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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
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JHN_2018-04-25_final
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JHN_2018-05-05_final
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49JHN_2018-05-08_final
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JHN_2018-05-15_final
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49JHN_2018-05-18_final
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_49JHN_2018-05-25_final
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49JHN_2018-05-28_final
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_49JHN_2018-06-04_final
2018-06-07 12:13:28	ga_s2am_ard_3-2-1_49JHN_2018-06-07_final
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JHN_2018-06-14_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JHN_2018-06-17_final
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JHN_2018-06-24_final
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49JHN_2018-06-27_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-04_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHN_2018-07-14_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-24_final
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-08-03_final
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49JHN_2018-08-06_final
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JHN_2018-08-13_final
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JHN_2018-08-23_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JHN_2018-09-02_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JHN_2018-09-05_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-09-12_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JHN_2018-09-25_final
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-10-02_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JHN_2018-10-12_final
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49JHN_2018-10-15_final
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-10-22_final
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49JHN_2018-10-25_final
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-11-01_final
2018-11-11 12:04:37	ga_s2am_ard_3-2-1_49JHN_2018-11-11_final
2018-11-14 12:14:25	ga_s2am_ard_3-2-1_49JHN_2018-11-14_final
2018-11-21 12:04:35	ga_s2am_ard_3-2-1_49JHN_2018-11-21_final
2018-11-24 12:14:24	ga_s2am_ard_3-2-1_49JHN_2018-11-24_final
2018-12-01 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-01_final
2018-12-04 12:14:23	ga_s2am_ard_3-2-1_49JHN_2018-12-04_final
2018-12-11 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-11_final
2018-12-14 12:14:22	ga_s2am_ard_3-2-1_49JHN_2018-12-14_final
2018-12-21 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-21_final
2018-12-31 12:04:36	ga_s2am_ard_3-2-1_49JHN_2018-12-31_final
2019-01-03 12:14:25	ga_s2am_ard_3-2-1_49JHN_2019-01-03_final
2019-01-10 12:04:38	ga_s2am_ard_3-2-1_49JHN_2019-01-10_final
2019-01-13 12:14:26	ga_s2am_ard_3-2-1_49JHN_2019-01-13_final
2019-01-20 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-01-20_final
2019-01-23 12:14:27	ga_s2am_ard_3-2-1_49JHN_2019-01-23_final
2019-01-30 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-01-30_final
2019-02-09 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-09_final
2019-02-19 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-19_final
2019-02-22 12:14:27	ga_s2am_ard_3-2-1_49JHN_2019-02-22_final
2019-03-01 12:04:37	ga_s2am_ard_3-2-1_49JHN_2019-03-01_final
2019-03-11 12:04:38	ga_s2am_ard_3-2-1_49JHN_2019-03-11_final
2019-03-14 12:14:27	ga_s2am_ard_3-2-1_49JHN_2019-03-14_final
2019-03-21 12:04:40	ga_s2am_ard_3-2-1_49JHN_2019-03-21_final
2019-03-24 12:14:29	ga_s2am_ard_3-2-1_49JHN_2019-03-24_final
2019-03-31 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-03-31_final
2019-04-03 12:14:31	ga_s2am_ard_3-2-1_49JHN_2019-04-03_final
2019-04-10 12:04:44	ga_s2am_ard_3-2-1_49JHN_2019-04-10_final
2019-04-13 12:14:33	ga_s2am_ard_3-2-1_49JHN_2019-04-13_final
2019-04-20 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-04-20_final
2019-04-23 12:14:34	ga_s2am_ard_3-2-1_49JHN_2019-04-23_final
2019-04-30 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-04-30_final
2019-05-03 12:14:35	ga_s2am_ard_3-2-1_49JHN_2019-05-03_final
2019-05-10 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-05-10_final
2019-05-20 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-05-20_final
2019-05-23 12:14:34	ga_s2am_ard_3-2-1_49JHN_2019-05-23_final
2019-05-30 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-05-30_final
2019-06-09 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-06-09_final
2019-06-12 12:14:34	ga_s2am_ard_3-2-1_49JHN_2019-06-12_final
2019-06-19 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-06-19_final
2019-06-22 12:14:35	ga_s2am_ard_3-2-1_49JHN_2019-06-22_final
2019-06-29 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-06-29_final
2019-07-09 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-07-09_final
2019-07-12 12:14:36	ga_s2am_ard_3-2-1_49JHN_2019-07-12_final
2019-07-19 12:04:48	ga_s2am_ard_3-2-1_49JHN_2019-07-19_final
2019-07-29 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-07-29_final
2019-08-02 11:44:35	ga_s2am_ard_3-2-1_50JRT_2019-08-02_final
2019-08-08 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-08-08_final
2019-08-18 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-08-18_final
2019-08-21 12:14:33	ga_s2am_ard_3-2-1_49JHN_2019-08-21_final
2019-08-28 12:04:44	ga_s2am_ard_3-2-1_49JHN_2019-08-28_final
2019-08-31 12:14:32	ga_s2am_ard_3-2-1_49JHN_2019-08-31_final
2019-09-07 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-09-07_final
2019-09-17 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-09-17_final
2019-09-20 12:14:31	ga_s2am_ard_3-2-1_49JHN_2019-09-20_final
2019-09-27 12:04:43	ga_s2am_ard_3-2-1_49JHN_2019-09-27_final
2019-10-07 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-10-07_final
2019-10-10 12:14:33	ga_s2am_ard_3-2-1_49JHN_2019-10-10_final
2019-10-17 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-10-17_final
2019-10-27 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-10-27_final
2019-11-06 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-11-06_final
2019-11-16 12:04:44	ga_s2am_ard_3-2-1_49JHN_2019-11-16_final
2019-11-19 12:14:32	ga_s2am_ard_3-2-1_49JHN_2019-11-19_final
2019-11-20 11:44:32	ga_s2am_ard_3-2-1_50JRT_2019-11-20_final
2019-11-26 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-11-26_final
2019-11-29 12:14:30	ga_s2am_ard_3-2-1_49JHN_2019-11-29_final
2019-12-06 12:04:40	ga_s2am_ard_3-2-1_49JHN_2019-12-06_final
2019-12-10 11:44:27	ga_s2am_ard_3-2-1_50JRT_2019-12-10_final
2019-12-16 12:04:37	ga_s2am_ard_3-2-1_49JHN_2019-12-16_final
2019-12-19 12:14:25	ga_s2am_ard_3-2-1_49JHN_2019-12-19_final
2019-12-26 12:04:37	ga_s2am_ard_3-2-1_49JHN_2019-12-26_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