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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
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KGP_2017-05-13_final
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49KGP_2017-06-02_final
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49KGP_2017-06-22_final
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGP_2017-07-12_final
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49KGP_2017-08-21_final
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KGP_2017-09-30_final
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KGP_2017-11-09_final
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGP_2017-11-19_final
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KGP_2017-11-29_final
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49KGP_2018-01-08_final
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-02-17_final
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-02-27_final
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-04-08_final
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-04-18_final
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-04-28_final
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49KGP_2018-05-08_final
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-05-18_final
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-05-28_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-06-17_final
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-06-27_final
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-07-07_final
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KGP_2018-07-27_final
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-08-06_final
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-08-16_final
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KGP_2018-08-26_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGP_2018-09-05_final
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-15_final
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-15_final
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-25_final
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-25_final
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2018-11-04_final
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KGP_2018-11-04_final
2018-11-14 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2018-11-14_final
2018-11-14 12:14:19	ga_s2am_ard_3-2-1_49KGP_2018-11-14_final
2018-11-14 12:14:25	ga_s2am_ard_3-2-1_49KGP_2018-11-14_final
2018-11-24 12:14:05	ga_s2am_ard_3-2-1_49KGQ_2018-11-24_final
2018-11-24 12:14:19	ga_s2am_ard_3-2-1_49KGP_2018-11-24_final
2018-12-04 12:14:04	ga_s2am_ard_3-2-1_49KGQ_2018-12-04_final
2018-12-14 12:14:04	ga_s2am_ard_3-2-1_49KGQ_2018-12-14_final
2018-12-24 12:14:05	ga_s2am_ard_3-2-1_49KGQ_2018-12-24_final
2019-01-03 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2019-01-03_final
2019-01-13 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2019-01-13_final
2019-01-23 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-01-23_final
2019-02-02 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2019-02-02_final
2019-02-12 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-02-12_final
2019-02-22 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-02-22_final
2019-03-04 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2019-03-04_final
2019-03-14 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-03-14_final
2019-03-24 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2019-03-24_final
2019-04-03 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-04-03_final
2019-04-13 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-04-13_final
2019-04-23 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-04-23_final
2019-05-03 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-05-03_final
2019-05-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-05-13_final
2019-05-23 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-05-23_final
2019-06-02 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-06-02_final
2019-06-12 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-06-12_final
2019-06-22 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2019-06-22_final
2019-07-02 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2019-07-02_final
2019-07-12 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2019-07-12_final
2019-07-22 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2019-07-22_final
2019-08-01 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-08-01_final
2019-08-01 12:14:23	ga_s2am_ard_3-2-1_49KGQ_2019-08-01_final
2019-08-11 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-08-11_final
2019-08-21 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-08-21_final
2019-08-31 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-08-31_final
2019-09-10 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2019-09-10_final
2019-09-20 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-09-20_final
2019-09-30 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2019-09-30_final
2019-10-10 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-10-10_final
2019-10-20 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-10-20_final
2019-10-30 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-10-30_final
2019-11-09 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-11-09_final
2019-11-19 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2019-11-19_final
2019-11-29 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2019-11-29_final
2019-12-09 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-12-09_final
2019-12-19 12:14:06	ga_s2am_ard_3-2-1_49KGQ_2019-12-19_final
2019-12-29 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2019-12-29_final
2020-01-08 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2020-01-08_final
2020-01-18 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2020-01-18_final
2020-01-28 12:14:05	ga_s2am_ard_3-2-1_49KGQ_2020-01-28_final
2022-02-06 12:14:26	ga_s2am_ard_3-2-1_49KGP_2022-02-06_final
2022-02-16 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-02-16_final
2022-02-26 12:14:30	ga_s2am_ard_3-2-1_49KGP_2022-02-26_final
2022-03-08 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-03-08_final
2022-03-18 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-03-18_final
2022-03-28 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final
2022-04-07 12:14:28	ga_s2am_ard_3-2-1_49KGP_2022-04-07_final
2022-04-17 12:14:30	ga_s2am_ard_3-2-1_49KGP_2022-04-17_final
2022-04-27 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-04-27_final
2022-05-07 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-05-07_final
2022-05-17 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-05-17_final
2022-05-27 12:14:34	ga_s2am_ard_3-2-1_49KGP_2022-05-27_final
2022-06-06 12:14:35	ga_s2am_ard_3-2-1_49KGP_2022-06-06_final
2022-06-16 12:14:38	ga_s2am_ard_3-2-1_49KGP_2022-06-16_final
2022-06-26 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-06-26_final
2022-07-06 12:14:40	ga_s2am_ard_3-2-1_49KGP_2022-07-06_final
2022-07-16 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-07-16_final
2022-07-26 12:14:37	ga_s2am_ard_3-2-1_49KGP_2022-07-26_final
2022-08-05 12:14:38	ga_s2am_ard_3-2-1_49KGP_2022-08-05_final

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

All years