Search ga_s2bm_ard_3 across 2022

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
2022-01-04 09:34:07	ga_s2bm_ard_3-2-1_56JLR_2022-01-04_final
2022-01-06 11:54:58	ga_s2bm_ard_3-2-1_50JPR_2022-01-06_final
2022-01-14 09:34:07	ga_s2bm_ard_3-2-1_56JLR_2022-01-14_final
2022-01-16 11:54:58	ga_s2bm_ard_3-2-1_50JPR_2022-01-16_final
2022-01-24 09:34:06	ga_s2bm_ard_3-2-1_56JLR_2022-01-24_final
2022-01-26 11:54:57	ga_s2bm_ard_3-2-1_50JPR_2022-01-26_final
2022-02-03 09:34:06	ga_s2bm_ard_3-2-1_56JLR_2022-02-03_final
2022-02-05 11:54:57	ga_s2bm_ard_3-2-1_50JPR_2022-02-05_final
2022-02-13 09:34:05	ga_s2bm_ard_3-2-1_56JLR_2022-02-13_final
2022-02-15 11:54:56	ga_s2bm_ard_3-2-1_50JPR_2022-02-15_final
2022-02-23 09:34:06	ga_s2bm_ard_3-2-1_56JLR_2022-02-23_final
2022-02-25 11:54:58	ga_s2bm_ard_3-2-1_50JPR_2022-02-25_final
2022-03-05 09:34:08	ga_s2bm_ard_3-2-1_56JLR_2022-03-05_final
2022-03-07 11:55:00	ga_s2bm_ard_3-2-1_50JPR_2022-03-07_final
2022-03-15 09:34:09	ga_s2bm_ard_3-2-1_56JLR_2022-03-15_final
2022-03-17 11:55:00	ga_s2bm_ard_3-2-1_50JPR_2022-03-17_final
2022-03-25 09:34:09	ga_s2bm_ard_3-2-1_56JLR_2022-03-25_final
2022-03-27 11:55:00	ga_s2bm_ard_3-2-1_50JPR_2022-03-27_final
2022-04-04 09:34:08	ga_s2bm_ard_3-2-1_56JLR_2022-04-04_final
2022-04-06 11:54:59	ga_s2bm_ard_3-2-1_50JPR_2022-04-06_final
2022-04-14 09:34:08	ga_s2bm_ard_3-2-1_56JLR_2022-04-14_final
2022-04-16 11:54:59	ga_s2bm_ard_3-2-1_50JPR_2022-04-16_final
2022-04-24 09:34:06	ga_s2bm_ard_3-2-1_56JLR_2022-04-24_final
2022-04-26 11:54:56	ga_s2bm_ard_3-2-1_50JPR_2022-04-26_final
2022-04-27 09:43:59	ga_s2bm_ard_3-2-1_56JLR_2022-04-27_final
2022-05-04 09:34:06	ga_s2bm_ard_3-2-1_56JLR_2022-05-04_final
2022-05-06 11:54:58	ga_s2bm_ard_3-2-1_50JPR_2022-05-06_final
2022-05-07 09:44:02	ga_s2bm_ard_3-2-1_56JLR_2022-05-07_final
2022-05-14 09:34:10	ga_s2bm_ard_3-2-1_56JLR_2022-05-14_final
2022-05-16 11:55:01	ga_s2bm_ard_3-2-1_50JPR_2022-05-16_final
2022-05-17 09:44:05	ga_s2bm_ard_3-2-1_56JLR_2022-05-17_final
2022-05-24 09:34:11	ga_s2bm_ard_3-2-1_56JLR_2022-05-24_final
2022-05-26 11:55:03	ga_s2bm_ard_3-2-1_50JPR_2022-05-26_final
2022-05-27 09:44:06	ga_s2bm_ard_3-2-1_56JLR_2022-05-27_final
2022-06-03 09:34:11	ga_s2bm_ard_3-2-1_56JLR_2022-06-03_final
2022-06-05 11:55:03	ga_s2bm_ard_3-2-1_50JPR_2022-06-05_final
2022-06-06 09:44:06	ga_s2bm_ard_3-2-1_56JLR_2022-06-06_final
2022-06-13 09:34:14	ga_s2bm_ard_3-2-1_56JLR_2022-06-13_final
2022-06-15 11:55:06	ga_s2bm_ard_3-2-1_50JPR_2022-06-15_final
2022-06-16 09:44:09	ga_s2bm_ard_3-2-1_56JLR_2022-06-16_final
2022-06-23 09:34:16	ga_s2bm_ard_3-2-1_56JLR_2022-06-23_final
2022-06-25 11:55:07	ga_s2bm_ard_3-2-1_50JPR_2022-06-25_final
2022-06-26 09:44:10	ga_s2bm_ard_3-2-1_56JLR_2022-06-26_final
2022-07-03 09:34:16	ga_s2bm_ard_3-2-1_56JLR_2022-07-03_final
2022-07-05 11:55:07	ga_s2bm_ard_3-2-1_50JPR_2022-07-05_final
2022-07-06 09:44:10	ga_s2bm_ard_3-2-1_56JLR_2022-07-06_final
2022-07-13 09:34:16	ga_s2bm_ard_3-2-1_56JLR_2022-07-13_final
2022-07-15 11:55:07	ga_s2bm_ard_3-2-1_50JPR_2022-07-15_final
2022-07-16 09:44:10	ga_s2bm_ard_3-2-1_56JLR_2022-07-16_final
2022-07-23 09:34:16	ga_s2bm_ard_3-2-1_56JLR_2022-07-23_final
2022-07-25 11:55:07	ga_s2bm_ard_3-2-1_50JPR_2022-07-25_final
2022-07-26 09:44:10	ga_s2bm_ard_3-2-1_56JLR_2022-07-26_final
2022-08-02 09:34:16	ga_s2bm_ard_3-2-1_56JLR_2022-08-02_final
2022-08-04 11:55:07	ga_s2bm_ard_3-2-1_50JPR_2022-08-04_final.stac-item
2022-08-05 09:44:10	ga_s2bm_ard_3-2-1_56JLR_2022-08-05_final
2022-08-11 11:45:16	ga_s2bm_ard_3-2-1_50JPR_2022-08-11_final
2022-08-12 09:34:15	ga_s2bm_ard_3-2-1_56JLR_2022-08-12_final
2022-08-14 11:55:06	ga_s2bm_ard_3-2-1_50JPR_2022-08-14_final
2022-08-15 09:44:08	ga_s2bm_ard_3-2-1_56JLR_2022-08-15_final
2022-08-22 09:34:12	ga_s2bm_ard_3-2-1_56JLR_2022-08-22_final
2022-08-24 11:55:03	ga_s2bm_ard_3-2-1_50JPR_2022-08-24_final
2022-08-25 09:44:06	ga_s2bm_ard_3-2-1_56JLR_2022-08-25_final
2022-09-01 09:34:12	ga_s2bm_ard_3-2-1_56JLR_2022-09-01_final.stac-item
2022-09-03 11:55:04	ga_s2bm_ard_3-2-1_50JPR_2022-09-03_final.stac-item
2022-09-04 09:44:07	ga_s2bm_ard_3-2-1_56JLR_2022-09-04_final.stac-item
2022-09-08 11:05:32	ga_s2bm_ard_3-2-1_52JEN_2022-09-08_final.stac-item
2022-09-11 09:34:13	ga_s2bm_ard_3-2-1_56JLR_2022-09-11_final.stac-item
2022-09-13 11:55:04	ga_s2bm_ard_3-2-1_50JPR_2022-09-13_final.stac-item
2022-09-14 09:44:08	ga_s2bm_ard_3-2-1_56JLR_2022-09-14_final.stac-item
2022-09-21 09:34:13	ga_s2bm_ard_3-2-1_56JLR_2022-09-21_final.stac-item
2022-09-23 11:55:03	ga_s2bm_ard_3-2-1_50JPR_2022-09-23_final.stac-item
2022-09-24 09:44:06	ga_s2bm_ard_3-2-1_56JLR_2022-09-24_final.stac-item
2022-09-28 11:05:31	ga_s2bm_ard_3-2-1_52JEN_2022-09-28_final.stac-item
2022-10-01 09:34:11	ga_s2bm_ard_3-2-1_56JLR_2022-10-01_final.stac-item
2022-10-03 11:55:01	ga_s2bm_ard_3-2-1_50JPR_2022-10-03_final.stac-item
2022-10-04 09:44:04	ga_s2bm_ard_3-2-1_56JLR_2022-10-04_final.stac-item
2022-10-05 10:55:32	ga_s2bm_ard_3-2-1_52JEN_2022-10-05_final.stac-item
2022-10-08 11:05:28	ga_s2bm_ard_3-2-1_52JEN_2022-10-08_final.stac-item
2022-10-11 09:34:10	ga_s2bm_ard_3-2-1_56JLR_2022-10-11_final.stac-item
2022-10-13 11:55:01	ga_s2bm_ard_3-2-1_50JPR_2022-10-13_final.stac-item
2022-10-14 09:44:01	ga_s2bm_ard_3-2-1_56JLR_2022-10-14_final.stac-item
2022-10-14 09:44:06	ga_s2bm_ard_3-2-1_56JLR_2022-10-14_final.stac-item
2022-10-18 11:05:30	ga_s2bm_ard_3-2-1_52JEN_2022-10-18_final.stac-item
2022-10-21 09:34:11	ga_s2bm_ard_3-2-1_56JLR_2022-10-21_final.stac-item
2022-10-23 11:55:02	ga_s2bm_ard_3-2-1_50JPR_2022-10-23_final.stac-item
2022-10-24 09:44:05	ga_s2bm_ard_3-2-1_56JLR_2022-10-24_final.stac-item
2022-10-25 10:55:34	ga_s2bm_ard_3-2-1_52JEN_2022-10-25_final.stac-item
2022-10-31 09:34:10	ga_s2bm_ard_3-2-1_56JLR_2022-10-31_final.stac-item
2022-11-02 11:55:00	ga_s2bm_ard_3-2-1_50JPR_2022-11-02_final.stac-item
2022-11-03 09:44:03	ga_s2bm_ard_3-2-1_56JLR_2022-11-03_final.stac-item
2022-11-10 09:34:10	ga_s2bm_ard_3-2-1_56JLR_2022-11-10_final.stac-item
2022-11-12 11:55:02	ga_s2bm_ard_3-2-1_50JPR_2022-11-12_final.stac-item
2022-11-13 09:44:05	ga_s2bm_ard_3-2-1_56JLR_2022-11-13_final.stac-item
2022-11-20 09:34:11	ga_s2bm_ard_3-2-1_56JLR_2022-11-20_final.stac-item
2022-11-22 11:55:02	ga_s2bm_ard_3-2-1_50JPR_2022-11-22_final.stac-item
2022-11-23 09:44:05	ga_s2bm_ard_3-2-1_56JLR_2022-11-23_final.stac-item
2022-11-30 09:34:10	ga_s2bm_ard_3-2-1_56JLR_2022-11-30_final.stac-item
2022-12-10 09:34:08	ga_s2bm_ard_3-2-1_56JLR_2022-12-10_final.stac-item
2022-12-20 09:34:10	ga_s2bm_ard_3-2-1_56JLR_2022-12-20_final.stac-item
2022-12-23 09:44:05	ga_s2bm_ard_3-2-1_56JLR_2022-12-23_final.stac-item

Return to ga_s2bm_ard_3 across 2022 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

2022

All months