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
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50KQA_2015-10-22_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50KQA_2016-03-20_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50KQA_2016-07-08_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50KQA_2016-12-15_final
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50KQA_2016-12-25_final
2017-01-14 11:34:53	ga_s2am_ard_3-2-1_50KQA_2017-01-14_final
2017-01-24 11:35:42	ga_s2am_ard_3-2-1_50KQA_2017-01-24_final
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50KQA_2017-02-03_final
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_50KQA_2017-02-13_final
2017-03-05 11:37:45	ga_s2am_ard_3-2-1_50KQA_2017-03-05_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_50KQA_2017-03-25_final
2017-04-14 11:38:34	ga_s2am_ard_3-2-1_50KQA_2017-04-14_final.stac-item
2017-05-04 11:38:37	ga_s2am_ard_3-2-1_50KQA_2017-05-04_final
2017-05-24 11:38:34	ga_s2am_ard_3-2-1_50KQA_2017-05-24_final
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50KQA_2017-06-13_final
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50KQA_2017-07-03_final
2017-07-23 11:38:36	ga_s2am_ard_3-2-1_50KQA_2017-07-23_final
2017-08-12 11:40:50	ga_s2am_ard_3-2-1_50KQA_2017-08-12_final
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_50KQA_2017-09-01_final
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_50KQA_2017-09-21_final
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_50KQA_2017-10-11_final
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50KQA_2017-10-31_final
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50KQA_2017-11-20_final
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50KQA_2017-12-10_final
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50KQA_2017-12-30_final
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50KQA_2018-01-19_final
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50KQA_2018-02-08_final
2018-02-18 11:42:05	ga_s2am_ard_3-2-1_50KQA_2018-02-18_final
2018-02-28 11:38:46	ga_s2am_ard_3-2-1_50KQA_2018-02-28_final
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50KQA_2018-03-10_final
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_50KQA_2018-03-20_final
2018-03-30 11:39:33	ga_s2am_ard_3-2-1_50KQA_2018-03-30_final
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50KQA_2018-04-09_final
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_50KQA_2018-04-19_final
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_50KQA_2018-04-29_final
2018-05-09 11:34:47	ga_s2am_ard_3-2-1_50KQA_2018-05-09_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50KQA_2018-05-19_final
2018-05-29 11:39:24	ga_s2am_ard_3-2-1_50KQA_2018-05-29_final
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50KQA_2018-06-08_final
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_50KQA_2018-06-18_final
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50KQA_2018-06-28_final
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50KQA_2018-07-08_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50KQA_2018-07-18_final
2018-07-28 11:40:21	ga_s2am_ard_3-2-1_50KQA_2018-07-28_final
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_50KQA_2018-08-07_final
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_50KQA_2018-08-17_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50KQA_2018-08-27_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50KQA_2018-09-06_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50KQA_2018-09-26_final
2019-06-23 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-06-23_final
2019-07-03 11:43:56	ga_s2am_ard_3-2-1_50KQA_2019-07-03_final
2019-07-13 11:43:56	ga_s2am_ard_3-2-1_50KQA_2019-07-13_final
2019-07-23 11:43:56	ga_s2am_ard_3-2-1_50KQA_2019-07-23_final
2019-08-02 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-08-02_final
2019-08-12 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-08-12_final
2019-08-22 11:43:53	ga_s2am_ard_3-2-1_50KQA_2019-08-22_final
2019-09-01 11:43:51	ga_s2am_ard_3-2-1_50KQA_2019-09-01_final
2019-09-11 11:43:49	ga_s2am_ard_3-2-1_50KQA_2019-09-11_final
2019-09-21 11:43:51	ga_s2am_ard_3-2-1_50KQA_2019-09-21_final
2019-10-01 11:43:53	ga_s2am_ard_3-2-1_50KQA_2019-10-01_final
2019-10-11 11:43:54	ga_s2am_ard_3-2-1_50KQA_2019-10-11_final
2019-10-21 11:43:54	ga_s2am_ard_3-2-1_50KQA_2019-10-21_final
2019-10-31 11:43:54	ga_s2am_ard_3-2-1_50KQA_2019-10-31_final
2019-11-10 11:43:53	ga_s2am_ard_3-2-1_50KQA_2019-11-10_final
2019-11-20 11:43:52	ga_s2am_ard_3-2-1_50KQA_2019-11-20_final
2019-11-30 11:43:50	ga_s2am_ard_3-2-1_50KQA_2019-11-30_final
2019-12-10 11:43:47	ga_s2am_ard_3-2-1_50KQA_2019-12-10_final
2019-12-20 11:43:45	ga_s2am_ard_3-2-1_50KQA_2019-12-20_final
2019-12-30 11:43:46	ga_s2am_ard_3-2-1_50KQA_2019-12-30_final
2020-01-09 11:43:45	ga_s2am_ard_3-2-1_50KQA_2020-01-09_final
2020-01-19 11:43:45	ga_s2am_ard_3-2-1_50KQA_2020-01-19_final
2020-01-29 11:43:44	ga_s2am_ard_3-2-1_50KQA_2020-01-29_final
2020-02-08 11:43:43	ga_s2am_ard_3-2-1_50KQA_2020-02-08_final
2020-02-18 11:43:45	ga_s2am_ard_3-2-1_50KQA_2020-02-18_final
2020-02-28 11:43:46	ga_s2am_ard_3-2-1_50KQA_2020-02-28_final
2020-03-09 11:43:47	ga_s2am_ard_3-2-1_50KQA_2020-03-09_final
2020-03-19 11:43:47	ga_s2am_ard_3-2-1_50KQA_2020-03-19_final
2020-03-29 11:43:47	ga_s2am_ard_3-2-1_50KQA_2020-03-29_final
2020-04-08 11:43:48	ga_s2am_ard_3-2-1_50KQA_2020-04-08_final
2020-04-18 11:43:51	ga_s2am_ard_3-2-1_50KQA_2020-04-18_final
2020-04-28 11:43:53	ga_s2am_ard_3-2-1_50KQA_2020-04-28_final
2020-05-08 11:43:55	ga_s2am_ard_3-2-1_50KQA_2020-05-08_final
2020-05-18 11:43:56	ga_s2am_ard_3-2-1_50KQA_2020-05-18_final
2020-05-28 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-05-28_final
2020-06-07 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-06-07_final
2020-06-17 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-06-17_final
2020-06-27 11:43:56	ga_s2am_ard_3-2-1_50KQA_2020-06-27_final
2020-07-07 11:43:55	ga_s2am_ard_3-2-1_50KQA_2020-07-07_final
2020-07-17 11:43:56	ga_s2am_ard_3-2-1_50KQA_2020-07-17_final
2020-07-27 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-07-27_final
2020-08-06 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-08-06_final
2020-08-16 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-08-16_final
2020-08-26 11:43:56	ga_s2am_ard_3-2-1_50KQA_2020-08-26_final
2020-09-05 11:43:55	ga_s2am_ard_3-2-1_50KQA_2020-09-05_final
2020-09-15 11:43:55	ga_s2am_ard_3-2-1_50KQA_2020-09-15_final
2020-10-25 11:43:56	ga_s2am_ard_3-2-1_50KQA_2020-10-25_final
2020-11-04 11:43:56	ga_s2am_ard_3-2-1_50KQA_2020-11-04_final
2020-12-04 11:43:50	ga_s2am_ard_3-2-1_50KQA_2020-12-04_final
2021-01-13 11:43:52	ga_s2am_ard_3-2-1_50KQA_2021-01-13_final
2021-02-12 11:43:50	ga_s2am_ard_3-2-1_50KQA_2021-02-12_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