Search ga_s2am_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
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JML_2016-04-19_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JNL_2016-04-19_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JPL_2016-04-19_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JQL_2016-04-19_final.stac-item
2016-04-22 10:14:47	ga_s2am_ard_3-2-1_54JUL_2016-04-22_final.stac-item
2016-04-22 10:14:47	ga_s2am_ard_3-2-1_54JVL_2016-04-22_final.stac-item
2016-04-22 10:14:47	ga_s2am_ard_3-2-1_54JWL_2016-04-22_final.stac-item
2016-04-22 10:14:47	ga_s2am_ard_3-2-1_54JXL_2016-04-22_final.stac-item
2016-04-27 11:01:40	ga_s2am_ard_3-2-1_52JBL_2016-04-27_final.stac-item
2016-04-27 11:01:40	ga_s2am_ard_3-2-1_52JEL_2016-04-27_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HQK_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50JPL_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50JQL_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JTF_2016-05-16_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JUF_2016-05-16_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLL_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JML_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNL_2016-05-22_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51JUF_2016-05-23_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51JVF_2016-05-23_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51JWF_2016-05-23_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51JXF_2016-05-23_final.stac-item
2016-05-24 10:55:20	ga_s2am_ard_3-2-1_53JKF_2016-05-24_final.stac-item
2016-05-24 10:55:20	ga_s2am_ard_3-2-1_52JEL_2016-05-24_final.stac-item
2016-05-24 10:55:20	ga_s2am_ard_3-2-1_52JFL_2016-05-24_final.stac-item
2016-05-24 10:55:20	ga_s2am_ard_3-2-1_52JGL_2016-05-24_final.stac-item
2016-05-24 10:55:20	ga_s2am_ard_3-2-1_52HGK_2016-05-24_final
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JML_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JNL_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JPL_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JQL_2016-10-16_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JLL_2016-10-19_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JML_2016-10-19_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JNL_2016-10-19_final.stac-item
2016-10-20 09:43:09	ga_s2am_ard_3-2-1_55JDF_2016-10-20_final.stac-item
2016-10-20 09:43:09	ga_s2am_ard_3-2-1_55JFF_2016-10-20_final.stac-item
2016-10-20 11:26:04	ga_s2am_ard_3-2-1_51JUF_2016-10-20_final.stac-item
2016-10-20 11:26:04	ga_s2am_ard_3-2-1_51JVF_2016-10-20_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JKF_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLF_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JMF_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_52JGL_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_52HGK_2016-10-28_final
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51JUF_2016-10-30_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51JVF_2016-10-30_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51JWF_2016-10-30_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51JXF_2016-10-30_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HQK_2016-11-02_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50JPL_2016-11-02_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50JQL_2016-11-02_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_51JTF_2016-11-02_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_51JUF_2016-11-02_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_51JVF_2016-11-02_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53JMF_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53JNF_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53JPF_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53JQF_2016-11-04_final.stac-item
2017-05-14 10:01:19	ga_s2am_ard_3-2-1_54HYK_2017-05-14_final.stac-item
2017-05-14 10:01:19	ga_s2am_ard_3-2-1_54JWL_2017-05-14_final.stac-item
2017-05-14 10:01:19	ga_s2am_ard_3-2-1_54JXL_2017-05-14_final.stac-item
2017-05-14 10:01:19	ga_s2am_ard_3-2-1_54JYL_2017-05-14_final.stac-item
2017-05-14 10:01:19	ga_s2am_ard_3-2-1_55JBF_2017-05-14_final.stac-item
2017-05-14 10:01:19	ga_s2am_ard_3-2-1_55JCF_2017-05-14_final.stac-item
2017-05-21 09:52:38	ga_s2am_ard_3-2-1_54HYK_2017-05-21_final.stac-item
2017-05-21 09:52:38	ga_s2am_ard_3-2-1_55JBF_2017-05-21_final.stac-item
2017-05-21 09:52:38	ga_s2am_ard_3-2-1_55JCF_2017-05-21_final.stac-item
2017-05-21 09:52:38	ga_s2am_ard_3-2-1_55JDF_2017-05-21_final.stac-item
2017-05-21 09:52:38	ga_s2am_ard_3-2-1_55JEF_2017-05-21_final.stac-item
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_50HQK_2017-06-10_final.stac-item
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_50JQL_2017-06-10_final.stac-item
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_51JTF_2017-06-10_final.stac-item
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_51JUF_2017-06-10_final.stac-item
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_51JVF_2017-06-10_final.stac-item
2017-06-11 09:22:46	ga_s2am_ard_3-2-1_56JLL_2017-06-10_final.stac-item
2017-06-11 09:22:46	ga_s2am_ard_3-2-1_56JML_2017-06-10_final.stac-item
2017-06-11 09:22:46	ga_s2am_ard_3-2-1_56JNL_2017-06-10_final.stac-item
2022-11-18 11:26:09	ga_s2am_ard_3-2-1_51JXF_2022-11-18_final.stac-item
2022-11-18 11:26:13	ga_s2am_ard_3-2-1_51JWF_2022-11-18_final.stac-item
2022-11-18 11:26:16	ga_s2am_ard_3-2-1_51JVF_2022-11-18_final.stac-item
2022-11-18 11:26:19	ga_s2am_ard_3-2-1_51JUF_2022-11-18_final.stac-item
2022-11-26 10:45:51	ga_s2am_ard_3-2-1_53JMF_2022-11-26_final.stac-item
2022-11-26 10:45:54	ga_s2am_ard_3-2-1_53JLF_2022-11-26_final.stac-item
2022-11-26 10:45:57	ga_s2am_ard_3-2-1_53JKF_2022-11-26_final.stac-item
2022-11-26 10:45:59	ga_s2am_ard_3-2-1_52JGL_2022-11-26_final.stac-item
2022-11-28 11:26:07	ga_s2am_ard_3-2-1_51JXF_2022-11-28_final.stac-item
2022-11-28 11:26:11	ga_s2am_ard_3-2-1_51JWF_2022-11-28_final.stac-item
2022-11-28 11:26:14	ga_s2am_ard_3-2-1_51JVF_2022-11-28_final.stac-item
2022-11-28 11:26:18	ga_s2am_ard_3-2-1_51JUF_2022-11-28_final.stac-item
2022-12-01 09:55:29	ga_s2am_ard_3-2-1_55JEF_2022-12-01_final.stac-item
2022-12-01 09:55:33	ga_s2am_ard_3-2-1_55JDF_2022-12-01_final.stac-item
2022-12-01 09:55:36	ga_s2am_ard_3-2-1_55JCF_2022-12-01_final.stac-item
2022-12-01 09:55:39	ga_s2am_ard_3-2-1_55JBF_2022-12-01_final.stac-item
2022-12-01 09:55:57	ga_s2am_ard_3-2-1_54HYK_2022-12-01_final.stac-item
2022-12-04 10:05:29	ga_s2am_ard_3-2-1_55JCF_2022-12-04_final.stac-item
2022-12-04 10:05:35	ga_s2am_ard_3-2-1_55JBF_2022-12-04_final.stac-item
2022-12-04 10:05:38	ga_s2am_ard_3-2-1_54JYL_2022-12-04_final.stac-item
2022-12-04 10:05:41	ga_s2am_ard_3-2-1_54JXL_2022-12-04_final.stac-item
2022-12-04 10:05:45	ga_s2am_ard_3-2-1_54JWL_2022-12-04_final.stac-item
2022-12-04 10:05:52	ga_s2am_ard_3-2-1_54HYK_2022-12-04_final.stac-item
2022-12-06 09:05:10	ga_s2am_ard_3-2-1_57JWF_2022-12-05_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

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