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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
2018-09-05 10:27:05	ga_s2am_ard_3-2-1_53JQL_2018-09-05_final
2018-09-15 10:27:04	ga_s2am_ard_3-2-1_53JQL_2018-09-15_final
2018-09-17 09:32:36	ga_s2am_ard_3-2-1_55JHM_2018-09-17_final
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53JQL_2018-09-25_final
2018-09-27 09:32:36	ga_s2am_ard_3-2-1_55JHM_2018-09-27_final
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55JHM_2018-09-30_final
2018-10-05 10:27:04	ga_s2am_ard_3-2-1_53JQL_2018-10-05_final
2018-10-10 09:41:06	ga_s2am_ard_3-2-1_55JHM_2018-10-10_final
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQL_2018-10-15_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55JHM_2018-10-17_final
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55JHM_2018-10-20_final
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53JQL_2018-10-25_final
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_55JHM_2018-10-27_final
2018-11-04 10:27:04	ga_s2am_ard_3-2-1_53JQL_2018-11-04_final
2018-11-09 09:43:51	ga_s2am_ard_3-2-1_55JHM_2018-11-09_final
2018-11-14 10:34:27	ga_s2am_ard_3-2-1_53JQL_2018-11-14_final
2018-11-19 09:43:49	ga_s2am_ard_3-2-1_55JHM_2018-11-19_final
2018-11-24 10:34:25	ga_s2am_ard_3-2-1_53JQL_2018-11-24_final
2018-11-26 09:33:53	ga_s2am_ard_3-2-1_55JHM_2018-11-26_final
2018-11-29 09:43:47	ga_s2am_ard_3-2-1_55JHM_2018-11-29_final
2018-12-04 10:34:24	ga_s2am_ard_3-2-1_53JQL_2018-12-04_final
2018-12-09 09:43:47	ga_s2am_ard_3-2-1_55JHM_2018-12-09_final
2018-12-14 10:34:24	ga_s2am_ard_3-2-1_53JQL_2018-12-14_final
2018-12-19 09:43:47	ga_s2am_ard_3-2-1_55JHM_2018-12-19_final
2018-12-24 10:34:25	ga_s2am_ard_3-2-1_53JQL_2018-12-24_final
2018-12-26 09:33:53	ga_s2am_ard_3-2-1_55JHM_2018-12-26_final
2018-12-29 09:43:49	ga_s2am_ard_3-2-1_55JHM_2018-12-29_final
2019-01-03 10:34:27	ga_s2am_ard_3-2-1_53JQL_2019-01-03_final
2019-01-13 10:34:28	ga_s2am_ard_3-2-1_53JQL_2019-01-13_final
2019-01-15 09:33:57	ga_s2am_ard_3-2-1_55JHM_2019-01-15_final
2019-01-18 09:43:52	ga_s2am_ard_3-2-1_55JHM_2019-01-18_final
2019-01-23 10:34:29	ga_s2am_ard_3-2-1_53JQL_2019-01-23_final
2019-01-28 09:43:52	ga_s2am_ard_3-2-1_55JHM_2019-01-28_final
2019-02-02 10:34:29	ga_s2am_ard_3-2-1_53JQL_2019-02-02_final
2019-02-04 09:33:58	ga_s2am_ard_3-2-1_55JHM_2019-02-04_final
2019-02-12 10:34:29	ga_s2am_ard_3-2-1_53JQL_2019-02-12_final
2019-02-14 09:33:57	ga_s2am_ard_3-2-1_55JHM_2019-02-14_final
2019-02-22 10:34:28	ga_s2am_ard_3-2-1_53JQL_2019-02-22_final
2019-02-24 09:33:57	ga_s2am_ard_3-2-1_55JHM_2019-02-24_final
2019-02-27 09:43:51	ga_s2am_ard_3-2-1_55JHM_2019-02-27_final
2019-03-04 10:34:27	ga_s2am_ard_3-2-1_53JQL_2019-03-04_final
2019-03-09 09:43:50	ga_s2am_ard_3-2-1_55JHM_2019-03-09_final
2019-03-14 10:34:29	ga_s2am_ard_3-2-1_53JQL_2019-03-14_final
2019-03-19 09:43:53	ga_s2am_ard_3-2-1_55JHM_2019-03-19_final
2019-03-24 10:34:31	ga_s2am_ard_3-2-1_53JQL_2019-03-24_final
2019-04-03 10:34:33	ga_s2am_ard_3-2-1_53JQL_2019-04-03_final
2019-04-13 10:34:35	ga_s2am_ard_3-2-1_53JQL_2019-04-13_final
2019-04-23 10:34:36	ga_s2am_ard_3-2-1_53JQL_2019-04-23_final
2019-05-03 10:34:36	ga_s2am_ard_3-2-1_53JQL_2019-05-03_final
2020-06-22 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-06-22_final
2020-07-02 10:54:49	ga_s2am_ard_3-2-1_52JGR_2020-07-02_final
2020-07-12 10:54:48	ga_s2am_ard_3-2-1_52JGR_2020-07-12_final
2020-07-22 10:54:49	ga_s2am_ard_3-2-1_52JGR_2020-07-22_final
2020-08-01 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-08-01_final
2020-08-11 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-08-11_final
2020-08-21 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-08-21_final
2020-08-31 10:54:49	ga_s2am_ard_3-2-1_52JGR_2020-08-31_final
2020-09-10 10:54:48	ga_s2am_ard_3-2-1_52JGR_2020-09-10_final
2020-09-20 10:54:49	ga_s2am_ard_3-2-1_52JGR_2020-09-20_final
2020-09-30 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-09-30_final
2020-10-10 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-10-10_final
2020-10-20 10:54:50	ga_s2am_ard_3-2-1_52JGR_2020-10-20_final
2020-10-30 10:54:49	ga_s2am_ard_3-2-1_52JGR_2020-10-30_final
2020-11-09 10:54:48	ga_s2am_ard_3-2-1_52JGR_2020-11-09_final
2020-11-19 10:54:47	ga_s2am_ard_3-2-1_52JGR_2020-11-19_final
2020-11-29 10:54:44	ga_s2am_ard_3-2-1_52JGR_2020-11-29_final
2020-12-09 10:54:41	ga_s2am_ard_3-2-1_52JGR_2020-12-09_final
2020-12-19 10:54:42	ga_s2am_ard_3-2-1_52JGR_2020-12-19_final
2021-01-08 10:54:45	ga_s2am_ard_3-2-1_52JGR_2021-01-08_final
2021-01-18 10:54:45	ga_s2am_ard_3-2-1_52JGR_2021-01-18_final
2021-01-28 10:54:45	ga_s2am_ard_3-2-1_52JGR_2021-01-28_final
2021-02-07 10:54:43	ga_s2am_ard_3-2-1_52JGR_2021-02-07_final
2021-02-17 10:54:43	ga_s2am_ard_3-2-1_52JGR_2021-02-17_final
2022-01-27 10:34:30	ga_s2am_ard_3-2-1_53JQL_2022-01-27_final
2022-02-06 10:34:32	ga_s2am_ard_3-2-1_53JQL_2022-02-06_final
2022-02-16 10:34:33	ga_s2am_ard_3-2-1_53JQL_2022-02-16_final
2022-02-26 10:34:35	ga_s2am_ard_3-2-1_53JQL_2022-02-26_final
2022-03-08 10:34:36	ga_s2am_ard_3-2-1_53JQL_2022-03-08_final
2022-03-18 10:34:32	ga_s2am_ard_3-2-1_53JQL_2022-03-18_final
2022-03-28 10:34:35	ga_s2am_ard_3-2-1_53JQL_2022-03-28_final
2022-04-07 10:34:33	ga_s2am_ard_3-2-1_53JQL_2022-04-07_final
2022-04-17 10:34:36	ga_s2am_ard_3-2-1_53JQL_2022-04-17_final
2022-04-27 10:34:38	ga_s2am_ard_3-2-1_53JQL_2022-04-27_final
2022-05-07 10:34:37	ga_s2am_ard_3-2-1_53JQL_2022-05-07_final
2022-05-17 10:34:38	ga_s2am_ard_3-2-1_53JQL_2022-05-17_final
2022-05-27 10:34:40	ga_s2am_ard_3-2-1_53JQL_2022-05-27_final
2022-06-06 10:34:40	ga_s2am_ard_3-2-1_53JQL_2022-06-06_final.stac-item
2022-06-16 10:34:43	ga_s2am_ard_3-2-1_53JQL_2022-06-16_final
2022-06-26 10:34:45	ga_s2am_ard_3-2-1_53JQL_2022-06-26_final
2022-07-06 10:34:46	ga_s2am_ard_3-2-1_53JQL_2022-07-06_final
2022-07-16 10:34:45	ga_s2am_ard_3-2-1_53JQL_2022-07-16_final
2022-07-26 10:34:43	ga_s2am_ard_3-2-1_53JQL_2022-07-26_final
2022-08-05 10:34:43	ga_s2am_ard_3-2-1_53JQL_2022-08-05_final
2022-08-15 10:34:45	ga_s2am_ard_3-2-1_53JQL_2022-08-15_final
2022-08-25 10:34:45	ga_s2am_ard_3-2-1_53JQL_2022-08-25_final
2022-09-04 10:34:44	ga_s2am_ard_3-2-1_53JQL_2022-09-04_final.stac-item
2022-09-24 10:34:40	ga_s2am_ard_3-2-1_53JQL_2022-09-24_final.stac-item
2022-10-04 10:34:40	ga_s2am_ard_3-2-1_53JQL_2022-10-04_final.stac-item
2022-10-24 10:34:35	ga_s2am_ard_3-2-1_53JQL_2022-10-24_final.stac-item
2022-11-03 10:34:37	ga_s2am_ard_3-2-1_53JQL_2022-11-03_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

All years