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
2022-04-06 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2022-04-06_final
2022-04-16 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2022-04-16_final
2022-04-26 11:55:06	ga_s2bm_ard_3-2-1_50JLR_2022-04-26_final
2022-05-06 11:55:08	ga_s2bm_ard_3-2-1_50JLR_2022-05-06_final
2022-05-16 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-05-16_final
2022-05-26 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2022-05-26_final
2022-06-05 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2022-06-05_final
2022-06-15 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2022-06-15_final
2022-06-25 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2022-06-25_final
2022-07-05 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2022-07-05_final
2022-07-14 10:44:46	ga_s2bm_ard_3-2-1_53JLL_2022-07-14_final
2022-07-15 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2022-07-15_final
2022-07-24 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2022-07-24_final
2022-07-25 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2022-07-25_final
2022-08-03 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2022-08-03_final
2022-08-04 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2022-08-04_final.stac-item
2022-08-13 10:44:45	ga_s2bm_ard_3-2-1_53JLL_2022-08-13_final
2022-08-14 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2022-08-14_final.stac-item
2022-08-23 10:44:43	ga_s2bm_ard_3-2-1_53JLL_2022-08-23_final
2022-08-24 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2022-08-24_final
2022-09-02 10:44:43	ga_s2bm_ard_3-2-1_53JLL_2022-09-02_final.stac-item
2022-09-03 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2022-09-03_final.stac-item
2022-09-12 10:44:44	ga_s2bm_ard_3-2-1_53JLL_2022-09-12_final.stac-item
2022-09-13 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2022-09-13_final.stac-item
2022-09-22 10:44:43	ga_s2bm_ard_3-2-1_53JLL_2022-09-22_final.stac-item
2022-09-23 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2022-09-23_final.stac-item
2022-10-02 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2022-10-02_final.stac-item
2022-10-03 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2022-10-03_final.stac-item
2022-10-12 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2022-10-12_final.stac-item
2022-10-13 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2022-10-13_final.stac-item
2022-10-22 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2022-10-22_final.stac-item
2022-10-23 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-10-23_final.stac-item
2022-11-01 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2022-11-01_final.stac-item
2022-11-02 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2022-11-02_final.stac-item
2022-11-02 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2022-11-02_final.stac-item
2022-11-11 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2022-11-11_final.stac-item
2022-11-12 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-11-12_final.stac-item
2022-11-21 10:44:42	ga_s2bm_ard_3-2-1_53JLL_2022-11-21_final.stac-item
2022-11-22 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-11-22_final.stac-item
2022-12-01 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2022-12-01_final.stac-item
2022-12-02 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2022-12-02_final.stac-item
2022-12-11 10:44:39	ga_s2bm_ard_3-2-1_53JLL_2022-12-11_final.stac-item
2022-12-12 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2022-12-12_final.stac-item
2022-12-21 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2022-12-21_final.stac-item
2022-12-22 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-12-22_final.stac-item
2022-12-31 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2022-12-31_final.stac-item
2023-01-01 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2023-01-01_final.stac-item
2023-01-10 10:44:39	ga_s2bm_ard_3-2-1_53JLL_2023-01-10_final.stac-item
2023-01-11 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2023-01-11_final.stac-item
2023-01-20 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2023-01-20_final.stac-item
2023-01-21 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2023-01-21_final.stac-item
2023-01-30 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2023-01-30_final.stac-item
2023-01-31 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2023-01-31_final.stac-item
2023-02-09 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2023-02-09_final.stac-item
2023-02-10 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2023-02-10_final.stac-item
2023-02-12 10:54:38	ga_s2bm_ard_3-2-1_53JLL_2023-02-12_final.stac-item
2023-02-19 10:44:41	ga_s2bm_ard_3-2-1_53JLL_2023-02-19_final.stac-item
2023-02-20 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2023-02-20_final.stac-item
2023-03-01 10:44:43	ga_s2bm_ard_3-2-1_53JLL_2023-03-01_final.stac-item
2023-03-11 10:44:46	ga_s2bm_ard_3-2-1_53JLL_2023-03-11_final.stac-item
2023-03-12 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2023-03-12_final.stac-item
2023-03-21 10:44:45	ga_s2bm_ard_3-2-1_53JLL_2023-03-21_final.stac-item
2023-03-22 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2023-03-22_final.stac-item
2023-03-31 10:44:45	ga_s2bm_ard_3-2-1_53JLL_2023-03-31_final.stac-item
2023-04-01 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2023-04-01_final.stac-item
2023-04-10 10:44:44	ga_s2bm_ard_3-2-1_53JLL_2023-04-10_final.stac-item
2023-04-11 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2023-04-11_final.stac-item
2023-04-20 10:44:44	ga_s2bm_ard_3-2-1_53JLL_2023-04-20_final.stac-item
2023-04-21 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2023-04-21_final.stac-item
2023-04-30 10:44:44	ga_s2bm_ard_3-2-1_53JLL_2023-04-30_final.stac-item
2023-05-01 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2023-05-01_final.stac-item
2023-05-10 10:44:45	ga_s2bm_ard_3-2-1_53JLL_2023-05-10_final.stac-item
2023-05-11 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2023-05-11_final.stac-item
2023-05-20 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-05-20_final.stac-item
2023-05-21 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-05-21_final.stac-item
2023-05-30 10:44:46	ga_s2bm_ard_3-2-1_53JLL_2023-05-30_final.stac-item
2023-05-30 10:44:52	ga_s2bm_ard_3-2-1_53JKL_2023-05-30_final.stac-item
2023-05-31 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2023-05-31_final.stac-item
2023-06-09 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-06-09_final.stac-item
2023-06-10 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-06-10_final.stac-item
2023-06-19 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-06-19_final.stac-item
2023-06-20 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2023-06-20_final.stac-item
2023-06-29 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-06-29_final.stac-item
2023-06-30 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-06-30_final.stac-item
2023-07-09 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-07-09_final.stac-item
2023-07-10 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-07-10_final.stac-item
2023-07-19 10:44:48	ga_s2bm_ard_3-2-1_53JLL_2023-07-19_final.stac-item
2023-07-20 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-07-20_final.stac-item
2023-07-29 10:44:48	ga_s2bm_ard_3-2-1_53JLL_2023-07-29_final.stac-item
2023-07-30 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-07-30_final.stac-item
2023-08-08 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-08-08_final.stac-item
2023-08-09 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-08-09_final.stac-item
2023-08-18 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-08-18_final.stac-item
2023-08-19 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-08-19_final.stac-item
2023-08-28 10:44:47	ga_s2bm_ard_3-2-1_53JLL_2023-08-28_final.stac-item
2023-08-29 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2023-08-29_final.stac-item
2023-09-07 10:44:46	ga_s2bm_ard_3-2-1_53JLL_2023-09-07_final.stac-item
2023-09-07 10:44:52	ga_s2bm_ard_3-2-1_53JKL_2023-09-07_final.stac-item
2023-09-17 10:44:45	ga_s2bm_ard_3-2-1_53JLL_2023-09-17_final.stac-item
2023-09-27 10:44:45	ga_s2bm_ard_3-2-1_53JLL_2023-09-27_final.stac-item

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

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