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
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_51HVE_2018-05-16_final
2018-05-23 11:25:37	ga_s2am_ard_3-2-1_51HVE_2018-05-23_final
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_51HVE_2018-05-26_final
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51HVE_2018-06-05_final
2018-06-12 11:22:26	ga_s2am_ard_3-2-1_51HVE_2018-06-12_final
2018-07-02 11:23:55	ga_s2am_ard_3-2-1_51HVE_2018-07-02_final
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_51HVE_2018-07-05_final
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HVE_2018-07-15_final
2018-07-22 11:25:32	ga_s2am_ard_3-2-1_51HVE_2018-07-22_final
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51HVE_2018-08-01_final
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51HVE_2018-08-14_final
2018-08-21 11:21:36	ga_s2am_ard_3-2-1_51HVE_2018-08-21_final
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51HVE_2018-08-31_final
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51HVE_2018-09-03_final
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HNK_2018-09-06_final
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51HVE_2018-09-10_final
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_51HVE_2018-09-13_final
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51HVE_2018-09-20_final
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51HVE_2018-09-23_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50HNK_2018-09-26_final
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51HVE_2018-09-30_final
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50HNK_2018-10-06_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HVE_2018-10-10_final
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HVE_2018-10-13_final
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HNK_2018-10-16_final
2018-10-20 11:23:51	ga_s2am_ard_3-2-1_51HVE_2018-10-20_final
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51HVE_2018-10-23_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HNK_2018-10-26_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HNJ_2018-10-26_final
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HNK_2018-10-26_final
2018-10-30 11:24:52	ga_s2am_ard_3-2-1_51HVE_2018-10-30_final
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51HVE_2018-11-02_final
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HNK_2018-11-05_final
2018-11-15 11:46:32	ga_s2am_ard_3-2-1_50HNK_2018-11-15_final
2018-11-25 11:46:30	ga_s2am_ard_3-2-1_50HNK_2018-11-25_final
2018-12-05 11:46:29	ga_s2am_ard_3-2-1_50HNK_2018-12-05_final
2018-12-15 11:46:29	ga_s2am_ard_3-2-1_50HNK_2018-12-15_final
2018-12-25 11:46:30	ga_s2am_ard_3-2-1_50HNK_2018-12-25_final
2019-01-04 11:46:32	ga_s2am_ard_3-2-1_50HNK_2019-01-04_final
2019-01-14 11:46:33	ga_s2am_ard_3-2-1_50HNK_2019-01-14_final
2019-01-24 11:46:34	ga_s2am_ard_3-2-1_50HNK_2019-01-24_final
2019-02-03 11:46:34	ga_s2am_ard_3-2-1_50HNK_2019-02-03_final
2019-02-13 11:46:34	ga_s2am_ard_3-2-1_50HNK_2019-02-13_final
2019-02-23 11:46:33	ga_s2am_ard_3-2-1_50HNK_2019-02-23_final
2019-03-05 11:46:32	ga_s2am_ard_3-2-1_50HNK_2019-03-05_final
2019-03-15 11:46:34	ga_s2am_ard_3-2-1_50HNK_2019-03-15_final
2019-03-25 11:46:36	ga_s2am_ard_3-2-1_50HNK_2019-03-25_final
2019-04-04 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-04-04_final
2019-04-14 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-04-14_final
2019-04-14 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2019-04-14_final
2019-04-14 11:46:45	ga_s2am_ard_3-2-1_50HNK_2019-04-14_final
2019-04-24 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-04-24_final
2019-05-04 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-05-04_final
2019-05-14 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-05-14_final
2019-05-24 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-05-24_final
2019-06-03 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-06-03_final
2019-06-13 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-06-13_final
2019-06-23 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-06-23_final
2019-07-03 11:46:42	ga_s2am_ard_3-2-1_50HNK_2019-07-03_final
2019-07-13 11:46:42	ga_s2am_ard_3-2-1_50HNK_2019-07-13_final
2019-07-23 11:46:42	ga_s2am_ard_3-2-1_50HNK_2019-07-23_final
2019-08-02 11:46:42	ga_s2am_ard_3-2-1_50HNK_2019-08-02_final
2019-08-12 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-08-12_final
2019-08-22 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-08-22_final
2019-09-01 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-09-01_final
2019-09-11 11:46:36	ga_s2am_ard_3-2-1_50HNK_2019-09-11_final
2019-09-21 11:46:37	ga_s2am_ard_3-2-1_50HNK_2019-09-21_final
2019-10-01 11:46:39	ga_s2am_ard_3-2-1_50HNK_2019-10-01_final
2019-10-11 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-10-11_final
2019-10-21 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-10-21_final
2019-10-31 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-10-31_final
2019-11-10 11:46:40	ga_s2am_ard_3-2-1_50HNK_2019-11-10_final
2019-11-20 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-11-20_final
2019-11-30 11:46:36	ga_s2am_ard_3-2-1_50HNK_2019-11-30_final
2019-12-10 11:46:34	ga_s2am_ard_3-2-1_50HNK_2019-12-10_final
2019-12-20 11:46:31	ga_s2am_ard_3-2-1_50HNK_2019-12-20_final
2020-08-26 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-08-26_final
2020-09-05 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-09-05_final
2020-09-15 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-09-15_final
2020-09-25 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-09-25_final
2020-10-05 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-05_final
2020-10-15 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-15_final
2020-10-25 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-25_final
2020-11-04 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-11-04_final
2020-11-14 11:46:41	ga_s2am_ard_3-2-1_50HNK_2020-11-14_final
2020-11-24 11:46:39	ga_s2am_ard_3-2-1_50HNK_2020-11-24_final
2020-12-04 11:46:36	ga_s2am_ard_3-2-1_50HNK_2020-12-04_final
2020-12-14 11:46:34	ga_s2am_ard_3-2-1_50HNK_2020-12-14_final
2020-12-24 11:46:36	ga_s2am_ard_3-2-1_50HNK_2020-12-24_final
2021-01-03 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-03_final
2021-01-13 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-13_final
2021-01-23 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-23_final
2021-02-02 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-02-02_final
2021-02-12 11:46:36	ga_s2am_ard_3-2-1_50HNK_2021-02-12_final
2021-02-22 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-02-22_final
2021-03-04 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-03-04_final
2021-03-14 11:46:37	ga_s2am_ard_3-2-1_50HNK_2021-03-14_final
2021-03-24 11:46:36	ga_s2am_ard_3-2-1_50HNK_2021-03-24_final
2021-04-03 11:46:34	ga_s2am_ard_3-2-1_50HNK_2021-04-03_final
2021-04-13 11:46:32	ga_s2am_ard_3-2-1_50HNK_2021-04-13_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

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