Search ga_s2bm_ard_3 across 2019

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
2019-01-05 10:26:11	ga_s2bm_ard_3-2-1_54HUJ_2019-01-05_final
2019-02-04 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-02-04_final
2019-02-14 10:26:12	ga_s2bm_ard_3-2-1_54HUJ_2019-02-14_final
2019-02-24 10:26:11	ga_s2bm_ard_3-2-1_54HUJ_2019-02-24_final
2019-03-06 10:26:10	ga_s2bm_ard_3-2-1_54HUJ_2019-03-06_final
2019-03-16 10:26:10	ga_s2bm_ard_3-2-1_54HUJ_2019-03-16_final
2019-03-26 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-03-26_final
2019-04-05 10:26:16	ga_s2bm_ard_3-2-1_54HUJ_2019-04-05_final
2019-04-15 10:26:18	ga_s2bm_ard_3-2-1_54HUJ_2019-04-15_final
2019-04-25 10:26:19	ga_s2bm_ard_3-2-1_54HUJ_2019-04-25_final
2019-05-15 10:26:21	ga_s2bm_ard_3-2-1_54HUJ_2019-05-15_final
2019-05-25 10:26:21	ga_s2bm_ard_3-2-1_54HUJ_2019-05-25_final
2019-05-29 10:06:18	ga_s2bm_ard_3-2-1_54HXJ_2019-05-29_final
2019-05-30 09:35:56	ga_s2bm_ard_3-2-1_56HLJ_2019-05-30_final
2019-05-30 09:36:03	ga_s2bm_ard_3-2-1_56HLJ_2019-05-30_final
2019-06-01 10:16:08	ga_s2bm_ard_3-2-1_54HXJ_2019-06-01_final
2019-06-04 10:26:21	ga_s2bm_ard_3-2-1_54HUJ_2019-06-04_final
2019-06-08 10:06:18	ga_s2bm_ard_3-2-1_54HXJ_2019-06-08_final
2019-06-09 09:36:01	ga_s2bm_ard_3-2-1_56HLJ_2019-06-09_final
2019-06-11 10:16:08	ga_s2bm_ard_3-2-1_54HXJ_2019-06-11_final
2019-06-14 10:26:20	ga_s2bm_ard_3-2-1_54HUJ_2019-06-14_final
2019-06-18 10:06:18	ga_s2bm_ard_3-2-1_54HXJ_2019-06-18_final
2019-06-19 09:36:01	ga_s2bm_ard_3-2-1_56HLJ_2019-06-19_final
2019-06-21 10:16:08	ga_s2bm_ard_3-2-1_54HXJ_2019-06-21_final
2019-06-28 10:06:18	ga_s2bm_ard_3-2-1_54HXJ_2019-06-28_final
2019-06-29 09:36:02	ga_s2bm_ard_3-2-1_56HLJ_2019-06-29_final
2019-07-01 10:16:09	ga_s2bm_ard_3-2-1_54HXJ_2019-07-01_final
2019-07-08 10:06:19	ga_s2bm_ard_3-2-1_54HXJ_2019-07-08_final
2019-07-09 09:36:02	ga_s2bm_ard_3-2-1_56HLJ_2019-07-09_final
2019-07-11 10:16:09	ga_s2bm_ard_3-2-1_54HXJ_2019-07-11_final
2019-07-18 10:06:19	ga_s2bm_ard_3-2-1_54HXJ_2019-07-18_final
2019-07-19 09:36:02	ga_s2bm_ard_3-2-1_56HLJ_2019-07-19_final
2019-07-21 10:16:09	ga_s2bm_ard_3-2-1_54HXJ_2019-07-21_final
2019-07-28 10:06:18	ga_s2bm_ard_3-2-1_54HXJ_2019-07-28_final
2019-07-29 09:36:01	ga_s2bm_ard_3-2-1_56HLJ_2019-07-29_final
2019-07-31 10:16:08	ga_s2bm_ard_3-2-1_54HXJ_2019-07-31_final
2019-08-07 10:06:17	ga_s2bm_ard_3-2-1_54HXJ_2019-08-07_final
2019-08-08 09:36:00	ga_s2bm_ard_3-2-1_56HLJ_2019-08-08_final
2019-08-10 10:16:07	ga_s2bm_ard_3-2-1_54HXJ_2019-08-10_final
2019-08-13 10:26:19	ga_s2bm_ard_3-2-1_54HUJ_2019-08-13_final
2019-08-17 10:06:16	ga_s2bm_ard_3-2-1_54HXJ_2019-08-17_final
2019-08-18 09:35:59	ga_s2bm_ard_3-2-1_56HLJ_2019-08-18_final
2019-08-20 10:16:06	ga_s2bm_ard_3-2-1_54HXJ_2019-08-20_final
2019-08-23 10:26:18	ga_s2bm_ard_3-2-1_54HUJ_2019-08-23_final
2019-08-27 10:06:14	ga_s2bm_ard_3-2-1_54HXJ_2019-08-27_final
2019-08-28 09:35:57	ga_s2bm_ard_3-2-1_56HLJ_2019-08-28_final
2019-08-30 10:16:04	ga_s2bm_ard_3-2-1_54HXJ_2019-08-30_final
2019-09-06 10:06:12	ga_s2bm_ard_3-2-1_54HXJ_2019-09-06_final
2019-09-07 09:35:55	ga_s2bm_ard_3-2-1_56HLJ_2019-09-07_final
2019-09-09 10:16:02	ga_s2bm_ard_3-2-1_54HXJ_2019-09-09_final
2019-09-12 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-09-12_final
2019-09-14 09:25:56	ga_s2bm_ard_3-2-1_56HLJ_2019-09-13_final
2019-09-16 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2019-09-16_final
2019-09-17 09:35:53	ga_s2bm_ard_3-2-1_56HLJ_2019-09-17_final
2019-09-19 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2019-09-19_final
2019-09-22 10:26:12	ga_s2bm_ard_3-2-1_54HUJ_2019-09-22_final
2019-09-26 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2019-09-26_final
2019-09-27 09:35:53	ga_s2bm_ard_3-2-1_56HLJ_2019-09-27_final
2019-09-29 10:16:00	ga_s2bm_ard_3-2-1_54HXJ_2019-09-29_final
2019-10-02 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-10-02_final
2019-10-06 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2019-10-06_final
2019-10-07 09:35:54	ga_s2bm_ard_3-2-1_56HLJ_2019-10-07_final
2019-10-09 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2019-10-09_final
2019-10-12 10:26:14	ga_s2bm_ard_3-2-1_54HUJ_2019-10-12_final
2019-10-16 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2019-10-16_final
2019-10-17 09:35:54	ga_s2bm_ard_3-2-1_56HLJ_2019-10-17_final
2019-10-19 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2019-10-19_final
2019-10-22 10:26:14	ga_s2bm_ard_3-2-1_54HUJ_2019-10-22_final
2019-10-26 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2019-10-26_final
2019-10-27 09:35:54	ga_s2bm_ard_3-2-1_56HLJ_2019-10-27_final
2019-10-29 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2019-10-29_final
2019-11-01 10:26:13	ga_s2bm_ard_3-2-1_54HUJ_2019-11-01_final
2019-11-05 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2019-11-05_final
2019-11-06 09:35:53	ga_s2bm_ard_3-2-1_56HLJ_2019-11-06_final
2019-11-08 10:16:00	ga_s2bm_ard_3-2-1_54HXJ_2019-11-08_final
2019-11-11 10:26:12	ga_s2bm_ard_3-2-1_54HUJ_2019-11-11_final
2019-11-15 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2019-11-15_final
2019-11-16 09:35:52	ga_s2bm_ard_3-2-1_56HLJ_2019-11-16_final
2019-11-18 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2019-11-18_final
2019-11-21 10:26:10	ga_s2bm_ard_3-2-1_54HUJ_2019-11-21_final
2019-11-21 10:26:17	ga_s2bm_ard_3-2-1_54HUJ_2019-11-21_final
2019-11-25 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2019-11-25_final
2019-11-28 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2019-11-28_final
2019-12-01 10:26:07	ga_s2bm_ard_3-2-1_54HUJ_2019-12-01_final
2019-12-05 10:06:04	ga_s2bm_ard_3-2-1_54HXJ_2019-12-05_final
2019-12-06 09:35:47	ga_s2bm_ard_3-2-1_56HLJ_2019-12-06_final
2019-12-08 10:15:55	ga_s2bm_ard_3-2-1_54HXJ_2019-12-08_final
2019-12-11 10:26:07	ga_s2bm_ard_3-2-1_54HUJ_2019-12-11_final
2019-12-15 10:06:02	ga_s2bm_ard_3-2-1_54HXJ_2019-12-15_final
2019-12-15 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2019-12-15_final
2019-12-16 09:35:48	ga_s2bm_ard_3-2-1_56HLJ_2019-12-16_final
2019-12-18 10:15:55	ga_s2bm_ard_3-2-1_54HXJ_2019-12-18_final
2019-12-18 10:15:57	ga_s2bm_ard_3-2-1_54HXJ_2019-12-18_final
2019-12-21 10:26:07	ga_s2bm_ard_3-2-1_54HUJ_2019-12-21_final
2019-12-25 10:06:04	ga_s2bm_ard_3-2-1_54HXJ_2019-12-25_final
2019-12-25 10:06:09	ga_s2bm_ard_3-2-1_54HXH_2019-12-25_final
2019-12-25 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2019-12-25_final
2019-12-26 09:35:48	ga_s2bm_ard_3-2-1_56HLJ_2019-12-26_final
2019-12-28 10:15:55	ga_s2bm_ard_3-2-1_54HXJ_2019-12-28_final
2019-12-28 10:15:57	ga_s2bm_ard_3-2-1_54HXJ_2019-12-28_final

Return to ga_s2bm_ard_3 across 2019 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

2019

All months