s2bm_ard_3-2-1_56JNS_2018-05-15_final.stac-item
2018-05-15 09:32:38	ga_s2bm_ard_3-2-1_55JHM_2018-05-15_final.stac-item
2018-05-16 10:37:25	ga_s2bm_ard_3-2-1_53JLM_2018-05-16_final.stac-item
2018-05-16 10:37:25	ga_s2bm_ard_3-2-1_53JMM_2018-05-16_final.stac-item
2018-05-16 10:37:25	ga_s2bm_ard_3-2-1_53JNM_2018-05-16_final.stac-item
2018-05-16 10:37:25	ga_s2bm_ard_3-2-1_53JPM_2018-05-16_final.stac-item
2018-05-17 10:07:03	ga_s2bm_ard_3-2-1_54JVS_2018-05-17_final.stac-item
2018-05-17 10:07:03	ga_s2bm_ard_3-2-1_54JWS_2018-05-17_final.stac-item
2018-05-17 10:07:03	ga_s2bm_ard_3-2-1_54JXS_2018-05-17_final.stac-item
2018-05-17 10:07:03	ga_s2bm_ard_3-2-1_54JYS_2018-05-17_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JDS_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JES_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JFS_2018-10-19_final.stac-item
2018-10-19 10:59:05	ga_s2bm_ard_3-2-1_52JGS_2018-10-19_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53JNM_2018-10-20_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53JPM_2018-10-20_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_54JTS_2018-10-20_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53JQM_2018-10-20_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53JRM_2018-10-20_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JFM_2018-10-20_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JGM_2018-10-20_final.stac-item
2018-10-21 11:38:40	ga_s2bm_ard_3-2-1_51JTM_2018-10-21_final.stac-item
2018-10-21 11:38:40	ga_s2bm_ard_3-2-1_51JUM_2018-10-21_final.stac-item
2018-10-21 11:38:40	ga_s2bm_ard_3-2-1_50JPS_2018-10-21_final.stac-item
2018-10-21 11:38:40	ga_s2bm_ard_3-2-1_50JQS_2018-10-21_final.stac-item
2018-10-21 11:38:40	ga_s2bm_ard_3-2-1_50JRS_2018-10-21_final.stac-item
2018-10-24 10:12:12	ga_s2bm_ard_3-2-1_54JVS_2018-10-24_final.stac-item
2018-10-24 10:12:12	ga_s2bm_ard_3-2-1_54JWS_2018-10-24_final.stac-item
2018-10-24 10:12:12	ga_s2bm_ard_3-2-1_54JXS_2018-10-24_final.stac-item
2018-10-24 10:12:12	ga_s2bm_ard_3-2-1_54JYS_2018-10-24_final.stac-item
2018-10-25 11:23:58	ga_s2bm_ard_3-2-1_52JBS_2018-10-25_final.stac-item
2018-10-25 11:23:58	ga_s2bm_ard_3-2-1_51JWM_2018-10-25_final.stac-item
2018-10-25 11:23:58	ga_s2bm_ard_3-2-1_51JXM_2018-10-25_final.stac-item
2018-10-25 11:23:58	ga_s2bm_ard_3-2-1_51JYM_2018-10-25_final.stac-item
2018-10-25 11:23:58	ga_s2bm_ard_3-2-1_51JZM_2018-10-25_final.stac-item
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_51JTM_2018-10-28_final.stac-item
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_51JUM_2018-10-28_final.stac-item
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_51JVM_2018-10-28_final.stac-item
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_51JWM_2018-10-28_final.stac-item
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_50JRS_2018-10-28_final.stac-item
2018-10-29 09:22:42	ga_s2bm_ard_3-2-1_56JNS_2018-10-28_final.stac-item
2018-11-03 10:13:24	ga_s2bm_ard_3-2-1_54JVS_2018-11-03_final.stac-item
2018-11-03 10:13:24	ga_s2bm_ard_3-2-1_54JWS_2018-11-03_final.stac-item
2018-11-03 10:13:24	ga_s2bm_ard_3-2-1_54JXS_2018-11-03_final.stac-item
2018-11-03 10:13:24	ga_s2bm_ard_3-2-1_54JYS_2018-11-03_final.stac-item
2018-11-05 10:53:12	ga_s2bm_ard_3-2-1_53JKM_2018-11-05_final.stac-item
2018-11-05 10:53:12	ga_s2bm_ard_3-2-1_53JLM_2018-11-05_final.stac-item
2018-11-05 10:53:12	ga_s2bm_ard_3-2-1_52JFS_2018-11-05_final.stac-item
2018-11-05 10:53:12	ga_s2bm_ard_3-2-1_52JGS_2018-11-05_final.stac-item
2018-11-05 10:53:12	ga_s2bm_ard_3-2-1_52JHS_2018-11-05_final.stac-item
2019-11-09 09:43:52	ga_s2bm_ard_3-2-1_56JLS_2019-11-09_final.stac-item
2019-11-09 09:43:55	ga_s2bm_ard_3-2-1_55JHM_2019-11-09_final.stac-item
2019-11-09 09:43:55	ga_s2bm_ard_3-2-1_56JKS_2019-11-09_final.stac-item
2019-11-09 09:43:59	ga_s2bm_ard_3-2-1_55JGM_2019-11-09_final.stac-item
2019-11-09 09:44:02	ga_s2bm_ard_3-2-1_55JFM_2019-11-09_final.stac-item
2019-11-28 11:54:44	ga_s2bm_ard_3-2-1_50JPS_2019-11-28_final.stac-item
2019-11-28 11:54:47	ga_s2bm_ard_3-2-1_50JNS_2019-11-28_final.stac-item
2019-11-28 11:54:51	ga_s2bm_ard_3-2-1_50JMS_2019-11-28_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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