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
2016-12-13 11:02:39	ga_s2am_ard_3-2-1_52JDL_2016-12-13_final
2016-12-23 11:02:53	ga_s2am_ard_3-2-1_52JDL_2016-12-23_final
2017-02-01 10:57:59	ga_s2am_ard_3-2-1_52JDL_2017-02-01_final
2017-02-11 11:01:12	ga_s2am_ard_3-2-1_52JDL_2017-02-11_final
2017-02-21 11:00:21	ga_s2am_ard_3-2-1_52JDL_2017-02-21_final
2017-03-13 11:02:50	ga_s2am_ard_3-2-1_52JDL_2017-03-13_final
2017-04-02 11:02:44	ga_s2am_ard_3-2-1_52JDL_2017-04-02_final
2017-04-22 11:03:00	ga_s2am_ard_3-2-1_52JDL_2017-04-22_final
2017-05-12 11:03:02	ga_s2am_ard_3-2-1_52JDL_2017-05-12_final
2017-06-01 11:03:01	ga_s2am_ard_3-2-1_52JDL_2017-06-01_final
2017-06-21 11:02:58	ga_s2am_ard_3-2-1_52JDL_2017-06-21_final
2017-07-11 11:02:59	ga_s2am_ard_3-2-1_52JDL_2017-07-11_final
2017-07-31 11:03:00	ga_s2am_ard_3-2-1_52JDL_2017-07-31_final
2017-09-09 11:02:57	ga_s2am_ard_3-2-1_52JDL_2017-09-09_final
2017-09-29 11:02:55	ga_s2am_ard_3-2-1_52JDL_2017-09-29_final
2017-10-19 11:02:58	ga_s2am_ard_3-2-1_52JDL_2017-10-19_final
2017-11-08 11:02:57	ga_s2am_ard_3-2-1_52JDL_2017-11-08_final
2017-11-28 11:02:54	ga_s2am_ard_3-2-1_52JDL_2017-11-28_final
2017-12-18 11:02:53	ga_s2am_ard_3-2-1_52JDL_2017-12-18_final
2018-01-07 11:02:51	ga_s2am_ard_3-2-1_52JDL_2018-01-07_final
2018-01-27 11:02:54	ga_s2am_ard_3-2-1_52JDL_2018-01-27_final
2018-02-16 11:04:36	ga_s2am_ard_3-2-1_52JDL_2018-02-16_final
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52JDL_2018-02-26_final
2018-03-08 11:03:09	ga_s2am_ard_3-2-1_52JDL_2018-03-08_final
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JDL_2018-03-18_final
2018-03-28 11:00:18	ga_s2am_ard_3-2-1_52JDL_2018-03-28_final
2018-04-07 10:57:16	ga_s2am_ard_3-2-1_52JDL_2018-04-07_final
2018-04-17 11:04:48	ga_s2am_ard_3-2-1_52JDL_2018-04-17_final
2018-04-27 10:57:18	ga_s2am_ard_3-2-1_52JDL_2018-04-27_final
2018-05-07 10:57:18	ga_s2am_ard_3-2-1_52JDL_2018-05-07_final
2018-05-17 11:04:42	ga_s2am_ard_3-2-1_52JDL_2018-05-17_final
2018-05-27 11:04:30	ga_s2am_ard_3-2-1_52JDL_2018-05-27_final
2018-06-06 10:57:16	ga_s2am_ard_3-2-1_52JDL_2018-06-06_final
2018-06-16 10:57:15	ga_s2am_ard_3-2-1_52JDL_2018-06-16_final
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JDL_2018-06-26_final
2018-07-06 10:57:17	ga_s2am_ard_3-2-1_52JDL_2018-07-06_final
2018-07-16 10:57:17	ga_s2am_ard_3-2-1_52JDL_2018-07-16_final
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52JDL_2018-07-26_final
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52JDL_2018-08-05_final
2018-08-15 11:05:44	ga_s2am_ard_3-2-1_52JDL_2018-08-15_final
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_52JDL_2018-08-25_final
2018-09-04 10:57:14	ga_s2am_ard_3-2-1_52JDL_2018-09-04_final
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JDL_2018-09-14_final
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JDL_2018-10-04_final
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52JDL_2018-10-14_final
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52JDL_2018-10-24_final
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_52JDL_2018-11-03_final
2018-11-13 11:05:58	ga_s2am_ard_3-2-1_52JDL_2018-11-13_final
2018-11-23 11:05:56	ga_s2am_ard_3-2-1_52JDL_2018-11-23_final
2018-12-03 11:05:55	ga_s2am_ard_3-2-1_52JDL_2018-12-03_final
2018-12-13 11:05:55	ga_s2am_ard_3-2-1_52JDL_2018-12-13_final
2018-12-23 11:05:55	ga_s2am_ard_3-2-1_52JDL_2018-12-23_final
2019-01-02 11:05:57	ga_s2am_ard_3-2-1_52JDL_2019-01-02_final
2019-01-12 11:05:59	ga_s2am_ard_3-2-1_52JDL_2019-01-12_final
2019-01-22 11:06:00	ga_s2am_ard_3-2-1_52JDL_2019-01-22_final
2019-02-01 11:06:00	ga_s2am_ard_3-2-1_52JDL_2019-02-01_final
2019-02-11 11:06:00	ga_s2am_ard_3-2-1_52JDL_2019-02-11_final
2019-02-21 11:05:59	ga_s2am_ard_3-2-1_52JDL_2019-02-21_final
2019-03-03 11:05:58	ga_s2am_ard_3-2-1_52JDL_2019-03-03_final
2019-03-13 11:05:59	ga_s2am_ard_3-2-1_52JDL_2019-03-13_final
2019-03-23 11:06:01	ga_s2am_ard_3-2-1_52JDL_2019-03-23_final
2019-04-02 11:06:09	ga_s2am_ard_3-2-1_52JDL_2019-04-02_final
2019-04-12 11:06:05	ga_s2am_ard_3-2-1_52JDL_2019-04-12_final
2019-04-22 11:06:06	ga_s2am_ard_3-2-1_52JDL_2019-04-22_final
2019-05-02 11:06:07	ga_s2am_ard_3-2-1_52JDL_2019-05-02_final
2019-05-12 11:06:07	ga_s2am_ard_3-2-1_52JDL_2019-05-12_final
2019-05-12 11:06:15	ga_s2am_ard_3-2-1_52JDL_2019-05-12_final
2019-05-22 11:06:07	ga_s2am_ard_3-2-1_52JDL_2019-05-22_final
2019-06-01 11:06:11	ga_s2am_ard_3-2-1_52JDL_2019-06-01_final
2019-06-11 11:06:06	ga_s2am_ard_3-2-1_52JDL_2019-06-11_final
2019-06-21 11:06:07	ga_s2am_ard_3-2-1_52JDL_2019-06-21_final
2019-07-01 11:06:08	ga_s2am_ard_3-2-1_52JDL_2019-07-01_final
2019-07-11 11:06:08	ga_s2am_ard_3-2-1_52JDL_2019-07-11_final
2019-07-21 11:06:08	ga_s2am_ard_3-2-1_52JDL_2019-07-21_final
2019-07-31 11:06:08	ga_s2am_ard_3-2-1_52JDL_2019-07-31_final
2019-08-10 11:06:07	ga_s2am_ard_3-2-1_52JDL_2019-08-10_final
2019-08-20 11:06:06	ga_s2am_ard_3-2-1_52JDL_2019-08-20_final
2019-08-30 11:06:04	ga_s2am_ard_3-2-1_52JDL_2019-08-30_final
2019-09-09 11:06:02	ga_s2am_ard_3-2-1_52JDL_2019-09-09_final
2019-09-19 11:05:59	ga_s2am_ard_3-2-1_52JEL_2019-09-19_final
2019-09-19 11:06:03	ga_s2am_ard_3-2-1_52JDL_2019-09-19_final
2019-09-29 11:06:04	ga_s2am_ard_3-2-1_52JDL_2019-09-29_final
2019-10-09 11:06:06	ga_s2am_ard_3-2-1_52JDL_2019-10-09_final
2019-10-19 11:06:07	ga_s2am_ard_3-2-1_52JDL_2019-10-19_final
2019-10-29 11:06:06	ga_s2am_ard_3-2-1_52JDL_2019-10-29_final
2019-11-08 11:06:02	ga_s2am_ard_3-2-1_52JEL_2019-11-08_final
2019-11-08 11:06:06	ga_s2am_ard_3-2-1_52JDL_2019-11-08_final
2019-11-18 11:06:05	ga_s2am_ard_3-2-1_52JDL_2019-11-18_final
2019-11-28 11:05:59	ga_s2am_ard_3-2-1_52JEL_2019-11-28_final
2019-11-28 11:06:03	ga_s2am_ard_3-2-1_52JDL_2019-11-28_final
2019-12-08 11:05:56	ga_s2am_ard_3-2-1_52JEL_2019-12-08_final
2019-12-08 11:06:00	ga_s2am_ard_3-2-1_52JDL_2019-12-08_final
2019-12-18 11:05:53	ga_s2am_ard_3-2-1_52JEL_2019-12-18_final
2019-12-18 11:05:57	ga_s2am_ard_3-2-1_52JDL_2019-12-18_final
2019-12-28 11:05:58	ga_s2am_ard_3-2-1_52JDL_2019-12-28_final
2020-01-07 11:05:58	ga_s2am_ard_3-2-1_52JDL_2020-01-07_final
2020-01-27 11:05:52	ga_s2am_ard_3-2-1_52JEL_2020-01-27_final
2020-02-16 11:05:53	ga_s2am_ard_3-2-1_52JEL_2020-02-16_final
2020-02-26 11:05:54	ga_s2am_ard_3-2-1_52JEL_2020-02-26_final
2020-03-07 11:05:55	ga_s2am_ard_3-2-1_52JEL_2020-03-07_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