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
2018-02-23 10:53:12	ga_s2am_ard_3-2-1_52JEP_2018-02-23_final
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-02-26_final
2018-03-05 10:47:21	ga_s2am_ard_3-2-1_52JEP_2018-03-05_final
2018-03-05 10:55:14	ga_s2am_ard_3-2-1_52JEP_2018-03-05_final
2018-03-08 11:03:09	ga_s2am_ard_3-2-1_52JEP_2018-03-08_final
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_52JEP_2018-03-15_final
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-03-18_final
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_52JEP_2018-03-25_final
2018-03-28 11:00:18	ga_s2am_ard_3-2-1_52JEP_2018-03-28_final
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_52JEP_2018-04-04_final
2018-04-07 10:57:16	ga_s2am_ard_3-2-1_52JEP_2018-04-07_final
2018-04-14 10:47:26	ga_s2am_ard_3-2-1_52JEP_2018-04-14_final
2018-04-17 11:04:48	ga_s2am_ard_3-2-1_52JEP_2018-04-17_final
2018-04-24 10:47:27	ga_s2am_ard_3-2-1_52JEP_2018-04-24_final
2018-04-27 10:57:18	ga_s2am_ard_3-2-1_52JEP_2018-04-27_final
2018-05-04 10:47:27	ga_s2am_ard_3-2-1_52JEP_2018-05-04_final
2018-05-07 10:57:18	ga_s2am_ard_3-2-1_52JEP_2018-05-07_final
2018-05-14 10:47:27	ga_s2am_ard_3-2-1_52JEP_2018-05-14_final
2018-05-17 11:04:42	ga_s2am_ard_3-2-1_52JEP_2018-05-17_final
2018-05-24 10:47:27	ga_s2am_ard_3-2-1_52JEP_2018-05-24_final
2018-05-27 11:04:30	ga_s2am_ard_3-2-1_52JEP_2018-05-27_final
2018-06-03 10:47:26	ga_s2am_ard_3-2-1_52JEP_2018-06-03_final
2018-06-06 10:57:16	ga_s2am_ard_3-2-1_52JEP_2018-06-06_final
2018-06-13 10:47:24	ga_s2am_ard_3-2-1_52JEP_2018-06-13_final
2018-06-16 10:57:15	ga_s2am_ard_3-2-1_52JEP_2018-06-16_final
2018-06-23 10:47:25	ga_s2am_ard_3-2-1_52JEP_2018-06-23_final
2018-06-26 11:02:55	ga_s2am_ard_3-2-1_52JEP_2018-06-26_final
2018-07-03 10:47:26	ga_s2am_ard_3-2-1_52JEP_2018-07-03_final
2018-07-06 10:57:17	ga_s2am_ard_3-2-1_52JEP_2018-07-06_final
2018-07-13 10:47:26	ga_s2am_ard_3-2-1_52JEP_2018-07-13_final
2018-07-16 10:57:17	ga_s2am_ard_3-2-1_52JEP_2018-07-16_final
2018-07-23 10:47:26	ga_s2am_ard_3-2-1_52JEP_2018-07-23_final
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52JEP_2018-07-26_final
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52JEP_2018-08-02_final
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52JEP_2018-08-05_final
2018-08-22 10:47:24	ga_s2am_ard_3-2-1_52JEP_2018-08-22_final
2018-08-25 10:57:15	ga_s2am_ard_3-2-1_52JEP_2018-08-25_final
2018-09-01 10:53:06	ga_s2am_ard_3-2-1_52JEP_2018-09-01_final
2018-09-04 10:57:14	ga_s2am_ard_3-2-1_52JEP_2018-09-04_final
2018-09-11 10:55:00	ga_s2am_ard_3-2-1_52JEP_2018-09-11_final
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-09-14_final
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52JEP_2018-10-01_final
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-10-04_final
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_52JEP_2018-10-11_final
2018-10-14 10:57:13	ga_s2am_ard_3-2-1_52JEP_2018-10-14_final
2018-10-21 10:47:22	ga_s2am_ard_3-2-1_52JEP_2018-10-21_final
2022-01-03 10:55:24	ga_s2am_ard_3-2-1_52JEP_2022-01-03_final
2022-01-06 11:05:18	ga_s2am_ard_3-2-1_52JEP_2022-01-06_final
2022-01-13 10:55:23	ga_s2am_ard_3-2-1_52JEP_2022-01-13_final
2022-01-16 11:05:17	ga_s2am_ard_3-2-1_52JEP_2022-01-16_final
2022-01-23 10:55:22	ga_s2am_ard_3-2-1_52JEP_2022-01-23_final
2022-01-26 11:05:16	ga_s2am_ard_3-2-1_52JEP_2022-01-26_final
2022-02-02 10:55:22	ga_s2am_ard_3-2-1_52JEP_2022-02-02_final
2022-02-05 11:05:16	ga_s2am_ard_3-2-1_52JEP_2022-02-05_final
2022-02-12 10:55:21	ga_s2am_ard_3-2-1_52JEP_2022-02-12_final
2022-02-15 11:05:16	ga_s2am_ard_3-2-1_52JEP_2022-02-15_final
2022-02-22 10:55:24	ga_s2am_ard_3-2-1_52JEP_2022-02-22_final
2022-02-25 11:05:19	ga_s2am_ard_3-2-1_52JEP_2022-02-25_final
2022-03-04 10:55:26	ga_s2am_ard_3-2-1_52JEP_2022-03-04_final
2022-03-07 11:05:17	ga_s2am_ard_3-2-1_52JEP_2022-03-07_final
2022-03-07 11:05:24	ga_s2am_ard_3-2-1_52JEP_2022-03-07_final
2022-03-14 10:55:26	ga_s2am_ard_3-2-1_52JEP_2022-03-14_final
2022-03-17 11:05:20	ga_s2am_ard_3-2-1_52JEP_2022-03-17_final
2022-03-24 10:55:25	ga_s2am_ard_3-2-1_52JEP_2022-03-24_final
2022-03-27 11:05:19	ga_s2am_ard_3-2-1_52JEP_2022-03-27_final
2022-04-03 10:55:24	ga_s2am_ard_3-2-1_52JEP_2022-04-03_final
2022-04-06 11:05:17	ga_s2am_ard_3-2-1_52JEP_2022-04-06_final
2022-04-13 10:55:25	ga_s2am_ard_3-2-1_52JEP_2022-04-13_final
2022-04-16 11:05:19	ga_s2am_ard_3-2-1_52JEP_2022-04-16_final
2022-04-23 10:55:27	ga_s2am_ard_3-2-1_52JEP_2022-04-23_final
2022-04-26 11:05:21	ga_s2am_ard_3-2-1_52JEP_2022-04-26_final
2022-05-03 10:55:27	ga_s2am_ard_3-2-1_52JEP_2022-05-03_final
2022-05-06 11:05:21	ga_s2am_ard_3-2-1_52JEP_2022-05-06_final
2022-05-13 10:55:26	ga_s2am_ard_3-2-1_52JEP_2022-05-13_final
2022-05-16 11:05:21	ga_s2am_ard_3-2-1_52JEP_2022-05-16_final
2022-05-23 10:55:29	ga_s2am_ard_3-2-1_52JEP_2022-05-23_final
2022-05-26 11:05:23	ga_s2am_ard_3-2-1_52JEP_2022-05-26_final
2022-06-02 10:55:30	ga_s2am_ard_3-2-1_52JEP_2022-06-02_final
2022-06-05 11:05:24	ga_s2am_ard_3-2-1_52JEP_2022-06-05_final
2022-06-12 10:55:32	ga_s2am_ard_3-2-1_52JEP_2022-06-12_final
2022-06-15 11:05:27	ga_s2am_ard_3-2-1_52JEP_2022-06-15_final
2022-06-22 10:55:34	ga_s2am_ard_3-2-1_52JEP_2022-06-22_final
2022-06-25 11:05:28	ga_s2am_ard_3-2-1_52JEP_2022-06-25_final
2022-07-02 10:55:35	ga_s2am_ard_3-2-1_52JEP_2022-07-02_final
2022-07-05 11:05:29	ga_s2am_ard_3-2-1_52JEP_2022-07-05_final
2022-07-12 10:55:35	ga_s2am_ard_3-2-1_52JEP_2022-07-12_final
2022-07-15 11:05:28	ga_s2am_ard_3-2-1_52JEP_2022-07-15_final
2022-07-22 10:55:33	ga_s2am_ard_3-2-1_52JEP_2022-07-22_final
2022-07-25 11:05:26	ga_s2am_ard_3-2-1_52JEP_2022-07-25_final
2022-08-01 10:55:32	ga_s2am_ard_3-2-1_52JEP_2022-08-01_final
2022-08-04 11:05:27	ga_s2am_ard_3-2-1_52JEP_2022-08-04_final
2022-08-11 10:55:34	ga_s2am_ard_3-2-1_52JEP_2022-08-11_final
2022-08-14 11:05:28	ga_s2am_ard_3-2-1_52JEP_2022-08-14_final
2022-08-21 10:55:35	ga_s2am_ard_3-2-1_52JEP_2022-08-21_final
2022-08-31 10:55:34	ga_s2am_ard_3-2-1_52JEP_2022-08-31_final
2022-09-03 11:05:28	ga_s2am_ard_3-2-1_52JEP_2022-09-03_final.stac-item
2022-09-30 10:55:29	ga_s2am_ard_3-2-1_52JEP_2022-09-30_final.stac-item
2022-10-13 11:05:21	ga_s2am_ard_3-2-1_52JEP_2022-10-13_final.stac-item
2022-10-30 10:55:26	ga_s2am_ard_3-2-1_52JEP_2022-10-30_final.stac-item
2022-11-02 11:05:20	ga_s2am_ard_3-2-1_52JEP_2022-11-02_final.stac-item

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