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
2016-10-17 09:32:13	ga_s2am_ard_3-2-1_56KMU_2016-10-17_final.stac-item
2016-10-17 09:32:13	ga_s2am_ard_3-2-1_56JLT_2016-10-17_final.stac-item
2016-10-17 09:32:13	ga_s2am_ard_3-2-1_56JMT_2016-10-17_final.stac-item
2016-10-17 09:32:13	ga_s2am_ard_3-2-1_56JNT_2016-10-17_final.stac-item
2016-10-17 09:32:13	ga_s2am_ard_3-2-1_56KLU_2016-10-17_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JPT_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JQT_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JRT_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_51JTN_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_51JUN_2016-10-26_final.stac-item
2016-10-27 09:32:14	ga_s2am_ard_3-2-1_56KMU_2016-10-27_final.stac-item
2016-10-27 09:32:14	ga_s2am_ard_3-2-1_56JLT_2016-10-27_final.stac-item
2016-10-27 09:32:14	ga_s2am_ard_3-2-1_56JMT_2016-10-27_final.stac-item
2016-10-27 09:32:14	ga_s2am_ard_3-2-1_56JNT_2016-10-27_final.stac-item
2016-10-27 09:32:14	ga_s2am_ard_3-2-1_56KLU_2016-10-27_final.stac-item
2017-09-28 09:52:00	ga_s2am_ard_3-2-1_55JFN_2017-09-28_final.stac-item
2017-09-28 09:52:00	ga_s2am_ard_3-2-1_55JGN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_50JRT_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JTN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JUN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JVN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JWN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JXN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KUP_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KVP_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KWP_2017-09-28_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JLT_2017-10-04_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JMT_2017-10-04_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JNT_2017-10-04_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JPT_2017-10-04_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50KLU_2017-10-04_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50KMU_2017-10-04_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50KNU_2017-10-04_final.stac-item
2017-10-05 09:41:06	ga_s2am_ard_3-2-1_56JKT_2017-10-05_final.stac-item
2017-10-05 09:41:06	ga_s2am_ard_3-2-1_56JLT_2017-10-05_final.stac-item
2017-10-05 09:41:06	ga_s2am_ard_3-2-1_55JFN_2017-10-05_final.stac-item
2017-10-05 09:41:06	ga_s2am_ard_3-2-1_55JGN_2017-10-05_final.stac-item
2017-10-05 09:41:06	ga_s2am_ard_3-2-1_55JHN_2017-10-05_final.stac-item
2018-04-12 10:10:23	ga_s2am_ard_3-2-1_54JWT_2018-04-12_final.stac-item
2018-04-12 10:10:23	ga_s2am_ard_3-2-1_54JXT_2018-04-12_final.stac-item
2018-04-12 10:10:23	ga_s2am_ard_3-2-1_54JYT_2018-04-12_final.stac-item
2018-04-12 10:10:23	ga_s2am_ard_3-2-1_54JZT_2018-04-12_final.stac-item
2018-04-12 10:10:23	ga_s2am_ard_3-2-1_54KWU_2018-04-12_final.stac-item
2018-04-12 10:10:23	ga_s2am_ard_3-2-1_55JBN_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JLT_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JMT_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JNT_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JPT_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JQT_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50KLU_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50KMU_2018-04-12_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50KNU_2018-04-12_final.stac-item
2018-04-13 09:41:10	ga_s2am_ard_3-2-1_56JKT_2018-04-13_final.stac-item
2018-04-13 09:41:10	ga_s2am_ard_3-2-1_56JLT_2018-04-13_final.stac-item
2018-04-13 09:41:10	ga_s2am_ard_3-2-1_55JFN_2018-04-13_final.stac-item
2018-04-13 09:41:10	ga_s2am_ard_3-2-1_55JGN_2018-04-13_final.stac-item
2018-04-13 09:41:10	ga_s2am_ard_3-2-1_55JHN_2018-04-13_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50JKT_2018-04-15_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50JLT_2018-04-15_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50JMT_2018-04-15_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50KLU_2018-04-15_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50KMU_2018-04-15_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49JGN_2018-04-15_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-04-15_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_54JYT_2018-04-19_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_54JZT_2018-04-19_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_55JBN_2018-04-19_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_55JCN_2018-04-19_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_55JDN_2018-04-19_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_55KCP_2018-04-19_final.stac-item
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_55KDP_2018-04-19_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_50JPT_2018-04-19_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_50JQT_2018-04-19_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_50JRT_2018-04-19_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_51JTN_2018-04-19_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_51JUN_2018-04-19_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54JTT_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54JUT_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54JVT_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54JWT_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54KUU_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54KVU_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54KWU_2018-04-25_final.stac-item
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_53JRN_2018-04-25_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50JRT_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51JTN_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51JUN_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51JVN_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51JWN_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51JXN_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51KUP_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51KVP_2018-04-26_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51KWP_2018-04-26_final.stac-item
2018-04-27 09:22:47	ga_s2am_ard_3-2-1_56JNT_2018-04-26_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JFN_2018-04-28_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JGN_2018-04-28_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_50JPT_2018-04-29_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_50JQT_2018-04-29_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_50JRT_2018-04-29_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51JTN_2018-04-29_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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