Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-08-20 09:54:21	ga_s2am_ard_3-2-1_55JDG_2015-08-20_final.stac-item
2015-08-20 09:54:21	ga_s2am_ard_3-2-1_55JDL_2015-08-20_final.stac-item
2015-08-30 09:54:21	ga_s2am_ard_3-2-1_55JDL_2015-08-30_final.stac-item
2015-11-18 09:47:56	ga_s2am_ard_3-2-1_55JDL_2015-11-18_final.stac-item
2015-11-18 09:54:04	ga_s2am_ard_3-2-1_55JDL_2015-11-18_final.stac-item
2015-11-28 09:47:27	ga_s2am_ard_3-2-1_55JDL_2015-11-28_final.stac-item
2015-12-28 09:55:35	ga_s2am_ard_3-2-1_55JDL_2015-12-28_final.stac-item
2016-03-27 09:49:02	ga_s2am_ard_3-2-1_55JDG_2016-03-27_final.stac-item
2016-03-27 09:49:02	ga_s2am_ard_3-2-1_55JDL_2016-03-27_final.stac-item
2016-04-26 09:51:11	ga_s2am_ard_3-2-1_55JDL_2016-04-26_final.stac-item
2016-05-03 09:46:30	ga_s2am_ard_3-2-1_55HDA_2016-05-03_final.stac-item
2016-05-06 09:52:47	ga_s2am_ard_3-2-1_55JDL_2016-05-06_final.stac-item
2016-05-26 09:52:48	ga_s2am_ard_3-2-1_55JDL_2016-05-26_final.stac-item
2016-06-15 09:52:45	ga_s2am_ard_3-2-1_55JDL_2016-06-15_final.stac-item
2016-07-02 09:46:28	ga_s2am_ard_3-2-1_55HDA_2016-07-02_final.stac-item
2016-07-25 09:52:36	ga_s2am_ard_3-2-1_55JDL_2016-07-25_final.stac-item
2016-08-14 09:52:35	ga_s2am_ard_3-2-1_55JDL_2016-08-14_final.stac-item
2016-09-03 09:52:32	ga_s2am_ard_3-2-1_55JDL_2016-09-03_final.stac-item
2016-09-23 09:52:34	ga_s2am_ard_3-2-1_55JDL_2016-09-23_final.stac-item
2016-10-10 09:46:21	ga_s2am_ard_3-2-1_55HDA_2016-10-10_final.stac-item
2016-10-13 09:52:35	ga_s2am_ard_3-2-1_55JDL_2016-10-13_final.stac-item
2016-11-02 09:53:27	ga_s2am_ard_3-2-1_55JDL_2016-11-02_final.stac-item
2016-11-22 09:51:04	ga_s2am_ard_3-2-1_55JDL_2016-11-22_final.stac-item
2016-12-02 09:51:03	ga_s2am_ard_3-2-1_55JDL_2016-12-02_final.stac-item
2016-12-12 09:51:01	ga_s2am_ard_3-2-1_55JDL_2016-12-12_final
2017-01-01 09:52:33	ga_s2am_ard_3-2-1_55JDL_2017-01-01_final
2017-01-11 09:49:33	ga_s2am_ard_3-2-1_55JDL_2017-01-11_final
2017-02-20 09:53:49	ga_s2am_ard_3-2-1_55JDL_2017-02-20_final
2017-03-02 09:53:37	ga_s2am_ard_3-2-1_55JDL_2017-03-02_final
2017-03-22 09:52:39	ga_s2am_ard_3-2-1_55JDL_2017-03-22_final
2017-04-11 09:52:34	ga_s2am_ard_3-2-1_55JDL_2017-04-11_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JDL_2017-05-01_final
2017-05-21 09:52:38	ga_s2am_ard_3-2-1_55JDL_2017-05-21_final
2017-06-10 09:52:47	ga_s2am_ard_3-2-1_55JDL_2017-06-10_final
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JDL_2017-06-30_final
2017-07-20 09:52:25	ga_s2am_ard_3-2-1_55JDL_2017-07-20_final
2017-08-09 09:51:07	ga_s2am_ard_3-2-1_55JDL_2017-08-09_final
2017-08-09 09:54:07	ga_s2am_ard_3-2-1_55JDL_2017-08-09_final
2017-12-27 09:52:51	ga_s2am_ard_3-2-1_55JDL_2017-12-27_final
2018-05-06 09:50:57	ga_s2am_ard_3-2-1_55JDL_2018-05-06_final
2018-05-16 09:50:57	ga_s2am_ard_3-2-1_55JDL_2018-05-16_final
2018-05-26 09:50:56	ga_s2am_ard_3-2-1_55JDL_2018-05-26_final
2018-06-05 09:50:55	ga_s2am_ard_3-2-1_55JDL_2018-06-05_final
2018-06-15 09:50:53	ga_s2am_ard_3-2-1_55JDL_2018-06-15_final
2018-06-25 09:52:18	ga_s2am_ard_3-2-1_55JDL_2018-06-25_final
2018-07-05 09:50:55	ga_s2am_ard_3-2-1_55JDL_2018-07-05_final
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JDL_2018-07-15_final
2023-01-10 09:54:16	ga_s2am_ard_3-2-1_55JDL_2023-01-10_final.stac-item
2023-01-10 09:54:23	ga_s2am_ard_3-2-1_55JDL_2023-01-10_final.stac-item
2023-01-20 09:54:14	ga_s2am_ard_3-2-1_55JDL_2023-01-20_final.stac-item
2023-01-27 09:46:14	ga_s2am_ard_3-2-1_55HDC_2023-01-27_final.stac-item
2023-01-30 09:54:18	ga_s2am_ard_3-2-1_55JDL_2023-01-30_final.stac-item
2023-02-09 09:54:19	ga_s2am_ard_3-2-1_55JDL_2023-02-09_final.stac-item
2023-02-19 09:54:17	ga_s2am_ard_3-2-1_55JDL_2023-02-19_final.stac-item
2023-03-01 09:54:17	ga_s2am_ard_3-2-1_55JDL_2023-03-01_final.stac-item
2023-03-11 09:54:15	ga_s2am_ard_3-2-1_55JDL_2023-03-11_final.stac-item
2023-03-21 09:54:18	ga_s2am_ard_3-2-1_55JDL_2023-03-21_final.stac-item
2023-03-31 09:54:18	ga_s2am_ard_3-2-1_55JDL_2023-03-31_final.stac-item
2023-04-10 09:54:20	ga_s2am_ard_3-2-1_55JDL_2023-04-10_final.stac-item
2023-04-20 09:54:18	ga_s2am_ard_3-2-1_55JDL_2023-04-20_final.stac-item
2023-04-30 09:54:20	ga_s2am_ard_3-2-1_55JDL_2023-04-30_final.stac-item
2023-05-10 09:54:19	ga_s2am_ard_3-2-1_55JDL_2023-05-10_final.stac-item
2023-05-20 09:54:22	ga_s2am_ard_3-2-1_55JDL_2023-05-20_final.stac-item
2023-05-30 09:54:23	ga_s2am_ard_3-2-1_55JDL_2023-05-30_final.stac-item
2023-06-09 09:54:23	ga_s2am_ard_3-2-1_55JDL_2023-06-09_final.stac-item
2023-06-19 09:54:24	ga_s2am_ard_3-2-1_55JDL_2023-06-19_final.stac-item
2023-06-29 09:54:24	ga_s2am_ard_3-2-1_55JDL_2023-06-29_final.stac-item
2023-07-09 09:54:25	ga_s2am_ard_3-2-1_55JDL_2023-07-09_final.stac-item
2023-07-19 09:54:24	ga_s2am_ard_3-2-1_55JDL_2023-07-19_final.stac-item
2023-07-29 09:54:25	ga_s2am_ard_3-2-1_55JDL_2023-07-29_final.stac-item
2023-08-08 09:54:24	ga_s2am_ard_3-2-1_55JDL_2023-08-08_final.stac-item
2023-08-18 09:54:26	ga_s2am_ard_3-2-1_55JDL_2023-08-18_final.stac-item
2023-08-28 09:54:25	ga_s2am_ard_3-2-1_55JDL_2023-08-28_final.stac-item
2023-09-07 09:54:25	ga_s2am_ard_3-2-1_55JDL_2023-09-07_final.stac-item
2023-09-17 09:54:23	ga_s2am_ard_3-2-1_55JDL_2023-09-17_final.stac-item
2023-09-27 09:54:22	ga_s2am_ard_3-2-1_55JDL_2023-09-27_final.stac-item
2023-09-27 09:55:30	ga_s2am_ard_3-2-1_55JDF_2023-09-27_final.stac-item
2023-10-07 09:54:20	ga_s2am_ard_3-2-1_55JDL_2023-10-07_final.stac-item
2023-10-17 09:54:19	ga_s2am_ard_3-2-1_55JDL_2023-10-17_final.stac-item
2023-10-27 09:54:20	ga_s2am_ard_3-2-1_55JDL_2023-10-27_final.stac-item
2023-11-06 09:54:19	ga_s2am_ard_3-2-1_55JDL_2023-11-06_final.stac-item
2023-11-16 09:54:18	ga_s2am_ard_3-2-1_55JDL_2023-11-16_final.stac-item
2023-11-26 09:54:14	ga_s2am_ard_3-2-1_55JDL_2023-11-26_final.stac-item
2023-12-06 09:54:13	ga_s2am_ard_3-2-1_55JDL_2023-12-06_final.stac-item
2023-12-16 09:54:16	ga_s2am_ard_3-2-1_55JDL_2023-12-16_final.stac-item
2023-12-26 09:54:17	ga_s2am_ard_3-2-1_55JDL_2023-12-26_final.stac-item
2024-01-05 09:54:16	ga_s2am_ard_3-2-1_55JDL_2024-01-05_final.stac-item
2024-01-15 09:54:13	ga_s2am_ard_3-2-1_55JDL_2024-01-15_final.stac-item
2024-01-25 09:54:14	ga_s2am_ard_3-2-1_55JDL_2024-01-25_final.stac-item
2024-02-04 09:54:16	ga_s2am_ard_3-2-1_55JDL_2024-02-04_final.stac-item
2024-02-14 09:54:17	ga_s2am_ard_3-2-1_55JDL_2024-02-14_final.stac-item
2024-02-24 09:54:18	ga_s2am_ard_3-2-1_55JDL_2024-02-24_final.stac-item
2024-03-05 09:54:20	ga_s2am_ard_3-2-1_55JDL_2024-03-05_final.stac-item
2024-03-15 09:54:19	ga_s2am_ard_3-2-1_55JDL_2024-03-15_final.stac-item
2024-03-25 09:54:21	ga_s2am_ard_3-2-1_55JDL_2024-03-25_final.stac-item
2024-04-04 09:54:17	ga_s2am_ard_3-2-1_55JDL_2024-04-04_final.stac-item
2024-04-11 09:46:46	ga_s2am_ard_3-2-1_55HDA_2024-04-11_final.stac-item
2024-04-14 09:54:22	ga_s2am_ard_3-2-1_55JDL_2024-04-14_final.stac-item
2024-04-24 09:54:22	ga_s2am_ard_3-2-1_55JDL_2024-04-24_final.stac-item
2024-05-04 09:54:23	ga_s2am_ard_3-2-1_55JDL_2024-05-04_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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