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
2017-07-11 11:49:46	ga_s2bm_ard_3-2-1_50JNQ_2017-07-11_final
2017-07-18 11:45:05	ga_s2bm_ard_3-2-1_50JNQ_2017-07-18_final
2017-07-31 11:49:45	ga_s2bm_ard_3-2-1_50JNQ_2017-07-31_final
2017-08-07 11:45:07	ga_s2bm_ard_3-2-1_50JNQ_2017-08-07_final
2017-08-20 11:49:42	ga_s2bm_ard_3-2-1_50JNQ_2017-08-20_final
2017-08-27 11:40:44	ga_s2bm_ard_3-2-1_50JNQ_2017-08-27_final
2017-09-09 11:51:47	ga_s2bm_ard_3-2-1_50JNQ_2017-09-09_final
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50JNQ_2017-09-16_final
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50JNQ_2017-09-29_final
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50JNQ_2017-10-06_final
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JNQ_2017-10-19_final
2017-10-26 11:41:25	ga_s2bm_ard_3-2-1_50JNQ_2017-10-26_final
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50JNQ_2017-11-05_final
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JNQ_2017-11-08_final
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50JNQ_2017-11-15_final
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50JNQ_2017-11-18_final
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50JNQ_2017-11-25_final
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50JNQ_2017-11-28_final
2017-12-05 11:40:37	ga_s2bm_ard_3-2-1_50JNQ_2017-12-05_final
2017-12-08 11:49:07	ga_s2bm_ard_3-2-1_50JNQ_2017-12-08_final
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50JNQ_2017-12-15_final
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JNQ_2017-12-18_final
2017-12-25 11:40:37	ga_s2bm_ard_3-2-1_50JNQ_2017-12-25_final
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNQ_2017-12-28_final
2018-01-04 11:37:43	ga_s2bm_ard_3-2-1_50JNQ_2018-01-04_final
2018-01-07 11:50:37	ga_s2bm_ard_3-2-1_50JNQ_2018-01-07_final
2018-01-14 11:40:41	ga_s2bm_ard_3-2-1_50JNQ_2018-01-14_final
2018-01-17 11:49:12	ga_s2bm_ard_3-2-1_50JNQ_2018-01-17_final
2018-01-24 11:37:42	ga_s2bm_ard_3-2-1_50JNQ_2018-01-24_final
2018-01-27 11:50:39	ga_s2bm_ard_3-2-1_50JNQ_2018-01-27_final
2018-02-03 11:40:42	ga_s2bm_ard_3-2-1_50JNQ_2018-02-03_final
2018-02-06 11:49:12	ga_s2bm_ard_3-2-1_50JNQ_2018-02-06_final
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50JNQ_2018-02-13_final
2018-02-16 11:54:55	ga_s2bm_ard_3-2-1_50JNQ_2018-02-16_final
2018-02-23 11:44:25	ga_s2bm_ard_3-2-1_50JNQ_2018-02-23_final
2018-02-26 11:49:11	ga_s2bm_ard_3-2-1_50JNQ_2018-02-26_final
2018-03-05 11:42:06	ga_s2bm_ard_3-2-1_50JNQ_2018-03-05_final
2018-03-08 11:51:37	ga_s2bm_ard_3-2-1_50JNQ_2018-03-08_final
2018-03-15 11:39:58	ga_s2bm_ard_3-2-1_50JNQ_2018-03-15_final
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JNQ_2018-03-18_final
2018-03-25 11:44:34	ga_s2bm_ard_3-2-1_50JNQ_2018-03-25_final
2018-03-28 11:51:53	ga_s2bm_ard_3-2-1_50JNQ_2018-03-28_final
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50JNQ_2018-04-04_final
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JNQ_2018-04-07_final
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50JNQ_2018-04-14_final
2018-04-17 11:52:54	ga_s2bm_ard_3-2-1_50JNQ_2018-04-17_final
2018-04-24 11:41:02	ga_s2bm_ard_3-2-1_50JNQ_2018-04-24_final
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JNQ_2018-04-27_final
2018-05-04 11:43:41	ga_s2bm_ard_3-2-1_50JNQ_2018-05-04_final
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50JNQ_2018-05-07_final
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50JNQ_2018-05-14_final
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50JNQ_2018-05-17_final
2018-05-24 11:43:21	ga_s2bm_ard_3-2-1_50JNQ_2018-05-24_final
2018-06-03 11:40:10	ga_s2bm_ard_3-2-1_50JNQ_2018-06-03_final
2018-06-06 11:51:08	ga_s2bm_ard_3-2-1_50JNQ_2018-06-06_final
2018-06-13 11:43:22	ga_s2bm_ard_3-2-1_50JNQ_2018-06-13_final
2018-06-16 11:51:10	ga_s2bm_ard_3-2-1_50JNQ_2018-06-16_final
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JNQ_2018-06-23_final
2018-06-26 11:54:14	ga_s2bm_ard_3-2-1_50JNQ_2018-06-26_final
2018-07-03 11:44:57	ga_s2bm_ard_3-2-1_50JNQ_2018-07-03_final
2018-07-06 11:51:46	ga_s2bm_ard_3-2-1_50JNQ_2018-07-06_final
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50JNQ_2018-07-13_final
2018-07-16 11:52:50	ga_s2bm_ard_3-2-1_50JNQ_2018-07-16_final
2018-07-23 11:40:57	ga_s2bm_ard_3-2-1_50JNQ_2018-07-23_final
2018-07-26 11:52:57	ga_s2bm_ard_3-2-1_50JNQ_2018-07-26_final
2018-08-02 11:44:54	ga_s2bm_ard_3-2-1_50JNQ_2018-08-02_final
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50JNQ_2018-08-05_final
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JNQ_2018-08-12_final
2018-08-15 11:54:27	ga_s2bm_ard_3-2-1_50JNQ_2018-08-15_final
2018-08-22 11:44:50	ga_s2bm_ard_3-2-1_50JNQ_2018-08-22_final
2018-08-25 11:52:52	ga_s2bm_ard_3-2-1_50JNQ_2018-08-25_final
2020-03-27 11:55:18	ga_s2bm_ard_3-2-1_50JNQ_2020-03-27_final
2020-04-03 11:45:22	ga_s2bm_ard_3-2-1_50JNQ_2020-04-03_final
2020-04-06 11:55:17	ga_s2bm_ard_3-2-1_50JNQ_2020-04-06_final
2020-04-13 11:45:21	ga_s2bm_ard_3-2-1_50JNQ_2020-04-13_final
2020-04-16 11:55:16	ga_s2bm_ard_3-2-1_50JNQ_2020-04-16_final
2020-04-23 11:45:19	ga_s2bm_ard_3-2-1_50JNQ_2020-04-23_final
2020-04-26 11:55:15	ga_s2bm_ard_3-2-1_50JNQ_2020-04-26_final
2020-05-03 11:45:21	ga_s2bm_ard_3-2-1_50JNQ_2020-05-03_final
2020-05-06 11:55:18	ga_s2bm_ard_3-2-1_50JNQ_2020-05-06_final
2020-05-13 11:45:23	ga_s2bm_ard_3-2-1_50JNQ_2020-05-13_final
2020-05-16 11:55:20	ga_s2bm_ard_3-2-1_50JNQ_2020-05-16_final
2020-05-23 11:45:25	ga_s2bm_ard_3-2-1_50JNQ_2020-05-23_final
2020-05-26 11:55:21	ga_s2bm_ard_3-2-1_50JNQ_2020-05-26_final
2020-06-02 11:45:26	ga_s2bm_ard_3-2-1_50JNQ_2020-06-02_final
2020-06-05 11:55:22	ga_s2bm_ard_3-2-1_50JNQ_2020-06-05_final
2020-06-12 11:45:27	ga_s2bm_ard_3-2-1_50JNQ_2020-06-12_final
2020-06-15 11:55:23	ga_s2bm_ard_3-2-1_50JNQ_2020-06-15_final
2020-06-22 11:45:27	ga_s2bm_ard_3-2-1_50JNQ_2020-06-22_final
2020-06-25 11:55:23	ga_s2bm_ard_3-2-1_50JNQ_2020-06-25_final
2020-07-02 11:45:27	ga_s2bm_ard_3-2-1_50JNQ_2020-07-02_final
2020-07-05 11:55:22	ga_s2bm_ard_3-2-1_50JNQ_2020-07-05_final
2020-07-12 11:45:26	ga_s2bm_ard_3-2-1_50JNQ_2020-07-12_final
2020-07-15 11:55:22	ga_s2bm_ard_3-2-1_50JNQ_2020-07-15_final
2020-07-22 11:45:26	ga_s2bm_ard_3-2-1_50JNQ_2020-07-22_final
2020-07-25 11:55:23	ga_s2bm_ard_3-2-1_50JNQ_2020-07-25_final
2020-08-01 11:45:27	ga_s2bm_ard_3-2-1_50JNQ_2020-08-01_final
2020-08-04 11:55:23	ga_s2bm_ard_3-2-1_50JNQ_2020-08-04_final
2020-08-11 11:45:28	ga_s2bm_ard_3-2-1_50JNQ_2020-08-11_final
2020-08-14 11:55:24	ga_s2bm_ard_3-2-1_50JNQ_2020-08-14_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