Search ga_s2am_ard_3 whole collection

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
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JVR_2017-07-06_final
2017-07-19 10:22:32	ga_s2am_ard_3-2-1_54JVR_2017-07-19_final
2017-08-08 10:22:57	ga_s2am_ard_3-2-1_54JVR_2017-08-08_final
2017-08-15 10:13:18	ga_s2am_ard_3-2-1_54JVR_2017-08-15_final
2017-09-24 10:13:12	ga_s2am_ard_3-2-1_54JVR_2017-09-24_final
2017-10-14 10:13:15	ga_s2am_ard_3-2-1_54JVR_2017-10-14_final
2017-12-06 10:23:23	ga_s2am_ard_3-2-1_54JVR_2017-12-06_final
2018-01-22 10:11:25	ga_s2am_ard_3-2-1_54JVR_2018-01-22_final
2018-02-14 10:17:02	ga_s2am_ard_3-2-1_54JVR_2018-02-14_final
2018-03-23 10:07:02	ga_s2am_ard_3-2-1_54JVR_2018-03-23_final
2018-04-05 10:17:06	ga_s2am_ard_3-2-1_54JVR_2018-04-05_final
2018-04-22 10:07:06	ga_s2am_ard_3-2-1_54JVR_2018-04-22_final
2018-04-25 10:23:34	ga_s2am_ard_3-2-1_54JVR_2018-04-25_final
2018-05-02 10:10:40	ga_s2am_ard_3-2-1_54JVR_2018-05-02_final
2018-05-05 10:17:08	ga_s2am_ard_3-2-1_54JVR_2018-05-05_final
2018-05-12 10:07:07	ga_s2am_ard_3-2-1_54JVR_2018-05-12_final
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_54JVR_2018-06-04_final
2018-06-11 10:07:04	ga_s2am_ard_3-2-1_54JVR_2018-06-11_final
2018-06-14 10:17:05	ga_s2am_ard_3-2-1_54JVR_2018-06-14_final
2018-06-24 10:17:06	ga_s2am_ard_3-2-1_54JVR_2018-06-24_final
2018-07-04 10:17:07	ga_s2am_ard_3-2-1_54JVR_2018-07-04_final
2018-08-10 10:07:04	ga_s2am_ard_3-2-1_54JVR_2018-08-10_final
2018-09-29 10:07:01	ga_s2am_ard_3-2-1_54JVR_2018-09-29_final
2018-10-02 10:17:02	ga_s2am_ard_3-2-1_54JVR_2018-10-02_final
2018-10-22 10:17:03	ga_s2am_ard_3-2-1_54JVR_2018-10-22_final
2018-11-01 10:17:02	ga_s2am_ard_3-2-1_54JVR_2018-11-01_final
2018-11-11 10:24:22	ga_s2am_ard_3-2-1_54JVR_2018-11-11_final
2018-11-21 10:24:20	ga_s2am_ard_3-2-1_54JVR_2018-11-21_final
2018-12-01 10:24:18	ga_s2am_ard_3-2-1_54JVR_2018-12-01_final
2018-12-11 10:24:18	ga_s2am_ard_3-2-1_54JVR_2018-12-11_final
2018-12-18 10:14:22	ga_s2am_ard_3-2-1_54JVR_2018-12-18_final
2018-12-21 10:24:18	ga_s2am_ard_3-2-1_54JVR_2018-12-21_final
2019-01-07 10:14:26	ga_s2am_ard_3-2-1_54JVR_2019-01-07_final
2019-01-20 10:24:23	ga_s2am_ard_3-2-1_54JVR_2019-01-20_final
2019-02-06 10:14:28	ga_s2am_ard_3-2-1_54JVR_2019-02-06_final
2019-02-09 10:24:24	ga_s2am_ard_3-2-1_54JVR_2019-02-09_final
2019-02-16 10:14:27	ga_s2am_ard_3-2-1_54JVR_2019-02-16_final
2019-02-19 10:24:23	ga_s2am_ard_3-2-1_54JVR_2019-02-19_final
2019-02-26 10:14:27	ga_s2am_ard_3-2-1_54JVR_2019-02-26_final
2019-03-01 10:24:22	ga_s2am_ard_3-2-1_54JVR_2019-03-01_final
2019-03-08 10:14:25	ga_s2am_ard_3-2-1_54JVR_2019-03-08_final
2019-03-11 10:24:22	ga_s2am_ard_3-2-1_54JVR_2019-03-11_final
2019-03-18 10:14:28	ga_s2am_ard_3-2-1_54JVR_2019-03-18_final
2019-03-21 10:24:25	ga_s2am_ard_3-2-1_54JVR_2019-03-21_final
2019-03-28 10:14:30	ga_s2am_ard_3-2-1_54JVR_2019-03-28_final
2019-03-31 10:24:27	ga_s2am_ard_3-2-1_54JVR_2019-03-31_final
2019-04-07 10:14:32	ga_s2am_ard_3-2-1_54JVR_2019-04-07_final
2019-04-10 10:24:28	ga_s2am_ard_3-2-1_54JVR_2019-04-10_final
2019-04-17 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-04-17_final
2019-04-20 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-04-20_final
2019-04-27 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-04-27_final
2019-04-30 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-04-30_final
2019-05-07 10:14:35	ga_s2am_ard_3-2-1_54JVR_2019-05-07_final
2019-05-10 10:24:31	ga_s2am_ard_3-2-1_54JVR_2019-05-10_final
2019-05-17 10:14:35	ga_s2am_ard_3-2-1_54JVR_2019-05-17_final
2019-05-20 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-05-20_final
2019-05-27 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-05-27_final
2019-05-30 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-05-30_final
2019-06-06 10:14:33	ga_s2am_ard_3-2-1_54JVR_2019-06-06_final
2019-06-09 10:24:29	ga_s2am_ard_3-2-1_54JVR_2019-06-09_final
2019-06-16 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-06-16_final
2019-06-19 10:24:31	ga_s2am_ard_3-2-1_54JVR_2019-06-19_final
2019-06-26 10:14:35	ga_s2am_ard_3-2-1_54JVR_2019-06-26_final
2019-06-29 10:24:31	ga_s2am_ard_3-2-1_54JVR_2019-06-29_final
2019-07-06 10:14:36	ga_s2am_ard_3-2-1_54JVR_2019-07-06_final
2019-07-09 10:24:32	ga_s2am_ard_3-2-1_54JVR_2019-07-09_final
2019-07-16 10:14:36	ga_s2am_ard_3-2-1_54JVR_2019-07-16_final
2019-07-19 10:24:32	ga_s2am_ard_3-2-1_54JVR_2019-07-19_final
2019-07-26 10:14:36	ga_s2am_ard_3-2-1_54JVR_2019-07-26_final
2019-07-29 10:24:32	ga_s2am_ard_3-2-1_54JVR_2019-07-29_final
2019-08-05 10:14:35	ga_s2am_ard_3-2-1_54JVR_2019-08-05_final
2019-08-08 10:24:31	ga_s2am_ard_3-2-1_54JVR_2019-08-08_final
2019-08-18 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-08-18_final
2019-08-25 10:14:33	ga_s2am_ard_3-2-1_54JVR_2019-08-25_final
2019-09-07 10:24:26	ga_s2am_ard_3-2-1_54JVR_2019-09-07_final
2019-09-14 10:14:30	ga_s2am_ard_3-2-1_54JVR_2019-09-14_final
2019-09-27 10:24:28	ga_s2am_ard_3-2-1_54JVR_2019-09-27_final
2019-10-04 10:14:33	ga_s2am_ard_3-2-1_54JVR_2019-10-04_final
2019-10-07 10:24:29	ga_s2am_ard_3-2-1_54JVR_2019-10-07_final
2019-10-14 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-10-14_final
2019-10-17 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-10-17_final
2019-10-24 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-10-24_final
2019-10-27 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-10-27_final
2019-11-03 10:14:34	ga_s2am_ard_3-2-1_54JVR_2019-11-03_final
2019-11-06 10:24:30	ga_s2am_ard_3-2-1_54JVR_2019-11-06_final
2019-11-13 10:14:33	ga_s2am_ard_3-2-1_54JVR_2019-11-13_final
2019-11-16 10:24:29	ga_s2am_ard_3-2-1_54JVR_2019-11-16_final
2019-11-23 10:14:32	ga_s2am_ard_3-2-1_54JVR_2019-11-23_final
2019-11-26 10:24:27	ga_s2am_ard_3-2-1_54JVR_2019-11-26_final
2019-12-03 10:14:29	ga_s2am_ard_3-2-1_54JVR_2019-12-03_final
2019-12-23 10:14:25	ga_s2am_ard_3-2-1_54JVR_2019-12-23_final
2020-01-02 10:14:26	ga_s2am_ard_3-2-1_54JVR_2020-01-02_final
2020-02-01 10:14:23	ga_s2am_ard_3-2-1_54JVR_2020-02-01_final
2020-02-11 10:14:24	ga_s2am_ard_3-2-1_54JVR_2020-02-11_final
2020-02-21 10:14:25	ga_s2am_ard_3-2-1_54JVR_2020-02-21_final
2020-03-12 10:14:27	ga_s2am_ard_3-2-1_54JVR_2020-03-12_final
2020-04-01 10:14:27	ga_s2am_ard_3-2-1_54JVR_2020-04-01_final
2020-04-04 10:24:23	ga_s2am_ard_3-2-1_54JVR_2020-04-04_final
2020-04-11 10:14:29	ga_s2am_ard_3-2-1_54JVR_2020-04-11_final
2020-04-24 10:24:28	ga_s2am_ard_3-2-1_54JVR_2020-04-24_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