Search ga_s2am_ard_3 across 2018

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
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_50JLP_2018-01-05_final
2018-01-09 10:01:33	ga_s2am_ard_3-2-1_55JCJ_2018-01-09_final
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_50JLP_2018-01-25_final
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_55JCJ_2018-01-29_final
2018-02-08 09:57:03	ga_s2am_ard_3-2-1_55JCJ_2018-02-08_final
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-02-14_final
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_55JCJ_2018-02-18_final
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-02-24_final
2018-02-28 09:57:04	ga_s2am_ard_3-2-1_55JCJ_2018-02-28_final
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-03-06_final
2018-03-10 09:57:03	ga_s2am_ard_3-2-1_55JCJ_2018-03-10_final
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_50JLP_2018-03-16_final
2018-03-20 09:57:04	ga_s2am_ard_3-2-1_55JCJ_2018-03-20_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JLP_2018-03-26_final
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_55JCJ_2018-03-30_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JLP_2018-04-05_final
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JLP_2018-04-15_final
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_55JCJ_2018-04-19_final
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JLP_2018-04-25_final
2018-04-29 09:57:09	ga_s2am_ard_3-2-1_55JCJ_2018-04-29_final
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JLP_2018-05-05_final
2018-05-09 10:02:56	ga_s2am_ard_3-2-1_55JCJ_2018-05-09_final
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_50JLP_2018-05-15_final
2018-05-19 09:57:09	ga_s2am_ard_3-2-1_55JCJ_2018-05-19_final
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JLP_2018-05-25_final
2018-05-29 09:57:09	ga_s2am_ard_3-2-1_55JCJ_2018-05-29_final
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50JLP_2018-06-04_final
2018-06-08 09:57:07	ga_s2am_ard_3-2-1_55JCJ_2018-06-08_final
2018-06-09 09:32:54	ga_s2am_ard_3-2-1_56JKN_2018-06-09_final
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLP_2018-06-14_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_55JCJ_2018-06-18_final
2018-06-19 09:32:58	ga_s2am_ard_3-2-1_56JKN_2018-06-19_final
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JLP_2018-06-24_final
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_55JCJ_2018-06-28_final
2018-06-29 09:32:41	ga_s2am_ard_3-2-1_56JKN_2018-06-29_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JLP_2018-07-04_final
2018-07-08 09:57:08	ga_s2am_ard_3-2-1_55JCJ_2018-07-08_final
2018-07-09 09:32:41	ga_s2am_ard_3-2-1_56JKN_2018-07-09_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLP_2018-07-14_final
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_55JBH_2018-07-15_final
2018-07-18 09:57:08	ga_s2am_ard_3-2-1_55JCJ_2018-07-18_final
2018-07-18 09:57:08	ga_s2am_ard_3-2-1_55JBH_2018-07-18_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JLP_2018-07-24_final
2018-07-25 09:50:55	ga_s2am_ard_3-2-1_55JBH_2018-07-25_final
2018-07-28 09:57:08	ga_s2am_ard_3-2-1_55JCJ_2018-07-28_final
2018-07-28 09:57:08	ga_s2am_ard_3-2-1_55JBH_2018-07-28_final
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50JLP_2018-08-03_final
2018-08-04 09:50:54	ga_s2am_ard_3-2-1_55JBH_2018-08-04_final
2018-08-07 09:57:07	ga_s2am_ard_3-2-1_55JCJ_2018-08-07_final
2018-08-07 09:57:07	ga_s2am_ard_3-2-1_55JBH_2018-08-07_final
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLP_2018-08-13_final
2018-08-14 09:50:54	ga_s2am_ard_3-2-1_55JBH_2018-08-14_final
2018-08-17 09:57:07	ga_s2am_ard_3-2-1_55JCJ_2018-08-17_final
2018-08-17 09:57:07	ga_s2am_ard_3-2-1_55JBH_2018-08-17_final
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JLP_2018-08-23_final
2018-08-24 09:50:53	ga_s2am_ard_3-2-1_55JBH_2018-08-24_final
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_55JCJ_2018-08-27_final
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_55JBH_2018-08-27_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLP_2018-09-02_final
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JBH_2018-09-03_final
2018-09-06 09:57:05	ga_s2am_ard_3-2-1_55JCJ_2018-09-06_final
2018-09-06 09:57:05	ga_s2am_ard_3-2-1_55JBH_2018-09-06_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-09-12_final
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JBH_2018-09-13_final
2018-09-26 09:57:03	ga_s2am_ard_3-2-1_55JCJ_2018-09-26_final
2018-09-26 09:57:03	ga_s2am_ard_3-2-1_55JBH_2018-09-26_final
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-10-02_final
2018-10-03 09:50:51	ga_s2am_ard_3-2-1_55JBH_2018-10-03_final
2018-10-06 09:57:04	ga_s2am_ard_3-2-1_55JCJ_2018-10-06_final
2018-10-06 09:57:04	ga_s2am_ard_3-2-1_55JBH_2018-10-06_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLP_2018-10-12_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JBH_2018-10-13_final
2018-10-16 09:57:04	ga_s2am_ard_3-2-1_55JCJ_2018-10-16_final
2018-10-16 09:57:04	ga_s2am_ard_3-2-1_55JBH_2018-10-16_final
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-10-22_final
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55JBH_2018-10-23_final
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55JCJ_2018-10-26_final
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55JBH_2018-10-26_final
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-11-01_final
2018-11-02 09:50:51	ga_s2am_ard_3-2-1_55JBH_2018-11-02_final
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_55JCJ_2018-11-05_final
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_55JBH_2018-11-05_final
2018-11-11 12:05:33	ga_s2am_ard_3-2-1_50JLP_2018-11-11_final
2018-11-12 09:55:06	ga_s2am_ard_3-2-1_55JBH_2018-11-12_final
2018-11-15 10:04:42	ga_s2am_ard_3-2-1_55JCJ_2018-11-15_final
2018-11-15 10:05:00	ga_s2am_ard_3-2-1_55JBH_2018-11-15_final
2018-11-21 12:05:31	ga_s2am_ard_3-2-1_50JLP_2018-11-21_final
2018-11-22 09:55:04	ga_s2am_ard_3-2-1_55JBH_2018-11-22_final
2018-11-25 10:04:40	ga_s2am_ard_3-2-1_55JCJ_2018-11-25_final
2018-11-25 10:04:58	ga_s2am_ard_3-2-1_55JBH_2018-11-25_final
2018-12-01 12:05:29	ga_s2am_ard_3-2-1_50JLP_2018-12-01_final
2018-12-02 09:55:02	ga_s2am_ard_3-2-1_55JBH_2018-12-02_final
2018-12-11 12:05:29	ga_s2am_ard_3-2-1_50JLP_2018-12-11_final
2018-12-12 09:55:03	ga_s2am_ard_3-2-1_55JBH_2018-12-12_final
2018-12-15 10:04:39	ga_s2am_ard_3-2-1_55JCJ_2018-12-15_final
2018-12-15 10:04:57	ga_s2am_ard_3-2-1_55JBH_2018-12-15_final
2018-12-21 12:05:29	ga_s2am_ard_3-2-1_50JLP_2018-12-21_final
2018-12-22 09:55:03	ga_s2am_ard_3-2-1_55JBH_2018-12-22_final
2018-12-25 10:04:40	ga_s2am_ard_3-2-1_55JCJ_2018-12-25_final
2018-12-25 10:04:58	ga_s2am_ard_3-2-1_55JBH_2018-12-25_final

Return to ga_s2am_ard_3 across 2018 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

2018

All months