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
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52JEP_2018-10-24_final
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_52JEP_2018-10-31_final
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-11-03_final
2018-11-10 10:55:17	ga_s2am_ard_3-2-1_52JEP_2018-11-10_final
2018-11-13 11:05:11	ga_s2am_ard_3-2-1_52JEP_2018-11-13_final
2018-11-20 10:55:16	ga_s2am_ard_3-2-1_52JEP_2018-11-20_final
2018-11-23 11:05:09	ga_s2am_ard_3-2-1_52JEP_2018-11-23_final
2018-11-30 10:55:14	ga_s2am_ard_3-2-1_52JEP_2018-11-30_final
2018-12-03 11:05:07	ga_s2am_ard_3-2-1_52JEP_2018-12-03_final
2018-12-10 10:55:14	ga_s2am_ard_3-2-1_52JEP_2018-12-10_final
2018-12-13 11:05:08	ga_s2am_ard_3-2-1_52JEP_2018-12-13_final
2018-12-23 11:05:08	ga_s2am_ard_3-2-1_52JEP_2018-12-23_final
2018-12-30 10:55:16	ga_s2am_ard_3-2-1_52JEP_2018-12-30_final
2019-01-02 11:05:10	ga_s2am_ard_3-2-1_52JEP_2019-01-02_final
2019-01-09 10:55:17	ga_s2am_ard_3-2-1_52JEP_2019-01-09_final
2019-01-12 11:05:12	ga_s2am_ard_3-2-1_52JEP_2019-01-12_final
2019-01-19 10:55:18	ga_s2am_ard_3-2-1_52JEP_2019-01-19_final
2019-01-22 11:05:12	ga_s2am_ard_3-2-1_52JEP_2019-01-22_final
2019-01-29 10:55:19	ga_s2am_ard_3-2-1_52JEP_2019-01-29_final
2019-02-01 11:05:13	ga_s2am_ard_3-2-1_52JEP_2019-02-01_final
2019-02-08 10:55:19	ga_s2am_ard_3-2-1_52JEP_2019-02-08_final
2019-02-11 11:05:13	ga_s2am_ard_3-2-1_52JEP_2019-02-11_final
2019-02-18 10:55:18	ga_s2am_ard_3-2-1_52JEP_2019-02-18_final
2019-02-21 11:05:12	ga_s2am_ard_3-2-1_52JEP_2019-02-21_final
2019-02-28 10:55:17	ga_s2am_ard_3-2-1_52JEP_2019-02-28_final
2019-03-03 11:05:11	ga_s2am_ard_3-2-1_52JEP_2019-03-03_final
2019-03-10 10:55:17	ga_s2am_ard_3-2-1_52JEP_2019-03-10_final
2019-03-13 11:05:12	ga_s2am_ard_3-2-1_52JEP_2019-03-13_final
2019-03-20 10:55:20	ga_s2am_ard_3-2-1_52JEP_2019-03-20_final
2019-03-23 11:05:14	ga_s2am_ard_3-2-1_52JEP_2019-03-23_final
2019-03-30 10:55:22	ga_s2am_ard_3-2-1_52JEP_2019-03-30_final
2019-04-02 11:05:16	ga_s2am_ard_3-2-1_52JEP_2019-04-02_final
2019-04-09 10:55:24	ga_s2am_ard_3-2-1_52JEP_2019-04-09_final
2019-04-12 11:05:18	ga_s2am_ard_3-2-1_52JEP_2019-04-12_final
2019-04-19 10:55:25	ga_s2am_ard_3-2-1_52JEP_2019-04-19_final
2019-04-22 11:05:19	ga_s2am_ard_3-2-1_52JEP_2019-04-22_final
2019-04-29 10:55:26	ga_s2am_ard_3-2-1_52JEP_2019-04-29_final
2019-05-02 11:05:20	ga_s2am_ard_3-2-1_52JEP_2019-05-02_final
2019-05-09 10:55:26	ga_s2am_ard_3-2-1_52JEP_2019-05-09_final
2019-05-12 11:05:20	ga_s2am_ard_3-2-1_52JEP_2019-05-12_final
2019-05-19 10:55:26	ga_s2am_ard_3-2-1_52JEP_2019-05-19_final
2019-05-22 11:05:19	ga_s2am_ard_3-2-1_52JEP_2019-05-22_final
2019-05-29 10:55:25	ga_s2am_ard_3-2-1_52JEP_2019-05-29_final
2019-06-01 11:05:18	ga_s2am_ard_3-2-1_52JEP_2019-06-01_final
2019-06-08 10:55:25	ga_s2am_ard_3-2-1_52JEP_2019-06-08_final
2019-06-11 11:05:19	ga_s2am_ard_3-2-1_52JEP_2019-06-11_final
2019-06-18 10:55:26	ga_s2am_ard_3-2-1_52JEP_2019-06-18_final
2020-04-26 11:05:18	ga_s2am_ard_3-2-1_52JEP_2020-04-26_final
2020-05-06 11:05:20	ga_s2am_ard_3-2-1_52JEP_2020-05-06_final
2020-05-13 10:55:27	ga_s2am_ard_3-2-1_52JEP_2020-05-13_final
2020-08-24 11:05:21	ga_s2am_ard_3-2-1_52JEP_2020-08-24_final
2020-09-10 10:55:26	ga_s2am_ard_3-2-1_52JEP_2020-09-10_final
2021-05-12 10:35:08	ga_s2am_ard_3-2-1_53JNJ_2021-05-12_final
2021-05-15 10:45:04	ga_s2am_ard_3-2-1_53JNJ_2021-05-15_final
2021-05-22 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-05-22_final
2021-05-25 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-05-25_final
2021-06-01 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2021-06-01_final
2021-06-04 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-06-04_final
2021-06-11 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-06-11_final
2021-06-14 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-06-14_final
2021-06-21 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-06-21_final
2021-06-24 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-06-24_final
2021-07-01 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2021-07-01_final
2021-07-04 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2021-07-04_final
2021-07-11 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2021-07-11_final
2021-07-14 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2021-07-14_final
2021-07-21 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2021-07-21_final
2021-07-24 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2021-07-24_final
2021-07-31 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2021-07-31_final
2021-08-03 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2021-08-03_final
2021-08-10 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2021-08-10_final
2021-08-13 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2021-08-13_final
2021-08-20 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2021-08-20_final
2021-08-23 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2021-08-23_final
2021-08-30 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2021-08-30_final
2021-09-02 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-09-02_final
2021-09-09 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-09-09_final
2021-09-12 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-09-12_final
2021-09-19 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2021-09-19_final
2021-09-22 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2021-09-22_final
2021-09-29 10:35:13	ga_s2am_ard_3-2-1_53JNJ_2021-09-29_final
2021-10-02 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2021-10-02_final
2021-10-09 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2021-10-09_final
2021-10-12 10:45:10	ga_s2am_ard_3-2-1_53JNJ_2021-10-12_final
2021-10-19 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2021-10-19_final
2021-10-22 10:45:10	ga_s2am_ard_3-2-1_53JNJ_2021-10-22_final
2021-10-29 10:35:13	ga_s2am_ard_3-2-1_53JNJ_2021-10-29_final
2021-11-01 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2021-11-01_final
2021-11-08 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2021-11-08_final
2021-11-11 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2021-11-11_final
2021-11-18 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-11-18_final
2021-11-21 10:45:04	ga_s2am_ard_3-2-1_53JNJ_2021-11-21_final
2021-11-28 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-11-28_final
2021-12-01 10:45:04	ga_s2am_ard_3-2-1_53JNJ_2021-12-01_final
2021-12-08 10:35:08	ga_s2am_ard_3-2-1_53JNJ_2021-12-08_final
2021-12-11 10:45:03	ga_s2am_ard_3-2-1_53JNJ_2021-12-11_final
2021-12-18 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2021-12-18_final
2021-12-21 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2021-12-21_final
2021-12-28 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2021-12-28_final
2021-12-31 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2021-12-31_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