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
2017-11-07 10:37:13	ga_s2bm_ard_3-2-1_53KMQ_2017-11-07_final
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53KMQ_2017-11-17_final
2018-01-06 10:37:18	ga_s2bm_ard_3-2-1_53KMQ_2018-01-06_final
2018-01-16 10:42:58	ga_s2bm_ard_3-2-1_53KMQ_2018-01-16_final
2018-01-19 10:47:17	ga_s2bm_ard_3-2-1_53KMQ_2018-01-19_final
2018-01-26 10:37:20	ga_s2bm_ard_3-2-1_53KMQ_2018-01-26_final
2018-01-29 10:53:08	ga_s2bm_ard_3-2-1_53KMQ_2018-01-29_final
2018-02-05 10:42:59	ga_s2bm_ard_3-2-1_53KMQ_2018-02-05_final
2018-02-08 10:47:18	ga_s2bm_ard_3-2-1_53KMQ_2018-02-08_final
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53KMQ_2018-02-15_final
2018-02-18 10:53:07	ga_s2bm_ard_3-2-1_53KMQ_2018-02-18_final
2018-02-25 10:42:58	ga_s2bm_ard_3-2-1_53KMQ_2018-02-25_final
2018-02-28 10:47:16	ga_s2bm_ard_3-2-1_53KMQ_2018-02-28_final
2018-03-07 10:37:17	ga_s2bm_ard_3-2-1_53KMQ_2018-03-07_final
2018-03-10 10:47:15	ga_s2bm_ard_3-2-1_53KMQ_2018-03-10_final
2018-03-17 10:37:20	ga_s2bm_ard_3-2-1_53KMQ_2018-03-17_final
2018-03-20 10:51:09	ga_s2bm_ard_3-2-1_53KMQ_2018-03-20_final
2018-03-27 10:37:22	ga_s2bm_ard_3-2-1_53KMQ_2018-03-27_final
2018-03-30 10:47:20	ga_s2bm_ard_3-2-1_53KMQ_2018-03-30_final
2018-04-06 10:37:24	ga_s2bm_ard_3-2-1_53KMQ_2018-04-06_final
2018-04-09 10:50:37	ga_s2bm_ard_3-2-1_53KMQ_2018-04-09_final
2018-04-16 10:37:25	ga_s2bm_ard_3-2-1_53KMQ_2018-04-16_final
2018-04-19 10:47:23	ga_s2bm_ard_3-2-1_53KMQ_2018-04-19_final
2018-04-26 10:37:26	ga_s2bm_ard_3-2-1_53KMQ_2018-04-26_final
2018-04-29 10:47:24	ga_s2bm_ard_3-2-1_53KMQ_2018-04-29_final
2018-05-06 10:37:26	ga_s2bm_ard_3-2-1_53KMQ_2018-05-06_final
2018-05-09 10:47:23	ga_s2bm_ard_3-2-1_53KMQ_2018-05-09_final
2018-05-16 10:37:25	ga_s2bm_ard_3-2-1_53KMQ_2018-05-16_final
2018-05-19 10:47:23	ga_s2bm_ard_3-2-1_53KMQ_2018-05-19_final
2018-05-26 10:43:10	ga_s2bm_ard_3-2-1_53KMQ_2018-05-26_final
2018-05-29 10:47:21	ga_s2bm_ard_3-2-1_53KMQ_2018-05-29_final
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53KMQ_2018-06-05_final
2018-06-08 10:47:22	ga_s2bm_ard_3-2-1_53KMQ_2018-06-08_final
2018-06-15 10:37:25	ga_s2bm_ard_3-2-1_53KMQ_2018-06-15_final
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KMQ_2018-06-18_final
2018-06-25 10:42:47	ga_s2bm_ard_3-2-1_53KMQ_2018-06-25_final
2018-06-28 10:47:24	ga_s2bm_ard_3-2-1_53KMQ_2018-06-28_final
2018-07-05 10:40:12	ga_s2bm_ard_3-2-1_53KMQ_2018-07-05_final
2018-07-08 10:51:28	ga_s2bm_ard_3-2-1_53KMQ_2018-07-08_final
2018-07-15 10:41:45	ga_s2bm_ard_3-2-1_53KMQ_2018-07-15_final
2018-07-18 10:51:28	ga_s2bm_ard_3-2-1_53KMQ_2018-07-18_final
2018-07-25 10:41:04	ga_s2bm_ard_3-2-1_53KMQ_2018-07-25_final
2018-07-28 10:49:53	ga_s2bm_ard_3-2-1_53KMQ_2018-07-28_final
2018-08-04 10:40:09	ga_s2bm_ard_3-2-1_53KMQ_2018-08-04_final
2018-08-07 10:51:29	ga_s2bm_ard_3-2-1_53KMQ_2018-08-07_final
2018-08-14 10:41:41	ga_s2bm_ard_3-2-1_53KMQ_2018-08-14_final
2018-08-17 10:51:23	ga_s2bm_ard_3-2-1_53KMQ_2018-08-17_final
2018-08-24 10:41:39	ga_s2bm_ard_3-2-1_53KMQ_2018-08-24_final
2018-08-27 10:49:47	ga_s2bm_ard_3-2-1_53KMQ_2018-08-27_final
2018-09-01 09:58:07	ga_s2bm_ard_3-2-1_55KDQ_2018-09-01_final
2018-11-20 10:03:14	ga_s2bm_ard_3-2-1_55KDQ_2018-11-20_final
2019-02-08 10:03:17	ga_s2bm_ard_3-2-1_55KDQ_2019-02-08_final
2019-04-29 10:03:24	ga_s2bm_ard_3-2-1_55KDQ_2019-04-29_final
2019-05-06 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-05-06_final
2019-05-09 10:03:25	ga_s2bm_ard_3-2-1_55KDQ_2019-05-09_final
2019-05-16 09:53:30	ga_s2bm_ard_3-2-1_55KDQ_2019-05-16_final
2019-05-19 10:03:25	ga_s2bm_ard_3-2-1_55KDQ_2019-05-19_final
2019-05-26 09:53:30	ga_s2bm_ard_3-2-1_55KDQ_2019-05-26_final
2019-05-29 10:03:25	ga_s2bm_ard_3-2-1_55KDQ_2019-05-29_final
2019-06-05 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-06-05_final
2019-06-08 10:03:25	ga_s2bm_ard_3-2-1_55KDQ_2019-06-08_final
2019-06-15 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-06-15_final
2019-06-18 10:03:24	ga_s2bm_ard_3-2-1_55KDQ_2019-06-18_final
2019-06-25 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-06-25_final
2019-06-28 10:03:25	ga_s2bm_ard_3-2-1_55KDQ_2019-06-28_final
2019-07-05 09:53:30	ga_s2bm_ard_3-2-1_55KDQ_2019-07-05_final
2019-07-08 10:03:26	ga_s2bm_ard_3-2-1_55KDQ_2019-07-08_final
2019-07-15 09:53:30	ga_s2bm_ard_3-2-1_55KDQ_2019-07-15_final
2019-07-18 10:03:26	ga_s2bm_ard_3-2-1_55KDQ_2019-07-18_final
2019-07-25 09:53:30	ga_s2bm_ard_3-2-1_55KDQ_2019-07-25_final
2019-07-28 10:03:25	ga_s2bm_ard_3-2-1_55KDQ_2019-07-28_final
2019-08-04 09:53:29	ga_s2bm_ard_3-2-1_55KDQ_2019-08-04_final
2019-08-07 10:03:24	ga_s2bm_ard_3-2-1_55KDQ_2019-08-07_final
2019-08-14 09:53:28	ga_s2bm_ard_3-2-1_55KDQ_2019-08-14_final
2019-08-17 10:03:23	ga_s2bm_ard_3-2-1_55KDQ_2019-08-17_final
2019-08-24 09:53:26	ga_s2bm_ard_3-2-1_55KDQ_2019-08-24_final
2019-08-27 10:03:21	ga_s2bm_ard_3-2-1_55KDQ_2019-08-27_final
2019-09-03 09:53:24	ga_s2bm_ard_3-2-1_55KDQ_2019-09-03_final
2019-09-06 10:03:19	ga_s2bm_ard_3-2-1_55KDQ_2019-09-06_final
2019-09-13 09:53:22	ga_s2bm_ard_3-2-1_55KDQ_2019-09-13_final
2019-09-16 10:03:17	ga_s2bm_ard_3-2-1_55KDQ_2019-09-16_final
2019-09-23 09:53:21	ga_s2bm_ard_3-2-1_55KDQ_2019-09-23_final
2019-09-26 10:03:17	ga_s2bm_ard_3-2-1_55KDQ_2019-09-26_final
2019-10-03 09:53:22	ga_s2bm_ard_3-2-1_55KDQ_2019-10-03_final
2019-10-06 10:03:18	ga_s2bm_ard_3-2-1_55KDQ_2019-10-06_final
2019-10-13 09:53:22	ga_s2bm_ard_3-2-1_55KDQ_2019-10-13_final
2019-10-16 10:03:18	ga_s2bm_ard_3-2-1_55KDQ_2019-10-16_final
2019-10-23 09:53:22	ga_s2bm_ard_3-2-1_55KDQ_2019-10-23_final
2019-10-26 10:03:18	ga_s2bm_ard_3-2-1_55KDQ_2019-10-26_final
2019-11-02 09:53:22	ga_s2bm_ard_3-2-1_55KDQ_2019-11-02_final
2019-11-05 10:03:17	ga_s2bm_ard_3-2-1_55KDQ_2019-11-05_final
2019-11-12 09:53:20	ga_s2bm_ard_3-2-1_55KDQ_2019-11-12_final
2019-11-15 10:03:16	ga_s2bm_ard_3-2-1_55KDQ_2019-11-15_final
2019-11-22 09:53:19	ga_s2bm_ard_3-2-1_55KDQ_2019-11-22_final
2019-11-25 10:03:13	ga_s2bm_ard_3-2-1_55KDQ_2019-11-25_final
2019-12-02 09:53:16	ga_s2bm_ard_3-2-1_55KDQ_2019-12-02_final
2019-12-05 10:03:11	ga_s2bm_ard_3-2-1_55KDQ_2019-12-05_final
2019-12-12 09:53:16	ga_s2bm_ard_3-2-1_55KDQ_2019-12-12_final
2019-12-15 10:03:11	ga_s2bm_ard_3-2-1_55KDQ_2019-12-15_final
2019-12-22 09:53:16	ga_s2bm_ard_3-2-1_55KDQ_2019-12-22_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