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
2017-06-30 10:43:28	ga_s2bm_ard_3-2-1_53JNK_2017-06-30_final
2017-07-07 10:32:11	ga_s2bm_ard_3-2-1_53JNK_2017-07-07_final
2017-07-20 10:43:06	ga_s2bm_ard_3-2-1_53JNK_2017-07-20_final
2017-07-27 10:32:10	ga_s2bm_ard_3-2-1_53JNK_2017-07-27_final
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JNK_2017-08-09_final
2017-08-16 10:32:08	ga_s2bm_ard_3-2-1_53JNK_2017-08-16_final
2017-09-05 10:32:04	ga_s2bm_ard_3-2-1_53JNK_2017-09-05_final
2017-09-18 10:42:55	ga_s2bm_ard_3-2-1_53JNK_2017-09-18_final
2017-09-25 10:31:57	ga_s2bm_ard_3-2-1_53JNK_2017-09-25_final
2017-10-08 10:42:51	ga_s2bm_ard_3-2-1_53JNK_2017-10-08_final
2017-10-15 10:31:57	ga_s2bm_ard_3-2-1_53JNK_2017-10-15_final
2017-10-28 10:42:53	ga_s2bm_ard_3-2-1_53JNK_2017-10-28_final
2017-11-04 10:32:19	ga_s2bm_ard_3-2-1_53JNK_2017-11-04_final
2017-11-07 10:37:13	ga_s2bm_ard_3-2-1_53JNK_2017-11-07_final
2017-11-14 10:26:54	ga_s2bm_ard_3-2-1_53JNK_2017-11-14_final
2017-11-17 10:42:53	ga_s2bm_ard_3-2-1_53JNK_2017-11-17_final
2017-11-24 10:32:21	ga_s2bm_ard_3-2-1_53JNK_2017-11-24_final
2017-11-27 10:37:15	ga_s2bm_ard_3-2-1_53JNK_2017-11-27_final
2017-12-07 10:42:54	ga_s2bm_ard_3-2-1_53JNK_2017-12-07_final
2017-12-14 10:32:21	ga_s2bm_ard_3-2-1_53JNK_2017-12-14_final
2017-12-17 10:37:15	ga_s2bm_ard_3-2-1_53JNK_2017-12-17_final
2017-12-24 10:26:56	ga_s2bm_ard_3-2-1_53JNK_2017-12-24_final
2017-12-27 10:42:55	ga_s2bm_ard_3-2-1_53JNK_2017-12-27_final
2018-01-03 10:32:23	ga_s2bm_ard_3-2-1_53JNK_2018-01-03_final
2018-01-06 10:37:18	ga_s2bm_ard_3-2-1_53JNK_2018-01-06_final
2018-01-13 10:27:00	ga_s2bm_ard_3-2-1_53JNK_2018-01-13_final
2018-01-16 10:42:58	ga_s2bm_ard_3-2-1_53JNK_2018-01-16_final
2018-01-23 10:32:25	ga_s2bm_ard_3-2-1_53JNK_2018-01-23_final
2018-01-26 10:37:20	ga_s2bm_ard_3-2-1_53JNK_2018-01-26_final
2018-02-02 10:27:01	ga_s2bm_ard_3-2-1_53JNK_2018-02-02_final
2018-02-05 10:42:59	ga_s2bm_ard_3-2-1_53JNK_2018-02-05_final
2018-02-12 10:31:32	ga_s2bm_ard_3-2-1_53JNK_2018-02-12_final
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JNK_2018-02-15_final
2018-02-22 10:27:00	ga_s2bm_ard_3-2-1_53JNK_2018-02-22_final
2018-02-25 10:42:58	ga_s2bm_ard_3-2-1_53JNK_2018-02-25_final
2018-03-04 10:26:58	ga_s2bm_ard_3-2-1_53JNK_2018-03-04_final
2018-03-07 10:37:17	ga_s2bm_ard_3-2-1_53JNK_2018-03-07_final
2018-03-14 10:27:00	ga_s2bm_ard_3-2-1_53JNK_2018-03-14_final
2018-03-17 10:37:20	ga_s2bm_ard_3-2-1_53JNK_2018-03-17_final
2018-03-24 10:27:02	ga_s2bm_ard_3-2-1_53JNK_2018-03-24_final
2018-03-27 10:37:22	ga_s2bm_ard_3-2-1_53JNK_2018-03-27_final
2018-04-03 10:27:04	ga_s2bm_ard_3-2-1_53JNK_2018-04-03_final
2018-04-06 10:37:24	ga_s2bm_ard_3-2-1_53JNK_2018-04-06_final
2018-04-13 10:27:05	ga_s2bm_ard_3-2-1_53JNK_2018-04-13_final
2018-04-16 10:37:25	ga_s2bm_ard_3-2-1_53JNK_2018-04-16_final
2018-04-23 10:27:06	ga_s2bm_ard_3-2-1_53JNK_2018-04-23_final
2018-04-26 10:37:26	ga_s2bm_ard_3-2-1_53JNK_2018-04-26_final
2018-05-03 10:27:07	ga_s2bm_ard_3-2-1_53JNK_2018-05-03_final
2018-05-06 10:37:26	ga_s2bm_ard_3-2-1_53JNK_2018-05-06_final
2018-05-13 10:30:42	ga_s2bm_ard_3-2-1_53JNK_2018-05-13_final
2018-05-16 10:37:25	ga_s2bm_ard_3-2-1_53JNK_2018-05-16_final
2018-05-23 10:32:01	ga_s2bm_ard_3-2-1_53JNK_2018-05-23_final
2018-05-26 10:43:10	ga_s2bm_ard_3-2-1_53JNK_2018-05-26_final
2018-06-02 10:34:28	ga_s2bm_ard_3-2-1_53JNK_2018-06-02_final
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53JNK_2018-06-05_final
2018-06-12 10:33:10	ga_s2bm_ard_3-2-1_53JNK_2018-06-12_final
2018-06-15 10:37:25	ga_s2bm_ard_3-2-1_53JNK_2018-06-15_final
2018-06-22 10:34:30	ga_s2bm_ard_3-2-1_53JNK_2018-06-22_final
2018-06-25 10:42:47	ga_s2bm_ard_3-2-1_53JNK_2018-06-25_final
2018-07-02 10:31:05	ga_s2bm_ard_3-2-1_53JNK_2018-07-02_final
2018-07-05 10:40:12	ga_s2bm_ard_3-2-1_53JNK_2018-07-05_final
2018-07-12 10:29:34	ga_s2bm_ard_3-2-1_53JNK_2018-07-12_final
2018-07-15 10:41:45	ga_s2bm_ard_3-2-1_53JNK_2018-07-15_final
2018-07-22 10:31:03	ga_s2bm_ard_3-2-1_53JNK_2018-07-22_final
2018-07-25 10:41:04	ga_s2bm_ard_3-2-1_53JNK_2018-07-25_final
2018-08-01 10:31:02	ga_s2bm_ard_3-2-1_53JNK_2018-08-01_final
2018-08-04 10:40:09	ga_s2bm_ard_3-2-1_53JNK_2018-08-04_final
2018-08-11 10:29:56	ga_s2bm_ard_3-2-1_53JNK_2018-08-11_final
2018-08-24 10:41:39	ga_s2bm_ard_3-2-1_53JNK_2018-08-24_final
2018-09-03 10:40:04	ga_s2bm_ard_3-2-1_53JNK_2018-09-03_final
2022-01-04 11:14:56	ga_s2bm_ard_3-2-1_52JDQ_2022-01-04_final
2022-01-11 11:05:01	ga_s2bm_ard_3-2-1_52JDQ_2022-01-11_final
2022-01-14 11:14:56	ga_s2bm_ard_3-2-1_52JDQ_2022-01-14_final
2022-01-21 11:05:00	ga_s2bm_ard_3-2-1_52JDQ_2022-01-21_final
2022-01-24 11:14:54	ga_s2bm_ard_3-2-1_52JDQ_2022-01-24_final
2022-01-31 11:04:59	ga_s2bm_ard_3-2-1_52JDQ_2022-01-31_final
2022-02-03 11:14:54	ga_s2bm_ard_3-2-1_52JDQ_2022-02-03_final
2022-02-10 11:04:59	ga_s2bm_ard_3-2-1_52JDQ_2022-02-10_final
2022-02-13 11:14:54	ga_s2bm_ard_3-2-1_52JDQ_2022-02-13_final
2022-02-20 11:04:59	ga_s2bm_ard_3-2-1_52JDQ_2022-02-20_final
2022-03-22 11:05:03	ga_s2bm_ard_3-2-1_52JDQ_2022-03-22_final
2022-03-25 11:14:57	ga_s2bm_ard_3-2-1_52JDQ_2022-03-25_final
2022-04-01 11:05:01	ga_s2bm_ard_3-2-1_52JDQ_2022-04-01_final
2022-04-11 11:05:01	ga_s2bm_ard_3-2-1_52JDQ_2022-04-11_final
2022-04-21 11:05:00	ga_s2bm_ard_3-2-1_52JDQ_2022-04-21_final
2022-04-24 11:14:54	ga_s2bm_ard_3-2-1_52JDQ_2022-04-24_final
2022-05-01 11:04:59	ga_s2bm_ard_3-2-1_52JDQ_2022-05-01_final
2022-05-04 11:14:55	ga_s2bm_ard_3-2-1_52JDQ_2022-05-04_final
2022-05-21 11:05:05	ga_s2bm_ard_3-2-1_52JDQ_2022-05-21_final
2022-05-31 11:05:05	ga_s2bm_ard_3-2-1_52JDQ_2022-05-31_final
2022-06-10 11:05:07	ga_s2bm_ard_3-2-1_52JDQ_2022-06-10_final
2022-06-20 11:05:09	ga_s2bm_ard_3-2-1_52JDQ_2022-06-20_final
2022-06-30 11:05:10	ga_s2bm_ard_3-2-1_52JDQ_2022-06-30_final
2022-07-10 11:05:09	ga_s2bm_ard_3-2-1_52JDQ_2022-07-10_final
2022-07-20 11:05:10	ga_s2bm_ard_3-2-1_52JDQ_2022-07-20_final
2022-07-30 11:05:10	ga_s2bm_ard_3-2-1_52JDQ_2022-07-30_final
2022-08-09 11:05:09	ga_s2bm_ard_3-2-1_52JDQ_2022-08-09_final
2022-08-12 11:15:03	ga_s2bm_ard_3-2-1_52JDQ_2022-08-12_final
2022-08-19 11:05:07	ga_s2bm_ard_3-2-1_52JDQ_2022-08-19_final
2022-08-22 11:15:01	ga_s2bm_ard_3-2-1_52JDQ_2022-08-22_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