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
2018-06-27 10:27:08	ga_s2am_ard_3-2-1_53JNJ_2018-06-27_final
2018-06-30 10:37:28	ga_s2am_ard_3-2-1_53JNJ_2018-06-30_final
2018-07-07 10:27:09	ga_s2am_ard_3-2-1_53JNJ_2018-07-07_final
2018-07-10 10:37:28	ga_s2am_ard_3-2-1_53JNJ_2018-07-10_final
2018-07-17 10:27:09	ga_s2am_ard_3-2-1_53JNJ_2018-07-17_final
2018-07-27 10:27:09	ga_s2am_ard_3-2-1_53JNJ_2018-07-27_final
2018-08-06 10:27:08	ga_s2am_ard_3-2-1_53JNJ_2018-08-06_final
2018-08-09 10:37:27	ga_s2am_ard_3-2-1_53JNJ_2018-08-09_final
2018-08-16 10:30:15	ga_s2am_ard_3-2-1_53JNJ_2018-08-16_final
2018-08-19 10:37:26	ga_s2am_ard_3-2-1_53JNJ_2018-08-19_final
2018-08-26 10:27:07	ga_s2am_ard_3-2-1_53JNJ_2018-08-26_final
2018-08-29 10:37:26	ga_s2am_ard_3-2-1_53JNJ_2018-08-29_final
2018-09-05 10:27:05	ga_s2am_ard_3-2-1_53JNJ_2018-09-05_final
2018-09-15 10:27:04	ga_s2am_ard_3-2-1_53JNJ_2018-09-15_final
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53JNJ_2018-09-25_final
2018-10-05 10:27:04	ga_s2am_ard_3-2-1_53JNJ_2018-10-05_final
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNJ_2018-10-15_final
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53JNJ_2018-10-25_final
2018-11-04 10:27:04	ga_s2am_ard_3-2-1_53JNJ_2018-11-04_final
2018-11-07 10:45:00	ga_s2am_ard_3-2-1_53JNJ_2018-11-07_final
2018-11-14 10:35:03	ga_s2am_ard_3-2-1_53JNJ_2018-11-14_final
2018-11-17 10:44:58	ga_s2am_ard_3-2-1_53JNJ_2018-11-17_final
2018-11-24 10:35:01	ga_s2am_ard_3-2-1_53JNJ_2018-11-24_final
2018-11-27 10:44:56	ga_s2am_ard_3-2-1_53JNJ_2018-11-27_final
2018-12-04 10:35:00	ga_s2am_ard_3-2-1_53JNJ_2018-12-04_final
2018-12-07 10:44:56	ga_s2am_ard_3-2-1_53JNJ_2018-12-07_final
2018-12-14 10:35:00	ga_s2am_ard_3-2-1_53JNJ_2018-12-14_final
2018-12-17 10:44:56	ga_s2am_ard_3-2-1_53JNJ_2018-12-17_final
2018-12-24 10:35:01	ga_s2am_ard_3-2-1_53JNJ_2018-12-24_final
2018-12-27 10:44:57	ga_s2am_ard_3-2-1_53JNJ_2018-12-27_final
2019-01-03 10:35:03	ga_s2am_ard_3-2-1_53JNJ_2019-01-03_final
2019-01-06 10:44:59	ga_s2am_ard_3-2-1_53JNJ_2019-01-06_final
2019-01-13 10:35:04	ga_s2am_ard_3-2-1_53JNJ_2019-01-13_final
2019-01-23 10:35:05	ga_s2am_ard_3-2-1_53JNJ_2019-01-23_final
2019-01-26 10:45:01	ga_s2am_ard_3-2-1_53JNJ_2019-01-26_final
2019-02-02 10:35:06	ga_s2am_ard_3-2-1_53JNJ_2019-02-02_final
2019-02-05 10:45:01	ga_s2am_ard_3-2-1_53JNJ_2019-02-05_final
2019-02-12 10:35:05	ga_s2am_ard_3-2-1_53JNJ_2019-02-12_final
2019-02-15 10:45:01	ga_s2am_ard_3-2-1_53JNJ_2019-02-15_final
2019-02-22 10:35:05	ga_s2am_ard_3-2-1_53JNJ_2019-02-22_final
2019-02-25 10:45:00	ga_s2am_ard_3-2-1_53JNJ_2019-02-25_final
2019-03-04 10:35:03	ga_s2am_ard_3-2-1_53JNJ_2019-03-04_final
2019-03-07 10:44:59	ga_s2am_ard_3-2-1_53JNJ_2019-03-07_final
2019-03-14 10:35:05	ga_s2am_ard_3-2-1_53JNJ_2019-03-14_final
2019-03-17 10:45:01	ga_s2am_ard_3-2-1_53JNJ_2019-03-17_final
2019-03-24 10:35:07	ga_s2am_ard_3-2-1_53JNJ_2019-03-24_final
2019-03-27 10:45:04	ga_s2am_ard_3-2-1_53JNJ_2019-03-27_final
2019-04-03 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2019-04-03_final
2019-04-06 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2019-04-06_final
2019-04-13 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-04-13_final
2019-04-16 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-04-16_final
2019-04-23 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-04-23_final
2019-04-26 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-04-26_final
2019-05-03 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-05-03_final
2019-05-06 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-05-06_final
2019-05-13 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-05-13_final
2019-05-16 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-05-16_final
2019-05-23 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-05-23_final
2019-05-26 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-05-26_final
2019-06-02 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-06-02_final
2019-06-05 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2019-06-05_final
2019-06-12 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-06-12_final
2019-06-15 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-06-15_final
2019-06-25 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-06-25_final
2019-07-02 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2019-07-02_final
2019-07-05 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-07-05_final
2019-07-12 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2019-07-12_final
2019-07-15 10:45:10	ga_s2am_ard_3-2-1_53JNJ_2019-07-15_final
2019-07-22 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2019-07-22_final
2019-07-25 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-07-25_final
2019-08-01 10:35:13	ga_s2am_ard_3-2-1_53JNJ_2019-08-01_final
2019-08-04 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-08-04_final
2019-08-11 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-08-11_final
2019-08-14 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-08-14_final
2019-08-21 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-08-21_final
2019-08-24 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2019-08-24_final
2019-08-31 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2019-08-31_final
2019-09-03 10:45:04	ga_s2am_ard_3-2-1_53JNJ_2019-09-03_final
2019-09-10 10:35:07	ga_s2am_ard_3-2-1_53JNJ_2019-09-10_final
2019-09-13 10:45:03	ga_s2am_ard_3-2-1_53JNJ_2019-09-13_final
2019-09-20 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2019-09-20_final
2019-09-23 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2019-09-23_final
2019-09-30 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2019-09-30_final
2019-10-03 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2019-10-03_final
2019-10-10 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-10-10_final
2019-10-13 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-10-13_final
2019-10-20 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-10-20_final
2019-10-23 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-10-23_final
2019-10-30 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-10-30_final
2019-11-02 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-11-02_final
2019-11-09 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-11-09_final
2019-11-12 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-11-12_final
2019-11-19 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2019-11-19_final
2019-11-22 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2019-11-22_final
2019-11-29 10:35:08	ga_s2am_ard_3-2-1_53JNJ_2019-11-29_final
2019-12-02 10:45:03	ga_s2am_ard_3-2-1_53JNJ_2019-12-02_final
2019-12-09 10:35:06	ga_s2am_ard_3-2-1_53JNJ_2019-12-09_final
2019-12-12 10:45:00	ga_s2am_ard_3-2-1_53JNJ_2019-12-12_final
2019-12-19 10:35:03	ga_s2am_ard_3-2-1_53JNJ_2019-12-19_final
2019-12-22 10:44:58	ga_s2am_ard_3-2-1_53JNJ_2019-12-22_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