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
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JNQ_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JNR_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JPQ_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JPR_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JQQ_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JQR_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_51JTK_2016-06-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_51JTL_2016-06-18_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JLQ_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JLR_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JMR_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JNQ_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JNR_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JPQ_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JPR_2016-07-01_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JNQ_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JNR_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JPQ_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JPR_2018-06-11_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_56JKQ_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_56JKR_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_56JLQ_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_56JLR_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_55JEK_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_55JFK_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_55JFL_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_55JGK_2018-06-12_final.stac-item
2018-06-12 09:41:08	ga_s2am_ard_3-2-1_55JGL_2018-06-12_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JCK_2018-06-25_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JCL_2018-06-25_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JDL_2018-06-25_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JEK_2018-06-25_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JEL_2018-06-25_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JFK_2018-06-25_final.stac-item
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JFL_2018-06-25_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JCQ_2018-06-26_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JCR_2018-06-26_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JDR_2018-06-26_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JEQ_2018-06-26_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JER_2018-06-26_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JFQ_2018-06-26_final.stac-item
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JFR_2018-06-26_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_54JXQ_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_54JXR_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_54JYQ_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_54JYR_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_55JBK_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_55JBL_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_55JCK_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_55JCL_2018-06-28_final.stac-item
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_55JDL_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JNQ_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JNR_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JPQ_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JPR_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JQQ_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JQR_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51JTK_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51JTL_2018-06-28_final.stac-item
2018-12-17 10:44:26	ga_s2am_ard_3-2-1_53JNL_2018-12-17_final.stac-item
2018-12-17 10:44:30	ga_s2am_ard_3-2-1_53JML_2018-12-17_final.stac-item
2018-12-17 10:44:33	ga_s2am_ard_3-2-1_53JLL_2018-12-17_final.stac-item
2018-12-17 10:44:39	ga_s2am_ard_3-2-1_53JKL_2018-12-17_final.stac-item
2018-12-17 10:44:48	ga_s2am_ard_3-2-1_53JLK_2018-12-17_final.stac-item
2018-12-17 10:44:51	ga_s2am_ard_3-2-1_53JKK_2018-12-17_final.stac-item
2018-12-22 09:54:05	ga_s2am_ard_3-2-1_55JFL_2018-12-22_final.stac-item
2018-12-22 09:54:08	ga_s2am_ard_3-2-1_55JEL_2018-12-22_final.stac-item
2018-12-22 09:54:11	ga_s2am_ard_3-2-1_55JDL_2018-12-22_final.stac-item
2018-12-22 09:54:14	ga_s2am_ard_3-2-1_55JCL_2018-12-22_final.stac-item
2018-12-22 09:54:19	ga_s2am_ard_3-2-1_55JFK_2018-12-22_final.stac-item
2018-12-22 09:54:23	ga_s2am_ard_3-2-1_55JEK_2018-12-22_final.stac-item
2018-12-22 09:54:29	ga_s2am_ard_3-2-1_55JCK_2018-12-22_final.stac-item
2018-12-26 11:14:39	ga_s2am_ard_3-2-1_52JDR_2018-12-26_final.stac-item
2018-12-26 11:14:42	ga_s2am_ard_3-2-1_52JCR_2018-12-26_final.stac-item
2018-12-26 11:14:45	ga_s2am_ard_3-2-1_52JBR_2018-12-26_final.stac-item
2018-12-26 11:14:48	ga_s2am_ard_3-2-1_51JYL_2018-12-26_final.stac-item
2018-12-26 11:14:57	ga_s2am_ard_3-2-1_52JCQ_2018-12-26_final.stac-item
2018-12-26 11:15:00	ga_s2am_ard_3-2-1_52JBQ_2018-12-26_final.stac-item
2018-12-26 11:15:03	ga_s2am_ard_3-2-1_51JYK_2018-12-26_final.stac-item
2018-12-27 10:44:28	ga_s2am_ard_3-2-1_53JNL_2018-12-27_final.stac-item
2018-12-27 10:44:32	ga_s2am_ard_3-2-1_53JML_2018-12-27_final.stac-item
2018-12-27 10:44:35	ga_s2am_ard_3-2-1_53JLL_2018-12-27_final.stac-item
2018-12-31 12:05:02	ga_s2am_ard_3-2-1_50JLR_2018-12-31_final.stac-item
2018-12-31 12:05:05	ga_s2am_ard_3-2-1_50JKR_2018-12-31_final.stac-item
2018-12-31 12:05:09	ga_s2am_ard_3-2-1_49JGL_2018-12-31_final.stac-item
2018-12-31 12:05:16	ga_s2am_ard_3-2-1_50JLQ_2018-12-31_final.stac-item
2018-12-31 12:05:20	ga_s2am_ard_3-2-1_50JKQ_2018-12-31_final.stac-item
2018-12-31 12:05:23	ga_s2am_ard_3-2-1_49JGK_2018-12-31_final.stac-item
2019-01-01 09:54:07	ga_s2am_ard_3-2-1_55JFL_2019-01-01_final.stac-item
2019-01-01 09:54:10	ga_s2am_ard_3-2-1_55JEL_2019-01-01_final.stac-item
2019-01-01 09:54:14	ga_s2am_ard_3-2-1_55JDL_2019-01-01_final.stac-item
2019-01-01 09:54:17	ga_s2am_ard_3-2-1_55JCL_2019-01-01_final.stac-item
2019-01-01 09:54:21	ga_s2am_ard_3-2-1_55JFK_2019-01-01_final.stac-item
2019-01-01 09:54:25	ga_s2am_ard_3-2-1_55JEK_2019-01-01_final.stac-item
2019-01-01 09:54:31	ga_s2am_ard_3-2-1_55JCK_2019-01-01_final.stac-item
2019-01-06 10:44:30	ga_s2am_ard_3-2-1_53JNL_2019-01-06_final.stac-item
2019-01-06 10:44:34	ga_s2am_ard_3-2-1_53JML_2019-01-06_final.stac-item
2019-01-06 10:44:37	ga_s2am_ard_3-2-1_53JLL_2019-01-06_final.stac-item
2019-01-06 10:44:43	ga_s2am_ard_3-2-1_53JKL_2019-01-06_final.stac-item
2019-01-06 10:44:51	ga_s2am_ard_3-2-1_53JLK_2019-01-06_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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