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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
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50KRD_2018-09-09_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50KRD_2018-09-19_final
2018-09-26 11:34:41	ga_s2am_ard_3-2-1_50KRD_2018-09-26_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50KRD_2018-09-26_final
2018-09-29 11:48:21	ga_s2am_ard_3-2-1_50KRD_2018-09-29_final
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50KRD_2018-10-06_final
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KRD_2018-10-09_final
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50KRD_2018-10-16_final
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KRD_2018-10-19_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50KRD_2018-10-26_final
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KRD_2018-10-29_final
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_50KRD_2018-11-05_final
2018-11-08 11:52:54	ga_s2am_ard_3-2-1_50KRD_2018-11-08_final
2018-11-15 11:42:58	ga_s2am_ard_3-2-1_50KRD_2018-11-15_final
2018-11-18 11:52:53	ga_s2am_ard_3-2-1_50KRD_2018-11-18_final
2018-11-25 11:42:56	ga_s2am_ard_3-2-1_50KRD_2018-11-25_final
2018-11-28 11:52:50	ga_s2am_ard_3-2-1_50KRD_2018-11-28_final
2018-12-08 11:52:50	ga_s2am_ard_3-2-1_50KRD_2018-12-08_final
2018-12-15 11:42:55	ga_s2am_ard_3-2-1_50KRD_2018-12-15_final
2018-12-18 11:52:50	ga_s2am_ard_3-2-1_50KRD_2018-12-18_final
2018-12-25 11:42:56	ga_s2am_ard_3-2-1_50KRD_2018-12-25_final
2018-12-28 11:52:52	ga_s2am_ard_3-2-1_50KRD_2018-12-28_final
2019-01-04 11:42:58	ga_s2am_ard_3-2-1_50KRD_2019-01-04_final
2019-01-07 11:52:54	ga_s2am_ard_3-2-1_50KRD_2019-01-07_final
2019-01-14 11:43:00	ga_s2am_ard_3-2-1_50KRD_2019-01-14_final
2019-01-17 11:52:55	ga_s2am_ard_3-2-1_50KRD_2019-01-17_final
2019-01-24 11:43:01	ga_s2am_ard_3-2-1_50KRD_2019-01-24_final
2019-01-27 11:52:56	ga_s2am_ard_3-2-1_50KRD_2019-01-27_final
2019-02-03 11:43:01	ga_s2am_ard_3-2-1_50KRD_2019-02-03_final
2019-02-06 11:52:56	ga_s2am_ard_3-2-1_50KRD_2019-02-06_final
2019-02-13 11:43:01	ga_s2am_ard_3-2-1_50KRD_2019-02-13_final
2019-02-16 11:52:55	ga_s2am_ard_3-2-1_50KRD_2019-02-16_final
2019-02-23 11:43:00	ga_s2am_ard_3-2-1_50KRD_2019-02-23_final
2019-02-26 11:52:54	ga_s2am_ard_3-2-1_50KRD_2019-02-26_final
2019-03-05 11:42:59	ga_s2am_ard_3-2-1_50KRD_2019-03-05_final
2019-03-08 11:52:53	ga_s2am_ard_3-2-1_50KRD_2019-03-08_final
2019-03-15 11:43:00	ga_s2am_ard_3-2-1_50KRD_2019-03-15_final
2019-03-18 11:52:56	ga_s2am_ard_3-2-1_50KRD_2019-03-18_final
2019-03-25 11:43:03	ga_s2am_ard_3-2-1_50KRD_2019-03-25_final
2019-03-28 11:52:58	ga_s2am_ard_3-2-1_50KRD_2019-03-28_final
2019-04-04 11:43:05	ga_s2am_ard_3-2-1_50KRD_2019-04-04_final
2019-04-07 11:53:00	ga_s2am_ard_3-2-1_50KRD_2019-04-07_final
2019-04-14 11:43:06	ga_s2am_ard_3-2-1_50KRD_2019-04-14_final
2019-04-17 11:53:01	ga_s2am_ard_3-2-1_50KRD_2019-04-17_final
2019-04-24 11:43:07	ga_s2am_ard_3-2-1_50KRD_2019-04-24_final
2019-04-27 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-04-27_final
2019-05-04 11:43:08	ga_s2am_ard_3-2-1_50KRD_2019-05-04_final
2019-05-07 11:53:03	ga_s2am_ard_3-2-1_50KRD_2019-05-07_final
2019-05-14 11:43:08	ga_s2am_ard_3-2-1_50KRD_2019-05-14_final
2019-05-17 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-05-17_final
2019-05-24 11:43:07	ga_s2am_ard_3-2-1_50KRD_2019-05-24_final
2019-05-27 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-05-27_final
2019-06-03 11:43:06	ga_s2am_ard_3-2-1_50KRD_2019-06-03_final
2019-06-06 11:53:01	ga_s2am_ard_3-2-1_50KRD_2019-06-06_final
2019-06-13 11:43:07	ga_s2am_ard_3-2-1_50KRD_2019-06-13_final
2019-06-16 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-06-16_final
2019-06-23 11:43:08	ga_s2am_ard_3-2-1_50KRD_2019-06-23_final
2019-06-26 11:53:03	ga_s2am_ard_3-2-1_50KRD_2019-06-26_final
2019-07-03 11:43:09	ga_s2am_ard_3-2-1_50KRD_2019-07-03_final
2019-07-06 11:53:04	ga_s2am_ard_3-2-1_50KRD_2019-07-06_final
2019-07-13 11:43:09	ga_s2am_ard_3-2-1_50KRD_2019-07-13_final
2019-07-16 11:53:04	ga_s2am_ard_3-2-1_50KRD_2019-07-16_final
2019-07-23 11:43:09	ga_s2am_ard_3-2-1_50KRD_2019-07-23_final
2019-07-26 11:53:04	ga_s2am_ard_3-2-1_50KRD_2019-07-26_final
2019-08-02 11:43:08	ga_s2am_ard_3-2-1_50KRD_2019-08-02_final
2019-08-05 11:53:03	ga_s2am_ard_3-2-1_50KRD_2019-08-05_final
2019-08-12 11:43:02	ga_s2am_ard_3-2-1_50KRD_2019-08-12_final
2019-08-12 11:43:09	ga_s2am_ard_3-2-1_50KRD_2019-08-12_final
2019-08-15 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-08-15_final
2019-08-22 11:43:06	ga_s2am_ard_3-2-1_50KRD_2019-08-22_final
2019-08-25 11:53:01	ga_s2am_ard_3-2-1_50KRD_2019-08-25_final
2019-09-01 11:43:04	ga_s2am_ard_3-2-1_50KRD_2019-09-01_final
2019-09-04 11:52:59	ga_s2am_ard_3-2-1_50KRD_2019-09-04_final
2019-09-11 11:43:02	ga_s2am_ard_3-2-1_50KRD_2019-09-11_final
2019-09-14 11:52:57	ga_s2am_ard_3-2-1_50KRD_2019-09-14_final
2019-09-21 11:43:04	ga_s2am_ard_3-2-1_50KRD_2019-09-21_final
2019-10-01 11:43:06	ga_s2am_ard_3-2-1_50KRD_2019-10-01_final
2019-10-04 11:53:01	ga_s2am_ard_3-2-1_50KRD_2019-10-04_final
2019-10-11 11:43:01	ga_s2am_ard_3-2-1_50KRD_2019-10-11_final
2019-10-11 11:43:08	ga_s2am_ard_3-2-1_50KRD_2019-10-11_final
2019-10-14 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-10-14_final
2019-10-21 11:43:07	ga_s2am_ard_3-2-1_50KRD_2019-10-21_final
2019-10-24 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-10-24_final
2019-10-31 11:43:07	ga_s2am_ard_3-2-1_50KRD_2019-10-31_final
2019-11-03 11:53:02	ga_s2am_ard_3-2-1_50KRD_2019-11-03_final
2019-11-10 11:43:03	ga_s2am_ard_3-2-1_50KRD_2019-11-10_final
2019-11-10 11:43:10	ga_s2am_ard_3-2-1_50KRD_2019-11-10_final
2019-11-13 11:53:01	ga_s2am_ard_3-2-1_50KRD_2019-11-13_final
2019-11-20 11:43:05	ga_s2am_ard_3-2-1_50KRD_2019-11-20_final
2019-11-23 11:52:59	ga_s2am_ard_3-2-1_50KRD_2019-11-23_final
2019-11-30 11:43:03	ga_s2am_ard_3-2-1_50KRD_2019-11-30_final
2019-12-03 11:52:57	ga_s2am_ard_3-2-1_50KRD_2019-12-03_final
2019-12-10 11:43:00	ga_s2am_ard_3-2-1_50KRD_2019-12-10_final
2019-12-13 11:52:54	ga_s2am_ard_3-2-1_50KRD_2019-12-13_final
2019-12-20 11:42:58	ga_s2am_ard_3-2-1_50KRD_2019-12-20_final
2019-12-23 11:52:53	ga_s2am_ard_3-2-1_50KRD_2019-12-23_final
2021-08-24 11:53:01	ga_s2am_ard_3-2-1_50KRD_2021-08-24_final
2021-10-23 11:53:04	ga_s2am_ard_3-2-1_50KRD_2021-10-23_final
2021-11-19 11:43:04	ga_s2am_ard_3-2-1_50KRD_2021-11-19_final
2021-12-09 11:43:03	ga_s2am_ard_3-2-1_50KRD_2021-12-09_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