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
2018-01-02 10:16:50	ga_s2am_ard_3-2-1_53HQA_2018-01-02_final
2018-01-09 10:01:33	ga_s2am_ard_3-2-1_54HYF_2018-01-09_final
2018-01-29 10:01:36	ga_s2am_ard_3-2-1_54HYF_2018-01-29_final
2018-02-05 09:52:53	ga_s2am_ard_3-2-1_54HYF_2018-02-05_final
2018-02-15 09:51:52	ga_s2am_ard_3-2-1_54HYF_2018-02-15_final
2018-03-07 09:50:50	ga_s2am_ard_3-2-1_54HYF_2018-03-07_final
2018-03-17 09:50:50	ga_s2am_ard_3-2-1_54HYF_2018-03-17_final
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_54HYF_2018-03-27_final
2018-04-09 09:57:08	ga_s2am_ard_3-2-1_54HYF_2018-04-09_final
2018-04-19 09:57:09	ga_s2am_ard_3-2-1_54HYF_2018-04-19_final
2018-04-29 09:57:09	ga_s2am_ard_3-2-1_54HYF_2018-04-29_final
2018-05-06 09:50:57	ga_s2am_ard_3-2-1_54HYF_2018-05-06_final
2018-05-09 10:02:56	ga_s2am_ard_3-2-1_54HYF_2018-05-09_final
2018-05-16 09:50:57	ga_s2am_ard_3-2-1_54HYF_2018-05-16_final
2018-05-19 09:57:09	ga_s2am_ard_3-2-1_54HYF_2018-05-19_final
2018-05-29 09:57:09	ga_s2am_ard_3-2-1_54HYF_2018-05-29_final
2018-06-05 09:50:55	ga_s2am_ard_3-2-1_54HYF_2018-06-05_final
2018-06-08 09:57:07	ga_s2am_ard_3-2-1_54HYF_2018-06-08_final
2018-06-15 09:50:53	ga_s2am_ard_3-2-1_54HYF_2018-06-15_final
2018-06-18 09:57:07	ga_s2am_ard_3-2-1_54HYF_2018-06-18_final
2018-06-28 09:57:08	ga_s2am_ard_3-2-1_54HYF_2018-06-28_final
2018-07-05 09:55:26	ga_s2am_ard_3-2-1_54HYF_2018-07-05_final
2018-07-15 09:50:55	ga_s2am_ard_3-2-1_54HYF_2018-07-15_final
2018-08-11 09:41:08	ga_s2am_ard_3-2-1_55HEA_2018-08-11_final
2018-08-18 09:36:30	ga_s2am_ard_3-2-1_55HEA_2018-08-18_final
2018-08-21 09:41:08	ga_s2am_ard_3-2-1_55HEA_2018-08-21_final
2018-08-21 09:46:40	ga_s2am_ard_3-2-1_55HDA_2018-08-21_final
2018-08-21 09:46:40	ga_s2am_ard_3-2-1_55HEA_2018-08-21_final
2018-08-24 09:50:53	ga_s2am_ard_3-2-1_55HDA_2018-08-24_final
2018-08-28 09:32:38	ga_s2am_ard_3-2-1_55HEA_2018-08-28_final
2018-08-28 09:32:38	ga_s2am_ard_3-2-1_56JLL_2018-08-28_final
2018-08-31 09:41:07	ga_s2am_ard_3-2-1_55HDA_2018-08-31_final
2018-08-31 09:41:07	ga_s2am_ard_3-2-1_55HEA_2018-08-31_final
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55HDA_2018-09-03_final
2018-09-04 09:22:42	ga_s2am_ard_3-2-1_56JLL_2018-09-03_final
2018-09-07 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-09-07_final
2018-09-07 09:32:37	ga_s2am_ard_3-2-1_56JLL_2018-09-07_final
2018-09-10 09:41:06	ga_s2am_ard_3-2-1_55HDA_2018-09-10_final
2018-09-10 09:41:06	ga_s2am_ard_3-2-1_55HEA_2018-09-10_final
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55HDA_2018-09-13_final
2018-09-14 09:22:41	ga_s2am_ard_3-2-1_56JLL_2018-09-13_final
2018-09-17 09:32:36	ga_s2am_ard_3-2-1_55HEA_2018-09-17_final
2018-09-17 09:32:36	ga_s2am_ard_3-2-1_56JLL_2018-09-17_final
2018-09-27 09:32:36	ga_s2am_ard_3-2-1_55HEA_2018-09-27_final
2018-09-27 09:32:36	ga_s2am_ard_3-2-1_56JLL_2018-09-27_final
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55HDA_2018-09-30_final
2018-09-30 09:41:05	ga_s2am_ard_3-2-1_55HEA_2018-09-30_final
2018-10-03 09:50:51	ga_s2am_ard_3-2-1_55HDA_2018-10-03_final
2018-10-04 09:22:41	ga_s2am_ard_3-2-1_56JLL_2018-10-03_final
2018-10-07 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-07_final
2018-10-07 09:32:37	ga_s2am_ard_3-2-1_56JLL_2018-10-07_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HDA_2018-10-10_final
2018-10-10 09:45:00	ga_s2am_ard_3-2-1_55HEA_2018-10-10_final
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55HDA_2018-10-13_final
2018-10-14 09:22:42	ga_s2am_ard_3-2-1_56JLL_2018-10-13_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-17_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JLL_2018-10-17_final
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55HDA_2018-10-20_final
2018-10-20 09:41:06	ga_s2am_ard_3-2-1_55HEA_2018-10-20_final
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55HDA_2018-10-23_final
2018-10-24 09:22:42	ga_s2am_ard_3-2-1_56JLL_2018-10-23_final
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_55HEA_2018-10-27_final
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_56JLL_2018-10-27_final
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55HDA_2018-10-30_final
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55HEA_2018-10-30_final
2018-11-02 09:50:51	ga_s2am_ard_3-2-1_55HDA_2018-11-02_final
2018-11-03 09:22:41	ga_s2am_ard_3-2-1_56JLL_2018-11-02_final
2018-11-06 09:32:36	ga_s2am_ard_3-2-1_55HEA_2018-11-06_final
2018-11-06 09:32:36	ga_s2am_ard_3-2-1_56JLL_2018-11-06_final
2018-11-09 09:46:41	ga_s2am_ard_3-2-1_55HEA_2018-11-09_final
2018-11-09 09:46:44	ga_s2am_ard_3-2-1_55HDA_2018-11-09_final
2018-11-12 09:56:40	ga_s2am_ard_3-2-1_55HDA_2018-11-12_final
2018-11-13 09:25:24	ga_s2am_ard_3-2-1_56JLL_2018-11-12_final
2018-11-16 09:35:18	ga_s2am_ard_3-2-1_56JLL_2018-11-16_final
2018-11-16 09:36:44	ga_s2am_ard_3-2-1_55HEA_2018-11-16_final
2018-11-19 09:46:39	ga_s2am_ard_3-2-1_55HEA_2018-11-19_final
2018-11-19 09:46:43	ga_s2am_ard_3-2-1_55HDA_2018-11-19_final
2018-11-22 09:56:38	ga_s2am_ard_3-2-1_55HDA_2018-11-22_final
2018-11-23 09:25:22	ga_s2am_ard_3-2-1_56JLL_2018-11-22_final
2018-11-26 09:35:16	ga_s2am_ard_3-2-1_56JLL_2018-11-26_final
2018-11-26 09:36:42	ga_s2am_ard_3-2-1_55HEA_2018-11-26_final
2018-11-29 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-11-29_final
2018-11-29 09:46:40	ga_s2am_ard_3-2-1_55HDA_2018-11-29_final
2018-12-02 09:56:36	ga_s2am_ard_3-2-1_55HDA_2018-12-02_final
2018-12-03 09:25:21	ga_s2am_ard_3-2-1_56JLL_2018-12-02_final
2018-12-06 09:35:16	ga_s2am_ard_3-2-1_56JLL_2018-12-06_final
2018-12-06 09:36:42	ga_s2am_ard_3-2-1_55HEA_2018-12-06_final
2018-12-09 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-12-09_final
2018-12-09 09:46:41	ga_s2am_ard_3-2-1_55HDA_2018-12-09_final
2018-12-12 09:56:37	ga_s2am_ard_3-2-1_55HDA_2018-12-12_final
2018-12-13 09:25:21	ga_s2am_ard_3-2-1_56JLL_2018-12-12_final
2018-12-16 09:35:16	ga_s2am_ard_3-2-1_56JLL_2018-12-16_final
2018-12-16 09:36:42	ga_s2am_ard_3-2-1_55HEA_2018-12-16_final
2018-12-19 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-12-19_final
2018-12-19 09:46:40	ga_s2am_ard_3-2-1_55HDA_2018-12-19_final
2018-12-22 09:56:37	ga_s2am_ard_3-2-1_55HDA_2018-12-22_final
2018-12-23 09:25:22	ga_s2am_ard_3-2-1_56JLL_2018-12-22_final
2018-12-26 09:35:17	ga_s2am_ard_3-2-1_56JLL_2018-12-26_final
2018-12-26 09:36:43	ga_s2am_ard_3-2-1_55HEA_2018-12-26_final
2018-12-29 09:46:39	ga_s2am_ard_3-2-1_55HEA_2018-12-29_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