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
2018-07-16 10:10:50	ga_s2bm_ard_3-2-1_54LZK_2018-07-16_final
2018-07-19 10:17:04	ga_s2bm_ard_3-2-1_54LZK_2018-07-19_final
2018-07-26 10:07:02	ga_s2bm_ard_3-2-1_54LZK_2018-07-26_final
2018-07-29 10:17:03	ga_s2bm_ard_3-2-1_54LZK_2018-07-29_final
2018-08-05 10:07:00	ga_s2bm_ard_3-2-1_54LZK_2018-08-05_final
2018-08-08 10:17:01	ga_s2bm_ard_3-2-1_54LZK_2018-08-08_final
2018-08-15 10:06:58	ga_s2bm_ard_3-2-1_54LZK_2018-08-15_final
2018-08-18 10:16:59	ga_s2bm_ard_3-2-1_54LZK_2018-08-18_final
2018-08-25 10:06:56	ga_s2bm_ard_3-2-1_54LZK_2018-08-25_final
2018-08-28 10:16:57	ga_s2bm_ard_3-2-1_54LZK_2018-08-28_final
2018-09-04 10:06:55	ga_s2bm_ard_3-2-1_54LZK_2018-09-04_final
2018-09-07 10:16:57	ga_s2bm_ard_3-2-1_54LZK_2018-09-07_final
2018-09-14 10:06:55	ga_s2bm_ard_3-2-1_54LZK_2018-09-14_final
2018-09-17 10:16:57	ga_s2bm_ard_3-2-1_54LZK_2018-09-17_final
2018-09-24 10:06:58	ga_s2bm_ard_3-2-1_54LZK_2018-09-24_final
2018-09-27 10:17:00	ga_s2bm_ard_3-2-1_54LZK_2018-09-27_final
2018-10-04 10:07:00	ga_s2bm_ard_3-2-1_54LZK_2018-10-04_final
2018-10-07 10:17:01	ga_s2bm_ard_3-2-1_54LZK_2018-10-07_final
2018-10-14 10:07:01	ga_s2bm_ard_3-2-1_54LZK_2018-10-14_final
2018-10-17 10:17:03	ga_s2bm_ard_3-2-1_54LZK_2018-10-17_final
2018-10-24 10:07:02	ga_s2bm_ard_3-2-1_54LZK_2018-10-24_final
2018-10-27 10:17:03	ga_s2bm_ard_3-2-1_54LZK_2018-10-27_final
2018-11-03 10:07:02	ga_s2bm_ard_3-2-1_54LZK_2018-11-03_final
2018-11-06 10:20:47	ga_s2bm_ard_3-2-1_54LZK_2018-11-06_final
2018-11-16 10:20:46	ga_s2bm_ard_3-2-1_54LZK_2018-11-16_final
2018-11-23 10:10:51	ga_s2bm_ard_3-2-1_54LZK_2018-11-23_final
2018-11-26 10:20:45	ga_s2bm_ard_3-2-1_54LZK_2018-11-26_final
2018-12-03 10:10:50	ga_s2bm_ard_3-2-1_54LZK_2018-12-03_final
2018-12-06 10:20:44	ga_s2bm_ard_3-2-1_54LZK_2018-12-06_final
2018-12-13 10:10:48	ga_s2bm_ard_3-2-1_54LZK_2018-12-13_final
2018-12-16 10:20:43	ga_s2bm_ard_3-2-1_54LZK_2018-12-16_final
2018-12-23 10:10:50	ga_s2bm_ard_3-2-1_54LZK_2018-12-23_final
2018-12-26 10:20:45	ga_s2bm_ard_3-2-1_54LZK_2018-12-26_final
2019-01-02 10:10:52	ga_s2bm_ard_3-2-1_54LZK_2019-01-02_final
2019-01-05 10:20:47	ga_s2bm_ard_3-2-1_54LZK_2019-01-05_final
2019-01-12 10:10:54	ga_s2bm_ard_3-2-1_54LZK_2019-01-12_final
2019-01-15 10:20:49	ga_s2bm_ard_3-2-1_54LZK_2019-01-15_final
2019-01-22 10:10:55	ga_s2bm_ard_3-2-1_54LZK_2019-01-22_final
2019-01-25 10:20:49	ga_s2bm_ard_3-2-1_54LZK_2019-01-25_final
2019-02-01 10:10:55	ga_s2bm_ard_3-2-1_54LZK_2019-02-01_final
2019-02-04 10:20:49	ga_s2bm_ard_3-2-1_54LZK_2019-02-04_final
2019-02-11 10:10:55	ga_s2bm_ard_3-2-1_54LZK_2019-02-11_final
2019-02-14 10:20:49	ga_s2bm_ard_3-2-1_54LZK_2019-02-14_final
2019-02-21 10:10:54	ga_s2bm_ard_3-2-1_54LZK_2019-02-21_final
2019-03-03 10:10:53	ga_s2bm_ard_3-2-1_54LZK_2019-03-03_final
2019-03-06 10:20:47	ga_s2bm_ard_3-2-1_54LZK_2019-03-06_final
2019-03-13 10:10:52	ga_s2bm_ard_3-2-1_54LZK_2019-03-13_final
2019-03-16 10:20:47	ga_s2bm_ard_3-2-1_54LZK_2019-03-16_final
2019-03-23 10:10:55	ga_s2bm_ard_3-2-1_54LZK_2019-03-23_final
2019-03-26 10:20:50	ga_s2bm_ard_3-2-1_54LZK_2019-03-26_final
2019-04-02 10:10:57	ga_s2bm_ard_3-2-1_54LZK_2019-04-02_final
2019-04-05 10:20:52	ga_s2bm_ard_3-2-1_54LZK_2019-04-05_final
2019-04-12 10:10:59	ga_s2bm_ard_3-2-1_54LZK_2019-04-12_final
2019-04-15 10:20:54	ga_s2bm_ard_3-2-1_54LZK_2019-04-15_final
2019-04-22 10:11:01	ga_s2bm_ard_3-2-1_54LZK_2019-04-22_final
2019-04-25 10:20:56	ga_s2bm_ard_3-2-1_54LZK_2019-04-25_final
2019-05-02 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-05-02_final
2019-05-05 10:20:57	ga_s2bm_ard_3-2-1_54LZK_2019-05-05_final
2019-05-12 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-05-12_final
2019-05-15 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-05-15_final
2019-05-22 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-05-22_final
2019-05-25 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-05-25_final
2019-06-01 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-06-01_final
2019-06-04 10:20:57	ga_s2bm_ard_3-2-1_54LZK_2019-06-04_final
2019-06-11 10:11:02	ga_s2bm_ard_3-2-1_54LZK_2019-06-11_final
2019-06-14 10:20:56	ga_s2bm_ard_3-2-1_54LZK_2019-06-14_final
2019-06-21 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-06-21_final
2019-06-24 10:20:57	ga_s2bm_ard_3-2-1_54LZK_2019-06-24_final
2019-07-01 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-07-01_final
2019-07-04 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-07-04_final
2019-07-11 10:11:04	ga_s2bm_ard_3-2-1_54LZK_2019-07-11_final
2019-07-14 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-07-14_final
2019-07-21 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-07-21_final
2019-07-24 10:20:58	ga_s2bm_ard_3-2-1_54LZK_2019-07-24_final
2019-07-31 10:11:03	ga_s2bm_ard_3-2-1_54LZK_2019-07-31_final
2019-08-03 10:20:57	ga_s2bm_ard_3-2-1_54LZK_2019-08-03_final
2019-08-10 10:11:02	ga_s2bm_ard_3-2-1_54LZK_2019-08-10_final
2019-08-13 10:20:56	ga_s2bm_ard_3-2-1_54LZK_2019-08-13_final
2019-08-20 10:11:00	ga_s2bm_ard_3-2-1_54LZK_2019-08-20_final
2019-08-23 10:20:54	ga_s2bm_ard_3-2-1_54LZK_2019-08-23_final
2019-08-30 10:10:59	ga_s2bm_ard_3-2-1_54LZK_2019-08-30_final
2019-09-02 10:20:52	ga_s2bm_ard_3-2-1_54LZK_2019-09-02_final
2019-09-09 10:10:56	ga_s2bm_ard_3-2-1_54LZK_2019-09-09_final
2019-09-12 10:20:50	ga_s2bm_ard_3-2-1_54LZK_2019-09-12_final
2019-09-19 10:10:54	ga_s2bm_ard_3-2-1_54LZK_2019-09-19_final
2019-09-22 10:20:49	ga_s2bm_ard_3-2-1_54LZK_2019-09-22_final
2019-09-29 10:10:55	ga_s2bm_ard_3-2-1_54LZK_2019-09-29_final
2019-10-09 10:10:56	ga_s2bm_ard_3-2-1_54LZK_2019-10-09_final
2019-10-12 10:20:50	ga_s2bm_ard_3-2-1_54LZK_2019-10-12_final
2019-10-19 10:10:56	ga_s2bm_ard_3-2-1_54LZK_2019-10-19_final
2019-10-22 10:20:50	ga_s2bm_ard_3-2-1_54LZK_2019-10-22_final
2019-10-29 10:10:56	ga_s2bm_ard_3-2-1_54LZK_2019-10-29_final
2019-11-01 10:20:50	ga_s2bm_ard_3-2-1_54LZK_2019-11-01_final
2019-11-08 10:10:55	ga_s2bm_ard_3-2-1_54LZK_2019-11-08_final
2019-11-11 10:20:49	ga_s2bm_ard_3-2-1_54LZK_2019-11-11_final
2019-11-18 10:10:53	ga_s2bm_ard_3-2-1_54LZK_2019-11-18_final
2019-11-21 10:20:47	ga_s2bm_ard_3-2-1_54LZK_2019-11-21_final
2019-11-28 10:10:51	ga_s2bm_ard_3-2-1_54LZK_2019-11-28_final
2020-05-06 10:10:52	ga_s2bm_ard_3-2-1_54LZK_2020-05-06_final
2020-05-29 10:20:50	ga_s2bm_ard_3-2-1_54LZK_2020-05-29_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