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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
2019-04-25 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-04-25_final
2019-05-02 11:05:08	ga_s2am_ard_3-2-1_52JDQ_2019-05-02_final
2019-05-05 11:15:04	ga_s2am_ard_3-2-1_52JDQ_2019-05-05_final
2019-05-12 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2019-05-12_final
2019-05-15 11:15:04	ga_s2am_ard_3-2-1_52JDQ_2019-05-15_final
2019-05-22 11:05:08	ga_s2am_ard_3-2-1_52JDQ_2019-05-22_final
2019-05-25 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-05-25_final
2019-06-01 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2019-06-01_final
2019-06-04 11:15:02	ga_s2am_ard_3-2-1_52JDQ_2019-06-04_final
2019-06-11 11:05:08	ga_s2am_ard_3-2-1_52JDQ_2019-06-11_final
2019-06-14 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-06-14_final
2019-06-21 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2019-06-21_final
2019-06-24 11:15:04	ga_s2am_ard_3-2-1_52JDQ_2019-06-24_final
2019-07-01 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2019-07-01_final
2019-07-04 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2019-07-04_final
2019-07-11 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2019-07-11_final
2019-07-14 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2019-07-14_final
2019-07-21 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2019-07-21_final
2019-07-24 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2019-07-24_final
2019-07-31 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2019-07-31_final
2019-08-03 11:15:04	ga_s2am_ard_3-2-1_52JDQ_2019-08-03_final
2019-08-10 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2019-08-10_final
2019-08-13 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-08-13_final
2019-08-20 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2019-08-20_final
2019-08-23 11:15:02	ga_s2am_ard_3-2-1_52JDQ_2019-08-23_final
2019-08-30 11:05:06	ga_s2am_ard_3-2-1_52JDQ_2019-08-30_final
2019-09-02 11:15:00	ga_s2am_ard_3-2-1_52JDQ_2019-09-02_final
2019-09-09 11:05:04	ga_s2am_ard_3-2-1_52JDQ_2019-09-09_final
2019-09-12 11:14:58	ga_s2am_ard_3-2-1_52JDQ_2019-09-12_final
2019-09-19 11:05:04	ga_s2am_ard_3-2-1_52JDQ_2019-09-19_final
2019-09-22 11:15:00	ga_s2am_ard_3-2-1_52JDQ_2019-09-22_final
2019-09-29 11:05:06	ga_s2am_ard_3-2-1_52JDQ_2019-09-29_final
2019-10-02 11:15:02	ga_s2am_ard_3-2-1_52JDQ_2019-10-02_final
2019-10-09 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2019-10-09_final
2019-10-12 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-10-12_final
2019-10-19 11:05:08	ga_s2am_ard_3-2-1_52JDQ_2019-10-19_final
2019-10-22 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-10-22_final
2019-10-29 11:05:08	ga_s2am_ard_3-2-1_52JDQ_2019-10-29_final
2019-11-01 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-11-01_final
2019-11-08 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2019-11-08_final
2019-11-11 11:15:02	ga_s2am_ard_3-2-1_52JDQ_2019-11-11_final
2019-11-18 11:05:06	ga_s2am_ard_3-2-1_52JDQ_2019-11-18_final
2019-11-21 11:15:01	ga_s2am_ard_3-2-1_52JDQ_2019-11-21_final
2019-11-28 11:05:04	ga_s2am_ard_3-2-1_52JDQ_2019-11-28_final
2019-12-01 11:14:59	ga_s2am_ard_3-2-1_52JDQ_2019-12-01_final
2019-12-08 11:05:02	ga_s2am_ard_3-2-1_52JDQ_2019-12-08_final
2019-12-11 11:14:56	ga_s2am_ard_3-2-1_52JDQ_2019-12-11_final
2019-12-18 11:04:59	ga_s2am_ard_3-2-1_52JDQ_2019-12-18_final
2019-12-21 11:14:54	ga_s2am_ard_3-2-1_52JDQ_2019-12-21_final
2019-12-28 11:04:59	ga_s2am_ard_3-2-1_52JDQ_2019-12-28_final
2019-12-31 11:14:55	ga_s2am_ard_3-2-1_52JDQ_2019-12-31_final
2020-01-07 11:04:59	ga_s2am_ard_3-2-1_52JDQ_2020-01-07_final
2020-01-10 11:14:54	ga_s2am_ard_3-2-1_52JDQ_2020-01-10_final
2020-01-17 11:04:59	ga_s2am_ard_3-2-1_52JDQ_2020-01-17_final
2020-01-20 11:14:54	ga_s2am_ard_3-2-1_52JDQ_2020-01-20_final
2020-01-27 11:04:58	ga_s2am_ard_3-2-1_52JDQ_2020-01-27_final
2020-01-30 11:14:53	ga_s2am_ard_3-2-1_52JDQ_2020-01-30_final
2020-02-06 11:04:56	ga_s2am_ard_3-2-1_52JDQ_2020-02-06_final
2020-02-09 11:14:52	ga_s2am_ard_3-2-1_52JDQ_2020-02-09_final
2020-02-16 11:04:58	ga_s2am_ard_3-2-1_52JDQ_2020-02-16_final
2020-02-19 11:14:54	ga_s2am_ard_3-2-1_52JDQ_2020-02-19_final
2020-02-26 11:05:00	ga_s2am_ard_3-2-1_52JDQ_2020-02-26_final
2020-02-29 11:14:55	ga_s2am_ard_3-2-1_52JDQ_2020-02-29_final
2020-03-07 11:05:01	ga_s2am_ard_3-2-1_52JDQ_2020-03-07_final
2020-03-10 11:14:56	ga_s2am_ard_3-2-1_52JDQ_2020-03-10_final
2020-03-17 11:05:01	ga_s2am_ard_3-2-1_52JDQ_2020-03-17_final
2020-03-20 11:14:56	ga_s2am_ard_3-2-1_52JDQ_2020-03-20_final
2020-03-27 11:05:01	ga_s2am_ard_3-2-1_52JDQ_2020-03-27_final
2020-03-30 11:14:56	ga_s2am_ard_3-2-1_52JDQ_2020-03-30_final
2020-04-06 11:05:02	ga_s2am_ard_3-2-1_52JDQ_2020-04-06_final
2020-04-09 11:14:58	ga_s2am_ard_3-2-1_52JDQ_2020-04-09_final
2020-04-16 11:05:04	ga_s2am_ard_3-2-1_52JDQ_2020-04-16_final
2020-04-19 11:15:00	ga_s2am_ard_3-2-1_52JDQ_2020-04-19_final
2020-04-26 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2020-04-26_final
2020-04-29 11:15:02	ga_s2am_ard_3-2-1_52JDQ_2020-04-29_final
2020-05-06 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2020-05-06_final
2020-05-09 11:15:04	ga_s2am_ard_3-2-1_52JDQ_2020-05-09_final
2020-05-16 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2020-05-16_final
2020-05-19 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2020-05-19_final
2020-05-26 11:05:11	ga_s2am_ard_3-2-1_52JDQ_2020-05-26_final
2020-05-29 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-05-29_final
2020-06-05 11:05:11	ga_s2am_ard_3-2-1_52JDQ_2020-06-05_final
2020-06-08 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-06-08_final
2020-06-15 11:05:11	ga_s2am_ard_3-2-1_52JDQ_2020-06-15_final
2020-06-18 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-06-18_final
2020-06-25 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2020-06-25_final
2020-06-28 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2020-06-28_final
2020-07-05 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2020-07-05_final
2020-07-08 11:15:04	ga_s2am_ard_3-2-1_52JDQ_2020-07-08_final
2020-07-15 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2020-07-15_final
2020-07-18 11:15:05	ga_s2am_ard_3-2-1_52JDQ_2020-07-18_final
2020-07-25 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2020-07-25_final
2020-07-28 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-07-28_final
2020-08-04 11:05:11	ga_s2am_ard_3-2-1_52JDQ_2020-08-04_final
2020-08-07 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-08-07_final
2020-08-14 11:05:11	ga_s2am_ard_3-2-1_52JDQ_2020-08-14_final
2020-08-17 11:15:06	ga_s2am_ard_3-2-1_52JDQ_2020-08-17_final
2020-08-24 11:05:10	ga_s2am_ard_3-2-1_52JDQ_2020-08-24_final
2022-01-16 11:05:05	ga_s2am_ard_3-2-1_52JDQ_2022-01-16_final
2022-03-27 11:05:07	ga_s2am_ard_3-2-1_52JDQ_2022-03-27_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