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
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JQP_2017-10-31_final
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50JQP_2017-11-20_final
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50JQP_2017-11-27_final
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_50JQP_2017-12-17_final
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50JQP_2017-12-30_final
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_50JQP_2018-01-06_final
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50JQP_2018-01-19_final
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_50JQP_2018-01-26_final
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JQP_2018-02-08_final
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_50JQP_2018-02-15_final
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50JQP_2018-02-18_final
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_50JQP_2018-02-25_final
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50JQP_2018-02-28_final
2018-03-07 11:30:40	ga_s2am_ard_3-2-1_50JQP_2018-03-07_final
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50JQP_2018-03-10_final
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50JQP_2018-03-17_final
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50JQP_2018-03-20_final
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_50JQP_2018-03-27_final
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50JQP_2018-03-30_final
2018-04-06 11:31:45	ga_s2am_ard_3-2-1_50JQP_2018-04-06_final
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50JQP_2018-04-09_final
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_50JQP_2018-04-16_final
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_50JQP_2018-04-19_final
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50JQP_2018-04-26_final
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_50JQP_2018-04-29_final
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_50JQN_2018-04-29_final
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JQP_2018-04-29_final
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50JQP_2018-05-06_final
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50JQP_2018-05-09_final
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50JQP_2018-05-16_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JQP_2018-05-19_final
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_50JQP_2018-05-26_final
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50JQP_2018-05-29_final
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_50JQP_2018-06-05_final
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JQP_2018-06-08_final
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_50JQP_2018-06-15_final
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQP_2018-06-18_final
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_50JQP_2018-06-25_final
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JQP_2018-06-28_final
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JQP_2018-06-28_final
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50JQP_2018-07-05_final
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JQP_2018-07-08_final
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50JQP_2018-07-15_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JQP_2018-07-18_final
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50JQP_2018-07-25_final
2018-07-28 11:40:21	ga_s2am_ard_3-2-1_50JQP_2018-07-28_final
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_50JQP_2018-08-04_final
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_50JQP_2018-08-07_final
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50JQP_2018-08-14_final
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_50JQP_2018-08-17_final
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_50JQP_2018-08-24_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JQP_2018-08-27_final
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50JQP_2018-09-03_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JQP_2018-09-06_final
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_50JQP_2018-09-13_final
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_50JQP_2018-09-23_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQP_2018-09-26_final
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50JQP_2018-10-03_final
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50JQP_2018-10-06_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50JQP_2018-10-13_final
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50JQP_2018-10-16_final
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_50JQP_2018-10-23_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JQP_2018-10-26_final
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_50JQP_2018-11-02_final
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_50JQP_2018-11-05_final
2018-11-12 11:35:32	ga_s2am_ard_3-2-1_50JQP_2018-11-12_final
2018-11-15 11:45:26	ga_s2am_ard_3-2-1_50JQP_2018-11-15_final
2018-11-22 11:35:30	ga_s2am_ard_3-2-1_50JQP_2018-11-22_final
2018-11-25 11:45:24	ga_s2am_ard_3-2-1_50JQP_2018-11-25_final
2018-12-02 11:35:29	ga_s2am_ard_3-2-1_50JQP_2018-12-02_final
2018-12-05 11:45:24	ga_s2am_ard_3-2-1_50JQP_2018-12-05_final
2018-12-12 11:35:29	ga_s2am_ard_3-2-1_50JQP_2018-12-12_final
2018-12-15 11:45:24	ga_s2am_ard_3-2-1_50JQP_2018-12-15_final
2018-12-22 11:35:29	ga_s2am_ard_3-2-1_50JQP_2018-12-22_final
2018-12-25 11:45:25	ga_s2am_ard_3-2-1_50JQP_2018-12-25_final
2019-01-01 11:35:31	ga_s2am_ard_3-2-1_50JQP_2019-01-01_final
2019-01-04 11:45:27	ga_s2am_ard_3-2-1_50JQP_2019-01-04_final
2019-01-11 11:35:32	ga_s2am_ard_3-2-1_50JQP_2019-01-11_final
2019-01-14 11:45:28	ga_s2am_ard_3-2-1_50JQP_2019-01-14_final
2019-01-21 11:35:33	ga_s2am_ard_3-2-1_50JQP_2019-01-21_final
2019-01-24 11:45:29	ga_s2am_ard_3-2-1_50JQP_2019-01-24_final
2019-01-31 11:35:34	ga_s2am_ard_3-2-1_50JQP_2019-01-31_final
2019-02-03 11:45:29	ga_s2am_ard_3-2-1_50JQP_2019-02-03_final
2019-02-10 11:35:34	ga_s2am_ard_3-2-1_50JQP_2019-02-10_final
2019-02-13 11:45:29	ga_s2am_ard_3-2-1_50JQP_2019-02-13_final
2019-02-20 11:35:33	ga_s2am_ard_3-2-1_50JQP_2019-02-20_final
2019-02-23 11:45:28	ga_s2am_ard_3-2-1_50JQP_2019-02-23_final
2019-03-02 11:35:32	ga_s2am_ard_3-2-1_50JQP_2019-03-02_final
2019-03-05 11:45:27	ga_s2am_ard_3-2-1_50JQP_2019-03-05_final
2019-03-12 11:35:32	ga_s2am_ard_3-2-1_50JQP_2019-03-12_final
2019-03-15 11:45:28	ga_s2am_ard_3-2-1_50JQP_2019-03-15_final
2019-03-22 11:35:35	ga_s2am_ard_3-2-1_50JQP_2019-03-22_final
2019-03-25 11:45:31	ga_s2am_ard_3-2-1_50JQP_2019-03-25_final
2019-04-01 11:35:37	ga_s2am_ard_3-2-1_50JQP_2019-04-01_final
2019-04-04 11:45:33	ga_s2am_ard_3-2-1_50JQP_2019-04-04_final
2019-04-11 11:35:39	ga_s2am_ard_3-2-1_50JQP_2019-04-11_final
2019-04-14 11:45:34	ga_s2am_ard_3-2-1_50JQP_2019-04-14_final
2019-04-21 11:35:40	ga_s2am_ard_3-2-1_50JQP_2019-04-21_final
2019-04-24 11:45:35	ga_s2am_ard_3-2-1_50JQP_2019-04-24_final
2019-05-01 11:35:41	ga_s2am_ard_3-2-1_50JQP_2019-05-01_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