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
2021-05-27 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2021-05-27_final
2021-06-06 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2021-06-06_final
2021-06-16 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2021-06-16_final
2021-06-26 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2021-06-26_final
2021-07-06 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2021-07-06_final
2021-07-16 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2021-07-16_final
2021-07-26 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2021-07-26_final
2021-08-05 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2021-08-05_final
2021-08-15 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2021-08-15_final
2021-08-25 12:14:44	ga_s2bm_ard_3-2-1_49JFN_2021-08-25_final
2021-09-04 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2021-09-04_final
2021-09-14 12:14:41	ga_s2bm_ard_3-2-1_49JFN_2021-09-14_final
2021-09-24 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2021-09-24_final
2021-10-04 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2021-10-04_final
2021-10-14 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2021-10-14_final
2021-10-24 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2021-10-24_final
2021-10-24 12:14:49	ga_s2bm_ard_3-2-1_49JFN_2021-10-24_final
2021-11-03 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2021-11-03_final
2021-11-13 12:14:44	ga_s2bm_ard_3-2-1_49JFN_2021-11-13_final
2021-11-23 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2021-11-23_final
2021-12-03 12:14:41	ga_s2bm_ard_3-2-1_49JFN_2021-12-03_final
2021-12-13 12:14:33	ga_s2bm_ard_3-2-1_49JFN_2021-12-13_final
2021-12-13 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2021-12-13_final
2021-12-23 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2021-12-23_final
2022-01-02 12:14:41	ga_s2bm_ard_3-2-1_49JFN_2022-01-02_final
2022-01-12 12:14:41	ga_s2bm_ard_3-2-1_49JFN_2022-01-12_final
2022-01-22 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2022-01-22_final
2022-02-01 12:14:39	ga_s2bm_ard_3-2-1_49JFN_2022-02-01_final
2022-02-11 12:14:39	ga_s2bm_ard_3-2-1_49JFN_2022-02-11_final
2022-02-21 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2022-02-21_final
2022-03-03 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2022-03-03_final
2022-03-13 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2022-03-13_final
2022-03-23 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2022-03-23_final
2022-04-02 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2022-04-02_final
2022-04-12 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2022-04-12_final
2022-04-22 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2022-04-22_final
2022-05-02 12:14:40	ga_s2bm_ard_3-2-1_49JFN_2022-05-02_final
2022-05-12 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2022-05-12_final
2022-05-22 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2022-05-22_final
2022-06-01 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2022-06-01_final
2022-06-11 12:14:48	ga_s2bm_ard_3-2-1_49JFN_2022-06-11_final
2022-06-21 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2022-06-21_final
2022-07-01 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2022-07-01_final
2022-07-11 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2022-07-11_final
2022-07-21 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2022-07-21_final
2022-07-31 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2022-07-31_final
2022-08-10 12:14:49	ga_s2bm_ard_3-2-1_49JFN_2022-08-10_final
2022-08-20 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2022-08-20_final
2022-08-30 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2022-08-30_final
2022-09-09 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2022-09-09_final.stac-item
2022-09-19 12:14:47	ga_s2bm_ard_3-2-1_49JFN_2022-09-19_final.stac-item
2022-09-29 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2022-09-29_final.stac-item
2022-10-09 12:14:43	ga_s2bm_ard_3-2-1_49JFN_2022-10-09_final.stac-item
2022-10-19 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2022-10-19_final.stac-item
2022-12-18 12:14:00	ga_s2bm_ard_3-2-1_49KFR_2022-12-18_nrt.stac-item
2022-12-18 12:15:13	ga_s2bm_ard_3-2-1_49JFL_2022-12-18_nrt.stac-item
2022-12-28 12:14:01	ga_s2bm_ard_3-2-1_49KFR_2022-12-28_nrt.stac-item
2022-12-28 12:15:13	ga_s2bm_ard_3-2-1_49JFL_2022-12-28_nrt.stac-item
2023-01-07 12:13:59	ga_s2bm_ard_3-2-1_49KFR_2023-01-07_nrt.stac-item
2023-01-17 12:13:59	ga_s2bm_ard_3-2-1_49KFR_2023-01-17_nrt.stac-item
2023-01-27 12:14:00	ga_s2bm_ard_3-2-1_49KFR_2023-01-27_nrt.stac-item
2023-02-06 12:13:59	ga_s2bm_ard_3-2-1_49KFR_2023-02-06_nrt.stac-item
2023-02-16 12:14:05	ga_s2bm_ard_3-2-1_49KFR_2023-02-16_nrt.stac-item
2023-03-18 12:14:20	ga_s2bm_ard_3-2-1_49KFQ_2023-03-18_nrt.stac-item
2023-03-28 12:14:19	ga_s2bm_ard_3-2-1_49KFQ_2023-03-28_nrt.stac-item
2023-04-07 12:14:19	ga_s2bm_ard_3-2-1_49KFQ_2023-04-07_nrt.stac-item
2023-04-17 12:14:18	ga_s2bm_ard_3-2-1_49KFQ_2023-04-17_nrt.stac-item
2023-04-27 12:14:18	ga_s2bm_ard_3-2-1_49KFQ_2023-04-27_nrt.stac-item
2023-05-07 12:14:19	ga_s2bm_ard_3-2-1_49KFQ_2023-05-07_nrt.stac-item
2023-05-07 12:14:26	ga_s2bm_ard_3-2-1_49KFQ_2023-05-07_nrt.stac-item
2023-05-17 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-05-17_nrt.stac-item
2023-05-27 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-05-27_nrt.stac-item
2023-06-06 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-06-06_nrt.stac-item
2023-06-16 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-06-16_nrt.stac-item
2023-06-26 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-06-26_nrt.stac-item
2023-07-06 12:14:22	ga_s2bm_ard_3-2-1_49KFQ_2023-07-06_nrt.stac-item
2023-07-16 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-07-16_nrt.stac-item
2023-07-26 12:14:22	ga_s2bm_ard_3-2-1_49KFQ_2023-07-26_nrt.stac-item
2023-08-05 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-08-05_nrt.stac-item
2023-08-15 12:14:22	ga_s2bm_ard_3-2-1_49KFQ_2023-08-15_nrt.stac-item
2023-08-25 12:14:20	ga_s2bm_ard_3-2-1_49KFQ_2023-08-25_nrt.stac-item
2023-09-04 12:14:21	ga_s2bm_ard_3-2-1_49KFQ_2023-09-04_nrt.stac-item
2023-09-14 12:14:19	ga_s2bm_ard_3-2-1_49KFQ_2023-09-14_nrt.stac-item
2023-09-24 12:14:20	ga_s2bm_ard_3-2-1_49KFQ_2023-09-24_nrt.stac-item
2023-10-04 12:14:17	ga_s2bm_ard_3-2-1_49KFQ_2023-10-04_nrt.stac-item
2023-10-14 12:14:18	ga_s2bm_ard_3-2-1_49KFQ_2023-10-14_nrt.stac-item
2023-10-24 12:14:15	ga_s2bm_ard_3-2-1_49KFQ_2023-10-24_nrt.stac-item
2023-10-24 12:14:22	ga_s2bm_ard_3-2-1_49KFQ_2023-10-24_nrt.stac-item
2023-11-03 12:14:19	ga_s2bm_ard_3-2-1_49KFQ_2023-11-03_nrt.stac-item
2023-11-13 12:14:17	ga_s2bm_ard_3-2-1_49KFQ_2023-11-13_nrt.stac-item
2023-11-23 12:14:11	ga_s2bm_ard_3-2-1_49KFQ_2023-11-23_nrt.stac-item
2023-12-03 12:14:13	ga_s2bm_ard_3-2-1_49KFQ_2023-12-03_nrt.stac-item
2023-12-13 12:14:14	ga_s2bm_ard_3-2-1_49KFQ_2023-12-13_nrt.stac-item
2023-12-23 12:14:17	ga_s2bm_ard_3-2-1_49KFQ_2023-12-23_nrt.stac-item
2024-01-02 12:14:17	ga_s2bm_ard_3-2-1_49KFQ_2024-01-02_nrt.stac-item
2024-01-12 12:14:14	ga_s2bm_ard_3-2-1_49KFQ_2024-01-12_nrt.stac-item
2024-01-22 12:14:15	ga_s2bm_ard_3-2-1_49KFQ_2024-01-22_nrt.stac-item
2024-02-01 12:14:13	ga_s2bm_ard_3-2-1_49KFQ_2024-02-01_nrt.stac-item
2024-02-11 12:14:17	ga_s2bm_ard_3-2-1_49KFQ_2024-02-11_nrt.stac-item
2024-02-21 12:14:09	ga_s2bm_ard_3-2-1_49KFQ_2024-02-21_nrt.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

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