Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-12-14 10:28:40	ga_s2am_ard_3-2-1_53KRB_2016-12-14_final
2016-12-17 10:38:38	ga_s2am_ard_3-2-1_53KRB_2016-12-17_final
2016-12-27 10:38:37	ga_s2am_ard_3-2-1_53KRB_2016-12-27_final
2017-01-16 10:38:05	ga_s2am_ard_3-2-1_53KRB_2017-01-16_final
2017-01-26 10:37:20	ga_s2am_ard_3-2-1_53KRB_2017-01-26_final
2017-02-15 10:37:21	ga_s2am_ard_3-2-1_53KRB_2017-02-15_final
2017-02-22 10:29:15	ga_s2am_ard_3-2-1_53KRB_2017-02-22_final
2017-03-07 10:37:20	ga_s2am_ard_3-2-1_53KRB_2017-03-07_final
2017-03-27 10:37:22	ga_s2am_ard_3-2-1_53KRB_2017-03-27_final
2017-04-13 10:27:07	ga_s2am_ard_3-2-1_53KRB_2017-04-13_final
2017-05-03 10:27:10	ga_s2am_ard_3-2-1_53KRB_2017-05-03_final
2017-05-23 10:27:11	ga_s2am_ard_3-2-1_53KRB_2017-05-23_final
2017-05-26 10:37:30	ga_s2am_ard_3-2-1_53KRB_2017-05-26_final
2017-06-12 10:27:09	ga_s2am_ard_3-2-1_53KRB_2017-06-12_final
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_53KRB_2017-07-02_final
2017-07-05 10:37:26	ga_s2am_ard_3-2-1_53KRB_2017-07-05_final
2017-07-22 10:27:09	ga_s2am_ard_3-2-1_53KRB_2017-07-22_final
2017-07-25 10:37:28	ga_s2am_ard_3-2-1_53KRB_2017-07-25_final
2017-08-14 10:37:29	ga_s2am_ard_3-2-1_53KRB_2017-08-14_final
2017-09-20 10:27:04	ga_s2am_ard_3-2-1_53KRB_2017-09-20_final
2017-11-02 10:37:26	ga_s2am_ard_3-2-1_53KRB_2017-11-02_final
2017-11-19 10:28:06	ga_s2am_ard_3-2-1_53KRB_2017-11-19_final
2017-12-09 10:27:03	ga_s2am_ard_3-2-1_53KRB_2017-12-09_final
2017-12-12 10:37:22	ga_s2am_ard_3-2-1_53KRB_2017-12-12_final
2017-12-29 10:27:01	ga_s2am_ard_3-2-1_53KRB_2017-12-29_final
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_53KRB_2018-01-18_final
2018-01-21 10:37:21	ga_s2am_ard_3-2-1_53KRB_2018-01-21_final
2018-02-07 10:27:04	ga_s2am_ard_3-2-1_53KRB_2018-02-07_final
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KRB_2018-02-20_final
2018-02-27 10:27:04	ga_s2am_ard_3-2-1_53KRB_2018-02-27_final
2018-03-02 10:37:24	ga_s2am_ard_3-2-1_53KRB_2018-03-02_final
2018-03-09 10:27:04	ga_s2am_ard_3-2-1_53KRB_2018-03-09_final
2018-03-12 10:37:23	ga_s2am_ard_3-2-1_53KRB_2018-03-12_final
2018-03-19 10:27:04	ga_s2am_ard_3-2-1_53KRB_2018-03-19_final
2018-03-22 10:37:24	ga_s2am_ard_3-2-1_53KRB_2018-03-22_final
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53KRB_2018-03-29_final
2018-05-01 10:37:29	ga_s2am_ard_3-2-1_53KRB_2018-05-01_final
2018-06-10 10:37:27	ga_s2am_ard_3-2-1_53KRB_2018-06-10_final
2018-09-15 10:27:04	ga_s2am_ard_3-2-1_53KRB_2018-09-15_final
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53KRB_2018-09-18_final
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53KRB_2018-09-25_final
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53KRB_2018-09-28_final
2018-10-18 10:37:24	ga_s2am_ard_3-2-1_53KRB_2018-10-18_final
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53KRB_2018-10-25_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KRB_2018-10-28_final
2018-11-04 10:27:04	ga_s2am_ard_3-2-1_53KRB_2018-11-04_final
2018-11-14 10:31:44	ga_s2am_ard_3-2-1_53KRB_2018-11-14_final
2018-11-17 10:41:39	ga_s2am_ard_3-2-1_53KRB_2018-11-17_final
2018-11-27 10:41:37	ga_s2am_ard_3-2-1_53KRB_2018-11-27_final
2018-12-04 10:31:41	ga_s2am_ard_3-2-1_53KRB_2018-12-04_final
2018-12-07 10:41:37	ga_s2am_ard_3-2-1_53KRB_2018-12-07_final
2018-12-14 10:31:41	ga_s2am_ard_3-2-1_53KRB_2018-12-14_final
2018-12-27 10:41:38	ga_s2am_ard_3-2-1_53KRB_2018-12-27_final
2019-01-03 10:31:44	ga_s2am_ard_3-2-1_53KRB_2019-01-03_final
2019-01-06 10:41:40	ga_s2am_ard_3-2-1_53KRB_2019-01-06_final
2019-01-23 10:31:46	ga_s2am_ard_3-2-1_53KRB_2019-01-23_final
2019-01-26 10:41:42	ga_s2am_ard_3-2-1_53KRB_2019-01-26_final
2019-02-05 10:41:42	ga_s2am_ard_3-2-1_53KRB_2019-02-05_final
2019-02-12 10:31:47	ga_s2am_ard_3-2-1_53KRB_2019-02-12_final
2019-02-15 10:41:42	ga_s2am_ard_3-2-1_53KRB_2019-02-15_final
2019-02-22 10:31:46	ga_s2am_ard_3-2-1_53KRB_2019-02-22_final
2019-03-07 10:41:39	ga_s2am_ard_3-2-1_53KRB_2019-03-07_final
2019-03-14 10:31:46	ga_s2am_ard_3-2-1_53KRB_2019-03-14_final
2019-03-17 10:41:42	ga_s2am_ard_3-2-1_53KRB_2019-03-17_final
2019-03-24 10:31:49	ga_s2am_ard_3-2-1_53KRB_2019-03-24_final
2019-03-27 10:41:44	ga_s2am_ard_3-2-1_53KRB_2019-03-27_final
2019-04-06 10:41:46	ga_s2am_ard_3-2-1_53KRB_2019-04-06_final
2019-04-13 10:31:52	ga_s2am_ard_3-2-1_53KRB_2019-04-13_final
2019-04-26 10:41:49	ga_s2am_ard_3-2-1_53KRB_2019-04-26_final
2019-05-03 10:31:54	ga_s2am_ard_3-2-1_53KRB_2019-05-03_final
2019-05-16 10:41:49	ga_s2am_ard_3-2-1_53KRB_2019-05-16_final
2019-05-23 10:31:53	ga_s2am_ard_3-2-1_53KRB_2019-05-23_final
2019-06-02 10:31:52	ga_s2am_ard_3-2-1_53KRB_2019-06-02_final
2019-06-05 10:41:47	ga_s2am_ard_3-2-1_53KRB_2019-06-05_final
2019-06-12 10:31:53	ga_s2am_ard_3-2-1_53KRB_2019-06-12_final
2019-06-15 10:41:48	ga_s2am_ard_3-2-1_53KRB_2019-06-15_final
2019-07-02 10:31:55	ga_s2am_ard_3-2-1_53KRB_2019-07-02_final
2019-07-05 10:41:50	ga_s2am_ard_3-2-1_53KRB_2019-07-05_final
2019-07-12 10:31:55	ga_s2am_ard_3-2-1_53KRB_2019-07-12_final
2019-08-01 10:31:55	ga_s2am_ard_3-2-1_53KRB_2019-08-01_final
2019-08-11 10:31:54	ga_s2am_ard_3-2-1_53KRB_2019-08-11_final
2019-08-31 10:31:51	ga_s2am_ard_3-2-1_53KRB_2019-08-31_final
2019-10-03 10:41:47	ga_s2am_ard_3-2-1_53KRB_2019-10-03_final
2019-10-23 10:41:48	ga_s2am_ard_3-2-1_53KRB_2019-10-23_final
2019-10-30 10:31:53	ga_s2am_ard_3-2-1_53KRB_2019-10-30_final
2019-11-19 10:31:51	ga_s2am_ard_3-2-1_53KRB_2019-11-19_final
2020-02-17 10:31:44	ga_s2am_ard_3-2-1_53KRB_2020-02-17_final
2020-02-20 10:41:39	ga_s2am_ard_3-2-1_53KRB_2020-02-20_final
2020-04-17 10:31:50	ga_s2am_ard_3-2-1_53KRB_2020-04-17_final
2020-04-30 10:41:48	ga_s2am_ard_3-2-1_53KRB_2020-04-30_final
2020-05-20 10:41:51	ga_s2am_ard_3-2-1_53KRB_2020-05-20_final
2020-05-27 10:31:56	ga_s2am_ard_3-2-1_53KRB_2020-05-27_final
2020-07-06 10:31:54	ga_s2am_ard_3-2-1_53KRB_2020-07-06_final
2020-07-09 10:41:49	ga_s2am_ard_3-2-1_53KRB_2020-07-09_final
2020-08-08 10:41:51	ga_s2am_ard_3-2-1_53KRB_2020-08-08_final
2020-08-18 10:41:51	ga_s2am_ard_3-2-1_53KRB_2020-08-18_final
2020-08-25 10:31:55	ga_s2am_ard_3-2-1_53KRB_2020-08-25_final
2020-09-07 10:41:49	ga_s2am_ard_3-2-1_53KRB_2020-09-07_final
2020-09-14 10:31:54	ga_s2am_ard_3-2-1_53KRB_2020-09-14_final
2020-09-17 10:41:50	ga_s2am_ard_3-2-1_53KRB_2020-09-17_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years