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
2017-12-11 11:11:56	ga_s2am_ard_3-2-1_51KZQ_2017-12-11_final
2017-12-21 11:12:09	ga_s2am_ard_3-2-1_51KZQ_2017-12-21_final
2017-12-31 11:11:55	ga_s2am_ard_3-2-1_51KZQ_2017-12-31_final
2018-01-10 11:12:24	ga_s2am_ard_3-2-1_51KZQ_2018-01-10_final
2018-01-20 11:11:55	ga_s2am_ard_3-2-1_51KZQ_2018-01-20_final
2018-01-30 11:12:10	ga_s2am_ard_3-2-1_51KZQ_2018-01-30_final
2018-02-09 11:11:58	ga_s2am_ard_3-2-1_51KZQ_2018-02-09_final
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_51KZQ_2018-02-19_final
2018-02-28 11:38:46	ga_s2am_ard_3-2-1_50KRV_2018-02-28_final
2018-03-01 11:11:47	ga_s2am_ard_3-2-1_51KZQ_2018-03-01_final
2018-03-11 11:12:00	ga_s2am_ard_3-2-1_51KZQ_2018-03-11_final
2018-03-21 11:11:51	ga_s2am_ard_3-2-1_51KZQ_2018-03-21_final
2018-03-31 11:07:12	ga_s2am_ard_3-2-1_51KZQ_2018-03-31_final
2018-04-10 11:09:59	ga_s2am_ard_3-2-1_51KZQ_2018-04-10_final
2018-04-20 11:10:14	ga_s2am_ard_3-2-1_51KZQ_2018-04-20_final
2018-05-10 11:12:54	ga_s2am_ard_3-2-1_51KZQ_2018-05-10_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50KRV_2018-05-19_final
2018-05-20 11:11:46	ga_s2am_ard_3-2-1_51KZQ_2018-05-20_final
2018-05-30 11:13:18	ga_s2am_ard_3-2-1_51KZQ_2018-05-30_final
2018-06-09 11:13:13	ga_s2am_ard_3-2-1_51KZQ_2018-06-09_final
2018-06-19 11:09:58	ga_s2am_ard_3-2-1_51KZQ_2018-06-19_final
2018-06-29 11:07:13	ga_s2am_ard_3-2-1_51KZQ_2018-06-29_final
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50KRV_2018-07-08_final
2018-07-09 11:13:18	ga_s2am_ard_3-2-1_51KZQ_2018-07-09_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50KRV_2018-07-18_final
2018-07-19 11:09:45	ga_s2am_ard_3-2-1_51KZQ_2018-07-19_final
2018-07-29 11:13:14	ga_s2am_ard_3-2-1_51KZQ_2018-07-29_final
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_50KRV_2018-08-07_final
2018-08-08 11:13:24	ga_s2am_ard_3-2-1_51KZQ_2018-08-08_final
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_50KRV_2018-08-17_final
2018-08-18 11:12:58	ga_s2am_ard_3-2-1_51KZQ_2018-08-18_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50KRV_2018-08-27_final
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_51KZQ_2018-08-28_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50KRV_2018-09-06_final
2018-09-07 11:13:22	ga_s2am_ard_3-2-1_51KZQ_2018-09-07_final
2018-09-17 11:13:02	ga_s2am_ard_3-2-1_51KZQ_2018-09-17_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50KRV_2018-09-26_final
2018-09-27 11:12:40	ga_s2am_ard_3-2-1_51KZQ_2018-09-27_final
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50KRV_2018-10-06_final
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_51KZQ_2018-10-07_final
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50KRV_2018-10-16_final
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_51KZQ_2018-10-17_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50KRV_2018-10-26_final
2018-10-27 11:07:09	ga_s2am_ard_3-2-1_51KZQ_2018-10-27_final
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_50KRV_2018-11-05_final
2018-11-06 11:13:50	ga_s2am_ard_3-2-1_51KZQ_2018-11-06_final
2018-11-15 11:43:56	ga_s2am_ard_3-2-1_50KRV_2018-11-15_final
2018-11-16 11:13:48	ga_s2am_ard_3-2-1_51KZQ_2018-11-16_final
2018-11-25 11:43:54	ga_s2am_ard_3-2-1_50KRV_2018-11-25_final
2018-11-26 11:13:46	ga_s2am_ard_3-2-1_51KZQ_2018-11-26_final
2018-12-06 11:13:46	ga_s2am_ard_3-2-1_51KZQ_2018-12-06_final
2018-12-15 11:43:53	ga_s2am_ard_3-2-1_50KRV_2018-12-15_final
2018-12-16 11:13:45	ga_s2am_ard_3-2-1_51KZQ_2018-12-16_final
2018-12-25 11:43:54	ga_s2am_ard_3-2-1_50KRV_2018-12-25_final
2018-12-26 11:13:47	ga_s2am_ard_3-2-1_51KZQ_2018-12-26_final
2019-01-04 11:43:56	ga_s2am_ard_3-2-1_50KRV_2019-01-04_final
2019-01-05 11:13:49	ga_s2am_ard_3-2-1_51KZQ_2019-01-05_final
2019-01-14 11:43:58	ga_s2am_ard_3-2-1_50KRV_2019-01-14_final
2019-01-15 11:13:50	ga_s2am_ard_3-2-1_51KZQ_2019-01-15_final
2019-01-24 11:43:58	ga_s2am_ard_3-2-1_50KRV_2019-01-24_final
2019-01-25 11:13:51	ga_s2am_ard_3-2-1_51KZQ_2019-01-25_final
2019-02-03 11:43:59	ga_s2am_ard_3-2-1_50KRV_2019-02-03_final
2019-02-04 11:13:51	ga_s2am_ard_3-2-1_51KZQ_2019-02-04_final
2019-02-13 11:43:58	ga_s2am_ard_3-2-1_50KRV_2019-02-13_final
2019-02-14 11:13:51	ga_s2am_ard_3-2-1_51KZQ_2019-02-14_final
2019-02-23 11:43:58	ga_s2am_ard_3-2-1_50KRV_2019-02-23_final
2019-02-24 11:13:50	ga_s2am_ard_3-2-1_51KZQ_2019-02-24_final
2019-03-05 11:43:56	ga_s2am_ard_3-2-1_50KRV_2019-03-05_final
2019-03-06 11:13:48	ga_s2am_ard_3-2-1_51KZQ_2019-03-06_final
2019-03-15 11:43:58	ga_s2am_ard_3-2-1_50KRV_2019-03-15_final
2019-03-16 11:13:51	ga_s2am_ard_3-2-1_51KZQ_2019-03-16_final
2019-03-25 11:44:01	ga_s2am_ard_3-2-1_50KRV_2019-03-25_final
2019-03-26 11:13:53	ga_s2am_ard_3-2-1_51KZQ_2019-03-26_final
2019-04-04 11:44:03	ga_s2am_ard_3-2-1_50KRV_2019-04-04_final
2019-04-05 11:13:55	ga_s2am_ard_3-2-1_51KZQ_2019-04-05_final
2019-04-14 11:44:04	ga_s2am_ard_3-2-1_50KRV_2019-04-14_final
2019-04-15 11:13:56	ga_s2am_ard_3-2-1_51KZQ_2019-04-15_final
2019-04-24 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-04-24_final
2019-05-04 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-05-04_final
2019-05-14 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-05-14_final
2019-05-24 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-05-24_final
2019-06-03 11:44:04	ga_s2am_ard_3-2-1_50KRV_2019-06-03_final
2019-06-13 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-06-13_final
2019-06-23 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-06-23_final
2019-07-03 11:44:07	ga_s2am_ard_3-2-1_50KRV_2019-07-03_final
2019-07-13 11:44:07	ga_s2am_ard_3-2-1_50KRV_2019-07-13_final
2019-07-23 11:44:07	ga_s2am_ard_3-2-1_50KRV_2019-07-23_final
2019-08-02 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-08-02_final
2019-08-12 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-08-12_final
2019-08-22 11:44:04	ga_s2am_ard_3-2-1_50KRV_2019-08-22_final
2019-09-01 11:44:02	ga_s2am_ard_3-2-1_50KRV_2019-09-01_final
2019-09-11 11:44:00	ga_s2am_ard_3-2-1_50KRV_2019-09-11_final
2019-09-21 11:44:02	ga_s2am_ard_3-2-1_50KRV_2019-09-21_final
2019-10-01 11:44:03	ga_s2am_ard_3-2-1_50KRV_2019-10-01_final
2019-10-11 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-10-11_final
2019-10-21 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-10-21_final
2019-10-31 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-10-31_final
2019-11-10 11:44:04	ga_s2am_ard_3-2-1_50KRV_2019-11-10_final
2019-11-20 11:44:03	ga_s2am_ard_3-2-1_50KRV_2019-11-20_final
2019-11-30 11:44:01	ga_s2am_ard_3-2-1_50KRV_2019-11-30_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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