Search ga_s2bm_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
2018-10-08 11:30:50	ga_s2bm_ard_3-2-1_50JQN_2018-10-08_final
2018-10-11 11:41:47	ga_s2bm_ard_3-2-1_50JQN_2018-10-11_final
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_50JQN_2018-10-28_final
2018-10-31 11:39:52	ga_s2bm_ard_3-2-1_50JQN_2018-10-31_final
2018-11-07 11:35:48	ga_s2bm_ard_3-2-1_50JQN_2018-11-07_final
2018-11-10 11:45:44	ga_s2bm_ard_3-2-1_50JQN_2018-11-10_final
2018-11-17 11:35:47	ga_s2bm_ard_3-2-1_50JQN_2018-11-17_final
2018-11-20 11:45:37	ga_s2bm_ard_3-2-1_50JQN_2018-11-20_final
2018-11-20 11:45:44	ga_s2bm_ard_3-2-1_50JQN_2018-11-20_final
2018-11-27 11:35:46	ga_s2bm_ard_3-2-1_50JQN_2018-11-27_final
2018-11-30 11:45:42	ga_s2bm_ard_3-2-1_50JQN_2018-11-30_final
2018-12-07 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2018-12-07_final
2018-12-10 11:45:40	ga_s2bm_ard_3-2-1_50JQN_2018-12-10_final
2018-12-17 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2018-12-17_final
2018-12-20 11:45:41	ga_s2bm_ard_3-2-1_50JQN_2018-12-20_final
2018-12-27 11:35:47	ga_s2bm_ard_3-2-1_50JQN_2018-12-27_final
2018-12-30 11:45:43	ga_s2bm_ard_3-2-1_50JQN_2018-12-30_final
2019-01-06 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2019-01-06_final
2019-01-09 11:45:45	ga_s2bm_ard_3-2-1_50JQN_2019-01-09_final
2019-01-16 11:35:50	ga_s2bm_ard_3-2-1_50JQN_2019-01-16_final
2019-01-19 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-01-19_final
2019-01-26 11:35:50	ga_s2bm_ard_3-2-1_50JQN_2019-01-26_final
2019-01-29 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2019-01-29_final
2019-02-05 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-02-05_final
2019-02-08 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2019-02-08_final
2019-02-15 11:35:50	ga_s2bm_ard_3-2-1_50JQN_2019-02-15_final
2019-02-18 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-02-18_final
2019-02-25 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2019-02-25_final
2019-02-28 11:45:45	ga_s2bm_ard_3-2-1_50JQN_2019-02-28_final
2019-03-10 11:45:44	ga_s2bm_ard_3-2-1_50JQN_2019-03-10_final
2019-03-17 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2019-03-17_final
2019-03-20 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-03-20_final
2019-03-27 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-03-27_final
2019-03-30 11:45:48	ga_s2bm_ard_3-2-1_50JQN_2019-03-30_final
2019-04-06 11:35:54	ga_s2bm_ard_3-2-1_50JQN_2019-04-06_final
2019-04-09 11:45:50	ga_s2bm_ard_3-2-1_50JQN_2019-04-09_final
2019-04-16 11:35:56	ga_s2bm_ard_3-2-1_50JQN_2019-04-16_final
2019-04-19 11:45:52	ga_s2bm_ard_3-2-1_50JQN_2019-04-19_final
2019-04-26 11:35:57	ga_s2bm_ard_3-2-1_50JQN_2019-04-26_final
2019-04-29 11:45:54	ga_s2bm_ard_3-2-1_50JQN_2019-04-29_final
2019-05-06 11:35:58	ga_s2bm_ard_3-2-1_50JQN_2019-05-06_final
2019-05-09 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-05-09_final
2019-05-16 11:35:55	ga_s2bm_ard_3-2-1_50JQN_2019-05-16_final
2019-05-16 11:36:01	ga_s2bm_ard_3-2-1_50JQN_2019-05-16_final
2019-05-19 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-05-19_final
2019-05-26 11:35:59	ga_s2bm_ard_3-2-1_50JQN_2019-05-26_final
2019-05-29 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-05-29_final
2019-06-05 11:35:58	ga_s2bm_ard_3-2-1_50JQN_2019-06-05_final
2019-06-08 11:45:54	ga_s2bm_ard_3-2-1_50JQN_2019-06-08_final
2019-06-15 11:35:58	ga_s2bm_ard_3-2-1_50JQN_2019-06-15_final
2019-06-18 11:45:54	ga_s2bm_ard_3-2-1_50JQN_2019-06-18_final
2019-06-25 11:35:59	ga_s2bm_ard_3-2-1_50JQN_2019-06-25_final
2019-06-28 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-06-28_final
2019-07-05 11:35:59	ga_s2bm_ard_3-2-1_50JQN_2019-07-05_final
2019-07-08 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-07-08_final
2019-07-15 11:35:59	ga_s2bm_ard_3-2-1_50JQN_2019-07-15_final
2019-07-18 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-07-18_final
2019-07-25 11:35:57	ga_s2bm_ard_3-2-1_50JQN_2019-07-25_final
2019-07-25 11:36:03	ga_s2bm_ard_3-2-1_50JQN_2019-07-25_final
2019-07-28 11:45:55	ga_s2bm_ard_3-2-1_50JQN_2019-07-28_final
2019-08-04 11:35:58	ga_s2bm_ard_3-2-1_50JQN_2019-08-04_final
2019-08-07 11:45:54	ga_s2bm_ard_3-2-1_50JQN_2019-08-07_final
2019-08-14 11:35:57	ga_s2bm_ard_3-2-1_50JQN_2019-08-14_final
2019-08-17 11:45:52	ga_s2bm_ard_3-2-1_50JQN_2019-08-17_final
2019-08-24 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-08-24_final
2019-08-24 11:35:58	ga_s2bm_ard_3-2-1_50JQN_2019-08-24_final
2019-08-27 11:45:51	ga_s2bm_ard_3-2-1_50JQN_2019-08-27_final
2019-09-03 11:35:53	ga_s2bm_ard_3-2-1_50JQN_2019-09-03_final
2019-09-06 11:45:49	ga_s2bm_ard_3-2-1_50JQN_2019-09-06_final
2019-09-13 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-09-13_final
2019-09-16 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-09-16_final
2019-09-23 11:35:50	ga_s2bm_ard_3-2-1_50JQN_2019-09-23_final
2019-09-26 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-09-26_final
2019-10-03 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-10-03_final
2019-10-06 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2019-10-06_final
2019-10-13 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-10-13_final
2019-10-16 11:45:48	ga_s2bm_ard_3-2-1_50JQN_2019-10-16_final
2019-10-23 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-10-23_final
2019-10-26 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2019-10-26_final
2019-11-02 11:35:51	ga_s2bm_ard_3-2-1_50JQN_2019-11-02_final
2019-11-05 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2019-11-05_final
2019-11-12 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2019-11-12_final
2019-11-15 11:45:45	ga_s2bm_ard_3-2-1_50JQN_2019-11-15_final
2019-11-22 11:35:49	ga_s2bm_ard_3-2-1_50JQN_2019-11-22_final
2019-11-25 11:45:43	ga_s2bm_ard_3-2-1_50JQN_2019-11-25_final
2019-12-02 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2019-12-02_final
2019-12-05 11:45:40	ga_s2bm_ard_3-2-1_50JQN_2019-12-05_final
2019-12-12 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2019-12-12_final
2019-12-15 11:45:41	ga_s2bm_ard_3-2-1_50JQN_2019-12-15_final
2019-12-22 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2019-12-22_final
2019-12-25 11:45:41	ga_s2bm_ard_3-2-1_50JQN_2019-12-25_final
2020-01-01 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2020-01-01_final
2020-01-04 11:45:41	ga_s2bm_ard_3-2-1_50JQN_2020-01-04_final
2020-01-11 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2020-01-11_final
2020-01-14 11:45:41	ga_s2bm_ard_3-2-1_50JQN_2020-01-14_final
2020-01-21 11:35:42	ga_s2bm_ard_3-2-1_50JQN_2020-01-21_final
2020-01-21 11:35:48	ga_s2bm_ard_3-2-1_50JQN_2020-01-21_final
2020-01-24 11:45:39	ga_s2bm_ard_3-2-1_50JQN_2020-01-24_final
2020-01-31 11:35:43	ga_s2bm_ard_3-2-1_50JQN_2020-01-31_final
2020-02-03 11:45:40	ga_s2bm_ard_3-2-1_50JQN_2020-02-03_final

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years