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
2018-08-11 09:41:08	ga_s2am_ard_3-2-1_55HEA_2018-08-11_final
2018-08-18 09:36:30	ga_s2am_ard_3-2-1_55HEA_2018-08-18_final
2018-08-21 09:46:40	ga_s2am_ard_3-2-1_55HEA_2018-08-21_final
2018-08-28 09:32:38	ga_s2am_ard_3-2-1_55HEA_2018-08-28_final
2018-08-31 09:41:07	ga_s2am_ard_3-2-1_55HEA_2018-08-31_final
2018-09-07 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-09-07_final
2018-09-10 09:41:06	ga_s2am_ard_3-2-1_55HEA_2018-09-10_final
2018-09-17 09:32:36	ga_s2am_ard_3-2-1_55HEA_2018-09-17_final
2018-09-27 09:32:36	ga_s2am_ard_3-2-1_55HEA_2018-09-27_final
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55HEA_2018-09-30_final
2018-10-07 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-07_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEA_2018-10-10_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-17_final
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55HEA_2018-10-20_final
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-27_final
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55HEA_2018-10-30_final
2018-11-06 09:32:36	ga_s2am_ard_3-2-1_55HEA_2018-11-06_final
2018-11-09 09:46:41	ga_s2am_ard_3-2-1_55HEA_2018-11-09_final
2018-11-16 09:36:44	ga_s2am_ard_3-2-1_55HEA_2018-11-16_final
2018-11-19 09:46:39	ga_s2am_ard_3-2-1_55HEA_2018-11-19_final
2018-11-26 09:36:42	ga_s2am_ard_3-2-1_55HEA_2018-11-26_final
2018-11-29 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-11-29_final
2018-12-06 09:36:42	ga_s2am_ard_3-2-1_55HEA_2018-12-06_final
2018-12-09 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-12-09_final
2018-12-16 09:36:42	ga_s2am_ard_3-2-1_55HEA_2018-12-16_final
2018-12-19 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-12-19_final
2018-12-26 09:36:43	ga_s2am_ard_3-2-1_55HEA_2018-12-26_final
2018-12-29 09:46:39	ga_s2am_ard_3-2-1_55HEA_2018-12-29_final
2019-01-05 09:36:45	ga_s2am_ard_3-2-1_55HEA_2019-01-05_final
2019-01-08 09:46:41	ga_s2am_ard_3-2-1_55HEA_2019-01-08_final
2019-01-15 09:36:46	ga_s2am_ard_3-2-1_55HEA_2019-01-15_final
2019-01-18 09:46:42	ga_s2am_ard_3-2-1_55HEA_2019-01-18_final
2019-01-25 09:36:47	ga_s2am_ard_3-2-1_55HEA_2019-01-25_final
2019-01-28 09:46:42	ga_s2am_ard_3-2-1_55HEA_2019-01-28_final
2019-02-04 09:36:47	ga_s2am_ard_3-2-1_55HEA_2019-02-04_final
2019-02-07 09:46:42	ga_s2am_ard_3-2-1_55HEA_2019-02-07_final
2019-02-14 09:36:47	ga_s2am_ard_3-2-1_55HEA_2019-02-14_final
2019-02-17 09:46:42	ga_s2am_ard_3-2-1_55HEA_2019-02-17_final
2019-02-24 09:36:46	ga_s2am_ard_3-2-1_55HEA_2019-02-24_final
2019-02-27 09:46:41	ga_s2am_ard_3-2-1_55HEA_2019-02-27_final
2019-03-06 09:36:45	ga_s2am_ard_3-2-1_55HEA_2019-03-06_final
2019-03-09 09:46:40	ga_s2am_ard_3-2-1_55HEA_2019-03-09_final
2019-03-16 09:36:47	ga_s2am_ard_3-2-1_55HEA_2019-03-16_final
2019-03-19 09:46:43	ga_s2am_ard_3-2-1_55HEA_2019-03-19_final
2019-03-26 09:36:49	ga_s2am_ard_3-2-1_55HEA_2019-03-26_final
2019-03-29 09:46:45	ga_s2am_ard_3-2-1_55HEA_2019-03-29_final
2019-04-05 09:36:51	ga_s2am_ard_3-2-1_55HEA_2019-04-05_final
2019-04-08 09:46:47	ga_s2am_ard_3-2-1_55HEA_2019-04-08_final
2022-01-12 09:46:50	ga_s2am_ard_3-2-1_55HDA_2022-01-12_final
2022-01-15 09:56:46	ga_s2am_ard_3-2-1_55HDA_2022-01-15_final
2022-01-22 09:46:49	ga_s2am_ard_3-2-1_55HDA_2022-01-22_final
2022-01-25 09:56:45	ga_s2am_ard_3-2-1_55HDA_2022-01-25_final
2022-02-01 09:46:48	ga_s2am_ard_3-2-1_55HDA_2022-02-01_final
2022-02-01 09:46:55	ga_s2am_ard_3-2-1_55HDA_2022-02-01_final
2022-02-04 09:56:45	ga_s2am_ard_3-2-1_55HDA_2022-02-04_final
2022-02-04 09:56:52	ga_s2am_ard_3-2-1_55HDA_2022-02-04_final
2022-02-11 09:46:48	ga_s2am_ard_3-2-1_55HDA_2022-02-11_final
2022-02-14 09:56:45	ga_s2am_ard_3-2-1_55HDA_2022-02-14_final
2022-02-21 09:46:51	ga_s2am_ard_3-2-1_55HDA_2022-02-21_final
2022-02-24 09:56:47	ga_s2am_ard_3-2-1_55HDA_2022-02-24_final
2022-02-24 09:56:55	ga_s2am_ard_3-2-1_55HDA_2022-02-24_final
2022-03-03 09:46:53	ga_s2am_ard_3-2-1_55HDA_2022-03-03_final
2022-03-06 09:56:49	ga_s2am_ard_3-2-1_55HDA_2022-03-06_final
2022-03-13 09:46:53	ga_s2am_ard_3-2-1_55HDA_2022-03-13_final
2022-03-16 09:56:49	ga_s2am_ard_3-2-1_55HDA_2022-03-16_final
2022-03-23 09:46:52	ga_s2am_ard_3-2-1_55HDA_2022-03-23_final
2022-03-26 09:56:48	ga_s2am_ard_3-2-1_55HDA_2022-03-26_final
2022-04-02 09:46:51	ga_s2am_ard_3-2-1_55HDA_2022-04-02_final
2022-04-05 09:56:46	ga_s2am_ard_3-2-1_55HDA_2022-04-05_final
2022-04-12 09:46:51	ga_s2am_ard_3-2-1_55HDA_2022-04-12_final
2022-04-15 09:56:48	ga_s2am_ard_3-2-1_55HDA_2022-04-15_final
2022-04-22 09:46:54	ga_s2am_ard_3-2-1_55HDA_2022-04-22_final
2022-04-25 09:56:50	ga_s2am_ard_3-2-1_55HDA_2022-04-25_final
2022-05-02 09:46:54	ga_s2am_ard_3-2-1_55HDA_2022-05-02_final
2022-05-05 09:56:50	ga_s2am_ard_3-2-1_55HDA_2022-05-05_final
2022-05-12 09:46:53	ga_s2am_ard_3-2-1_55HDA_2022-05-12_final
2022-05-15 09:56:49	ga_s2am_ard_3-2-1_55HDA_2022-05-15_final
2022-05-22 09:46:56	ga_s2am_ard_3-2-1_55HDA_2022-05-22_final
2022-05-25 09:56:52	ga_s2am_ard_3-2-1_55HDA_2022-05-25_final
2022-06-01 09:46:57	ga_s2am_ard_3-2-1_55HDA_2022-06-01_final
2022-06-04 09:56:53	ga_s2am_ard_3-2-1_55HDA_2022-06-04_final
2022-06-11 09:46:59	ga_s2am_ard_3-2-1_55HDA_2022-06-11_final
2022-06-14 09:56:55	ga_s2am_ard_3-2-1_55HDA_2022-06-14_final
2022-06-21 09:47:01	ga_s2am_ard_3-2-1_55HDA_2022-06-21_final
2022-06-30 10:17:09	ga_s2am_ard_3-2-1_54HVF_2022-06-30_final
2022-07-01 09:47:02	ga_s2am_ard_3-2-1_55HDA_2022-07-01_final
2022-07-04 09:56:58	ga_s2am_ard_3-2-1_55HDA_2022-07-04_final
2022-07-10 10:17:10	ga_s2am_ard_3-2-1_54HVF_2022-07-10_final
2022-07-11 09:47:02	ga_s2am_ard_3-2-1_55HDA_2022-07-11_final
2022-07-14 09:56:58	ga_s2am_ard_3-2-1_55HDA_2022-07-14_final
2022-07-21 09:47:00	ga_s2am_ard_3-2-1_55HDA_2022-07-21_final
2022-07-24 09:56:56	ga_s2am_ard_3-2-1_55HDA_2022-07-24_final
2022-07-31 09:46:59	ga_s2am_ard_3-2-1_55HDA_2022-07-31_final
2022-08-03 09:56:56	ga_s2am_ard_3-2-1_55HDA_2022-08-03_final
2022-08-06 10:07:12	ga_s2am_ard_3-2-1_54HVF_2022-08-06_final
2022-08-10 09:47:01	ga_s2am_ard_3-2-1_55HDA_2022-08-10_final
2022-08-13 09:56:57	ga_s2am_ard_3-2-1_55HDA_2022-08-13_final
2022-08-16 10:07:13	ga_s2am_ard_3-2-1_54HVF_2022-08-16_final
2022-08-23 09:56:58	ga_s2am_ard_3-2-1_55HDA_2022-08-23_final
2022-08-29 10:17:09	ga_s2am_ard_3-2-1_54HVF_2022-08-29_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