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
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_56HKK_2016-01-01_final.stac-item
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_56HLK_2016-01-01_final.stac-item
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_56JKL_2016-01-01_final.stac-item
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_56JLL_2016-01-01_final.stac-item
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_56JML_2016-01-01_final.stac-item
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_55HGE_2016-01-01_final.stac-item
2016-01-01 09:39:15	ga_s2am_ard_3-2-1_55JGF_2016-01-01_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_51HXE_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_51HYE_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_51JXF_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_51JYF_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_52HBK_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_52JBL_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_52JCL_2016-01-11_final.stac-item
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_52HCK_2016-01-11_final
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53HPE_2016-01-29_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53HQE_2016-01-29_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53JMF_2016-01-29_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53JNF_2016-01-29_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53JPF_2016-01-29_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53JQF_2016-01-29_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_53HLE_2016-07-10_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_53JKF_2016-07-10_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_53JLF_2016-07-10_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_53JMF_2016-07-10_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_52JGL_2016-07-10_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_53HKE_2016-07-10_final
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_52HGK_2016-07-10_final
2016-07-11 10:11:13	ga_s2am_ard_3-2-1_54JUL_2016-07-11_final.stac-item
2016-07-11 10:11:13	ga_s2am_ard_3-2-1_54JVL_2016-07-11_final.stac-item
2016-07-11 10:11:13	ga_s2am_ard_3-2-1_54JWL_2016-07-11_final.stac-item
2016-07-11 10:11:13	ga_s2am_ard_3-2-1_54JXL_2016-07-11_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50HPK_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50HQK_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50JPL_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50JQL_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51HTE_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51HUE_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51JTF_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51JUF_2016-07-15_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51JVF_2016-07-15_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HLK_2016-07-21_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JLL_2016-07-21_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JML_2016-07-21_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JNL_2016-07-21_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HPK_2016-07-28_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HQK_2016-07-28_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50JML_2016-07-28_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50JNL_2016-07-28_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50JPL_2016-07-28_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50JQL_2016-07-28_final.stac-item
2016-07-29 11:09:08	ga_s2am_ard_3-2-1_51HXE_2016-07-29_final.stac-item
2016-07-29 11:09:08	ga_s2am_ard_3-2-1_51HYE_2016-07-29_final.stac-item
2016-07-29 11:09:08	ga_s2am_ard_3-2-1_51JXF_2016-07-29_final.stac-item
2016-07-29 11:09:08	ga_s2am_ard_3-2-1_51JYF_2016-07-29_final.stac-item
2016-07-29 11:09:08	ga_s2am_ard_3-2-1_52HCK_2016-07-29_final
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_56HKK_2016-08-08_final.stac-item
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_56HLK_2016-08-08_final.stac-item
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_56JKL_2016-08-08_final.stac-item
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_56JLL_2016-08-08_final.stac-item
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_56JML_2016-08-08_final.stac-item
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_55HGE_2016-08-08_final.stac-item
2016-08-08 09:33:48	ga_s2am_ard_3-2-1_55JGF_2016-08-08_final.stac-item
2018-12-18 10:15:28	ga_s2am_ard_3-2-1_54JXL_2018-12-18_final.stac-item
2018-12-18 10:15:32	ga_s2am_ard_3-2-1_54JWL_2018-12-18_final
2018-12-18 10:15:35	ga_s2am_ard_3-2-1_54JVL_2018-12-18_final.stac-item
2018-12-18 10:15:39	ga_s2am_ard_3-2-1_54JUL_2018-12-18_final.stac-item
2018-12-23 11:05:51	ga_s2am_ard_3-2-1_52JEL_2018-12-23_final.stac-item
2018-12-23 11:05:55	ga_s2am_ard_3-2-1_52JDL_2018-12-23_final.stac-item
2018-12-23 11:05:58	ga_s2am_ard_3-2-1_52JCL_2018-12-23_final.stac-item
2018-12-23 11:06:02	ga_s2am_ard_3-2-1_52JBL_2018-12-23_final.stac-item
2018-12-23 11:06:16	ga_s2am_ard_3-2-1_52HBK_2018-12-23_final.stac-item
2019-01-02 11:05:53	ga_s2am_ard_3-2-1_52JEL_2019-01-02_final.stac-item
2019-01-02 11:05:57	ga_s2am_ard_3-2-1_52JDL_2019-01-02_final.stac-item
2019-01-02 11:06:00	ga_s2am_ard_3-2-1_52JCL_2019-01-02_final.stac-item
2019-01-02 11:06:04	ga_s2am_ard_3-2-1_52JBL_2019-01-02_final.stac-item
2019-01-02 11:06:18	ga_s2am_ard_3-2-1_52HBK_2019-01-02_final.stac-item
2019-07-26 11:56:23	ga_s2am_ard_3-2-1_50JNL_2019-07-26_final.stac-item
2019-07-26 11:56:27	ga_s2am_ard_3-2-1_50JML_2019-07-26_final.stac-item
2019-07-26 11:56:30	ga_s2am_ard_3-2-1_50JLL_2019-07-26_final.stac-item
2019-07-26 11:56:45	ga_s2am_ard_3-2-1_50HLK_2019-07-26_final.stac-item
2019-07-27 09:45:27	ga_s2am_ard_3-2-1_56JKL_2019-07-27_final.stac-item
2019-07-27 09:45:30	ga_s2am_ard_3-2-1_55JGF_2019-07-27_final.stac-item
2019-07-27 09:45:34	ga_s2am_ard_3-2-1_55JFF_2019-07-27_final.stac-item
2019-07-27 09:45:37	ga_s2am_ard_3-2-1_56HKK_2019-07-27_final.stac-item
2019-07-27 09:45:38	ga_s2am_ard_3-2-1_55JEF_2019-07-27_final.stac-item
2019-07-27 09:45:42	ga_s2am_ard_3-2-1_55JDF_2019-07-27_final.stac-item
2019-07-27 09:45:45	ga_s2am_ard_3-2-1_55HGE_2019-07-27_final.stac-item
2019-07-27 09:45:49	ga_s2am_ard_3-2-1_55HFE_2019-07-27_final.stac-item
2019-07-30 09:55:34	ga_s2am_ard_3-2-1_55JEF_2019-07-30_final.stac-item
2019-07-30 09:55:37	ga_s2am_ard_3-2-1_55JDF_2019-07-30_final.stac-item
2019-07-30 09:55:41	ga_s2am_ard_3-2-1_55JCF_2019-07-30_final.stac-item
2019-07-30 09:55:44	ga_s2am_ard_3-2-1_55JBF_2019-07-30_final.stac-item
2019-07-30 09:55:55	ga_s2am_ard_3-2-1_55HCE_2019-07-30_final.stac-item
2019-08-02 10:05:42	ga_s2am_ard_3-2-1_54JYL_2019-08-02_final.stac-item
2019-08-02 10:05:43	ga_s2am_ard_3-2-1_55HCE_2019-08-02_final.stac-item
2019-08-02 10:05:46	ga_s2am_ard_3-2-1_54JXL_2019-08-02_final.stac-item
2019-08-02 10:05:49	ga_s2am_ard_3-2-1_54JWL_2019-08-02_final.stac-item
2019-08-02 10:05:54	ga_s2am_ard_3-2-1_55HBE_2019-08-02_final.stac-item
2019-08-02 10:05:56	ga_s2am_ard_3-2-1_54HYK_2019-08-02_final.stac-item

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

Other products

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