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
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49KHP_2017-10-20_final
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49KHP_2018-01-08_final
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49KHP_2018-01-25_final
2019-04-07 10:13:34	ga_s2am_ard_3-2-1_54KZU_2019-04-07_final
2019-04-14 10:03:40	ga_s2am_ard_3-2-1_54KZU_2019-04-14_final
2019-04-17 10:13:36	ga_s2am_ard_3-2-1_54KZU_2019-04-17_final
2019-04-24 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-04-24_final
2019-04-27 10:13:37	ga_s2am_ard_3-2-1_54KZU_2019-04-27_final
2019-05-04 10:03:42	ga_s2am_ard_3-2-1_54KZU_2019-05-04_final
2019-05-07 10:13:37	ga_s2am_ard_3-2-1_54KZU_2019-05-07_final
2019-05-14 10:03:42	ga_s2am_ard_3-2-1_54KZU_2019-05-14_final
2019-05-17 10:13:37	ga_s2am_ard_3-2-1_54KZU_2019-05-17_final
2019-05-24 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-05-24_final
2019-05-27 10:13:36	ga_s2am_ard_3-2-1_54KZU_2019-05-27_final
2019-06-03 10:03:40	ga_s2am_ard_3-2-1_54KZU_2019-06-03_final
2019-06-06 10:13:35	ga_s2am_ard_3-2-1_54KZU_2019-06-06_final
2019-06-13 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-06-13_final
2019-06-16 10:13:37	ga_s2am_ard_3-2-1_54KZU_2019-06-16_final
2019-06-26 10:13:38	ga_s2am_ard_3-2-1_54KZU_2019-06-26_final
2019-07-03 10:03:43	ga_s2am_ard_3-2-1_54KZU_2019-07-03_final
2019-07-06 10:13:38	ga_s2am_ard_3-2-1_54KZU_2019-07-06_final
2019-07-13 10:03:43	ga_s2am_ard_3-2-1_54KZU_2019-07-13_final
2019-07-16 10:13:38	ga_s2am_ard_3-2-1_54KZU_2019-07-16_final
2019-07-23 10:03:43	ga_s2am_ard_3-2-1_54KZU_2019-07-23_final
2019-07-26 10:13:38	ga_s2am_ard_3-2-1_54KZU_2019-07-26_final
2019-08-02 10:03:43	ga_s2am_ard_3-2-1_54KZU_2019-08-02_final
2019-08-05 10:13:38	ga_s2am_ard_3-2-1_54KZU_2019-08-05_final
2019-08-12 10:03:42	ga_s2am_ard_3-2-1_54KZU_2019-08-12_final
2019-08-15 10:13:37	ga_s2am_ard_3-2-1_54KZU_2019-08-15_final
2019-08-22 10:03:40	ga_s2am_ard_3-2-1_54KZU_2019-08-22_final
2019-08-25 10:13:35	ga_s2am_ard_3-2-1_54KZU_2019-08-25_final
2019-09-01 10:03:39	ga_s2am_ard_3-2-1_54KZU_2019-09-01_final
2019-09-04 10:13:33	ga_s2am_ard_3-2-1_54KZU_2019-09-04_final
2019-09-11 10:03:36	ga_s2am_ard_3-2-1_54KZU_2019-09-11_final
2019-09-14 10:13:32	ga_s2am_ard_3-2-1_54KZU_2019-09-14_final
2019-09-21 10:03:38	ga_s2am_ard_3-2-1_54KZU_2019-09-21_final
2019-10-01 10:03:40	ga_s2am_ard_3-2-1_54KZU_2019-10-01_final
2019-10-04 10:13:35	ga_s2am_ard_3-2-1_54KZU_2019-10-04_final
2019-10-11 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-10-11_final
2019-10-14 10:13:36	ga_s2am_ard_3-2-1_54KZU_2019-10-14_final
2019-10-21 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-10-21_final
2019-10-24 10:13:36	ga_s2am_ard_3-2-1_54KZU_2019-10-24_final
2019-10-31 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-10-31_final
2019-11-03 10:13:36	ga_s2am_ard_3-2-1_54KZU_2019-11-03_final
2019-11-10 10:03:41	ga_s2am_ard_3-2-1_54KZU_2019-11-10_final
2019-11-13 10:13:35	ga_s2am_ard_3-2-1_54KZU_2019-11-13_final
2019-11-20 10:03:39	ga_s2am_ard_3-2-1_54KZU_2019-11-20_final
2019-11-23 10:13:34	ga_s2am_ard_3-2-1_54KZU_2019-11-23_final
2019-11-30 10:03:37	ga_s2am_ard_3-2-1_54KZU_2019-11-30_final
2019-12-03 10:13:32	ga_s2am_ard_3-2-1_54KZU_2019-12-03_final
2019-12-10 10:03:35	ga_s2am_ard_3-2-1_54KZU_2019-12-10_final
2019-12-13 10:13:29	ga_s2am_ard_3-2-1_54KZU_2019-12-13_final
2019-12-20 10:03:32	ga_s2am_ard_3-2-1_54KZU_2019-12-20_final
2019-12-23 10:13:28	ga_s2am_ard_3-2-1_54KZU_2019-12-23_final
2019-12-30 10:03:33	ga_s2am_ard_3-2-1_54KZU_2019-12-30_final
2020-01-02 10:13:28	ga_s2am_ard_3-2-1_54KZU_2020-01-02_final
2020-01-09 10:03:33	ga_s2am_ard_3-2-1_54KZU_2020-01-09_final
2020-01-12 10:13:28	ga_s2am_ard_3-2-1_54KZU_2020-01-12_final
2020-01-19 10:03:32	ga_s2am_ard_3-2-1_54KZU_2020-01-19_final
2020-01-22 10:13:27	ga_s2am_ard_3-2-1_54KZU_2020-01-22_final
2020-01-29 10:03:31	ga_s2am_ard_3-2-1_54KZU_2020-01-29_final
2020-02-01 10:13:26	ga_s2am_ard_3-2-1_54KZU_2020-02-01_final
2020-02-08 10:03:30	ga_s2am_ard_3-2-1_54KZU_2020-02-08_final
2020-02-11 10:13:26	ga_s2am_ard_3-2-1_54KZU_2020-02-11_final
2020-02-18 10:03:32	ga_s2am_ard_3-2-1_54KZU_2020-02-18_final
2020-02-21 10:13:28	ga_s2am_ard_3-2-1_54KZU_2020-02-21_final
2020-02-28 10:03:33	ga_s2am_ard_3-2-1_54KZU_2020-02-28_final
2020-03-02 10:13:29	ga_s2am_ard_3-2-1_54KZU_2020-03-02_final
2020-03-09 10:03:34	ga_s2am_ard_3-2-1_54KZU_2020-03-09_final
2020-03-12 10:13:29	ga_s2am_ard_3-2-1_54KZU_2020-03-12_final
2020-03-19 10:03:34	ga_s2am_ard_3-2-1_54KZU_2020-03-19_final
2020-03-22 10:13:30	ga_s2am_ard_3-2-1_54KZU_2020-03-22_final
2020-03-29 10:03:34	ga_s2am_ard_3-2-1_54KZU_2020-03-29_final
2020-04-01 10:13:29	ga_s2am_ard_3-2-1_54KZU_2020-04-01_final
2020-04-08 10:03:36	ga_s2am_ard_3-2-1_54KZU_2020-04-08_final
2020-04-11 10:13:32	ga_s2am_ard_3-2-1_54KZU_2020-04-11_final
2020-04-18 10:03:38	ga_s2am_ard_3-2-1_54KZU_2020-04-18_final
2020-04-21 10:13:34	ga_s2am_ard_3-2-1_54KZU_2020-04-21_final
2020-04-28 10:03:41	ga_s2am_ard_3-2-1_54KZU_2020-04-28_final
2020-05-01 10:13:36	ga_s2am_ard_3-2-1_54KZU_2020-05-01_final
2020-05-08 10:03:42	ga_s2am_ard_3-2-1_54KZU_2020-05-08_final
2020-05-11 10:13:38	ga_s2am_ard_3-2-1_54KZU_2020-05-11_final
2020-05-18 10:03:43	ga_s2am_ard_3-2-1_54KZU_2020-05-18_final
2020-05-21 10:13:39	ga_s2am_ard_3-2-1_54KZU_2020-05-21_final
2020-05-28 10:03:44	ga_s2am_ard_3-2-1_54KZU_2020-05-28_final
2020-05-31 10:13:39	ga_s2am_ard_3-2-1_54KZU_2020-05-31_final
2020-06-07 10:03:44	ga_s2am_ard_3-2-1_54KZU_2020-06-07_final
2020-06-10 10:13:39	ga_s2am_ard_3-2-1_54KZU_2020-06-10_final
2020-06-17 10:03:44	ga_s2am_ard_3-2-1_54KZU_2020-06-17_final
2020-06-20 10:13:39	ga_s2am_ard_3-2-1_54KZU_2020-06-20_final
2020-06-27 10:03:44	ga_s2am_ard_3-2-1_54KZU_2020-06-27_final
2020-06-30 10:13:38	ga_s2am_ard_3-2-1_54KZU_2020-06-30_final
2020-07-07 10:03:43	ga_s2am_ard_3-2-1_54KZU_2020-07-07_final
2020-07-10 10:13:37	ga_s2am_ard_3-2-1_54KZU_2020-07-10_final
2020-07-17 10:03:43	ga_s2am_ard_3-2-1_54KZU_2020-07-17_final
2020-07-20 10:13:38	ga_s2am_ard_3-2-1_54KZU_2020-07-20_final
2020-07-27 10:03:44	ga_s2am_ard_3-2-1_54KZU_2020-07-27_final
2020-07-30 10:13:39	ga_s2am_ard_3-2-1_54KZU_2020-07-30_final
2020-08-06 10:03:44	ga_s2am_ard_3-2-1_54KZU_2020-08-06_final
2020-08-09 10:13:39	ga_s2am_ard_3-2-1_54KZU_2020-08-09_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