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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JNL_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JNM_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JNN_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JNP_2015-11-14_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JNQ_2015-11-14_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNS_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNT_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50KNA_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50KNB_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50KNC_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50KNU_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50KNV_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNL_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNM_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNN_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNP_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNQ_2015-12-04_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JNR_2015-12-04_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNH_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNJ_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNK_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNL_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNM_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNN_2016-01-20_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50HNG_2016-01-20_final
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNN_2016-02-02_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNP_2016-02-02_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNQ_2016-02-02_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNR_2016-02-02_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JNS_2016-02-02_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JNM_2018-02-01_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JNN_2018-02-01_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JNP_2018-02-01_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JNQ_2018-02-01_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50JNL_2018-02-01_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50JNM_2018-02-01_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JNP_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JNQ_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JNR_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JNS_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JNT_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50KNA_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50KNB_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50KNC_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50KNU_2018-02-11_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50KNV_2018-02-11_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50JNL_2018-02-11_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50JNM_2018-02-11_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50JNN_2018-02-11_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50JNP_2018-02-11_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNL_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNM_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNN_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNP_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNQ_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNR_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNS_2018-02-21_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JNT_2018-02-21_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50KNB_2018-02-24_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50KNC_2018-02-24_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50JNS_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50JNT_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KNA_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KNB_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KNC_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KNU_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KNV_2018-03-03_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNL_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNM_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNN_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNP_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNQ_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNR_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNS_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JNT_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50KNA_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50KNB_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50KNC_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50KNU_2018-03-13_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50KNV_2018-03-13_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HNH_2018-03-20_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HNJ_2018-03-20_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HNK_2018-03-20_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50JNL_2018-03-20_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50JNM_2018-03-20_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50JNN_2018-03-20_final.stac-item
2018-11-18 11:53:18	ga_s2am_ard_3-2-1_50KNC_2018-11-18_final.stac-item
2018-11-18 11:53:33	ga_s2am_ard_3-2-1_50KNB_2018-11-18_final.stac-item
2018-12-08 11:54:14	ga_s2am_ard_3-2-1_50KNU_2018-12-08_final.stac-item
2018-12-08 11:54:29	ga_s2am_ard_3-2-1_50JNT_2018-12-08_final.stac-item
2018-12-08 11:54:43	ga_s2am_ard_3-2-1_50JNS_2018-12-08_final.stac-item
2018-12-08 11:54:58	ga_s2am_ard_3-2-1_50JNR_2018-12-08_final.stac-item
2018-12-08 11:55:12	ga_s2am_ard_3-2-1_50JNQ_2018-12-08_final.stac-item
2018-12-08 11:55:26	ga_s2am_ard_3-2-1_50JNP_2018-12-08_final.stac-item
2018-12-08 11:55:41	ga_s2am_ard_3-2-1_50JNN_2018-12-08_final.stac-item
2018-12-08 11:55:56	ga_s2am_ard_3-2-1_50JNM_2018-12-08_final.stac-item
2018-12-08 11:56:10	ga_s2am_ard_3-2-1_50JNL_2018-12-08_final.stac-item
2019-06-13 11:47:09	ga_s2am_ard_3-2-1_50HNH_2019-06-13_final.stac-item
2019-06-16 11:53:28	ga_s2am_ard_3-2-1_50KNC_2019-06-16_final.stac-item
2019-06-16 11:53:42	ga_s2am_ard_3-2-1_50KNB_2019-06-16_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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