Search ga_s2bm_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-07-06 11:02:11	ga_s2bm_ard_3-2-1_52KFA_2017-07-06_final.stac-item
2017-07-16 10:58:39	ga_s2bm_ard_3-2-1_52KFA_2017-07-16_final.stac-item
2017-07-26 11:02:11	ga_s2bm_ard_3-2-1_52KFA_2017-07-26_final.stac-item
2017-09-24 11:01:57	ga_s2bm_ard_3-2-1_52KFA_2017-09-24_final.stac-item
2017-10-04 11:02:43	ga_s2bm_ard_3-2-1_52KFA_2017-10-04_final.stac-item
2017-10-14 11:01:57	ga_s2bm_ard_3-2-1_52KFA_2017-10-14_final.stac-item
2017-10-24 11:02:45	ga_s2bm_ard_3-2-1_52KFA_2017-10-24_final.stac-item
2017-11-13 11:02:45	ga_s2bm_ard_3-2-1_52KFA_2017-11-13_final.stac-item
2017-11-23 11:02:50	ga_s2bm_ard_3-2-1_52KFA_2017-11-23_final.stac-item
2017-12-13 10:57:04	ga_s2bm_ard_3-2-1_52KFA_2017-12-13_final.stac-item
2017-12-23 11:02:47	ga_s2bm_ard_3-2-1_52KFA_2017-12-23_final.stac-item
2018-01-02 10:57:06	ga_s2bm_ard_3-2-1_52KFA_2018-01-02_final.stac-item
2018-01-12 11:02:50	ga_s2bm_ard_3-2-1_52KFA_2018-01-12_final.stac-item
2018-01-22 10:57:08	ga_s2bm_ard_3-2-1_52KFA_2018-01-22_final.stac-item
2018-02-01 11:02:52	ga_s2bm_ard_3-2-1_52KFA_2018-02-01_final.stac-item
2018-02-21 11:02:40	ga_s2bm_ard_3-2-1_52KFA_2018-02-21_final.stac-item
2018-03-23 10:57:10	ga_s2bm_ard_3-2-1_52KFA_2018-03-23_final.stac-item
2018-04-02 10:57:12	ga_s2bm_ard_3-2-1_52KFA_2018-04-02_final.stac-item
2018-04-12 10:57:13	ga_s2bm_ard_3-2-1_52KFA_2018-04-12_final.stac-item
2018-05-02 11:00:12	ga_s2bm_ard_3-2-1_52KFA_2018-05-02_final.stac-item
2018-05-12 11:01:55	ga_s2bm_ard_3-2-1_52KFA_2018-05-12_final.stac-item
2018-05-22 10:57:13	ga_s2bm_ard_3-2-1_52KFA_2018-05-22_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KFA_2018-06-11_final.stac-item
2018-07-01 10:57:40	ga_s2bm_ard_3-2-1_52KFA_2018-07-01_final.stac-item
2018-07-21 11:01:52	ga_s2bm_ard_3-2-1_52KFA_2018-07-21_final.stac-item
2021-02-15 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2021-02-15_final.stac-item
2021-02-25 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2021-02-25_final.stac-item
2021-03-07 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2021-03-07_final.stac-item
2021-03-17 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2021-03-17_final.stac-item
2021-03-27 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2021-03-27_final.stac-item
2021-04-06 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2021-04-06_final.stac-item
2021-04-16 11:03:27	ga_s2bm_ard_3-2-1_52KFA_2021-04-16_final.stac-item
2021-04-26 11:03:26	ga_s2bm_ard_3-2-1_52KFA_2021-04-26_final.stac-item
2021-05-06 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2021-05-06_final.stac-item
2021-05-26 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2021-05-26_final.stac-item
2021-06-15 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2021-06-15_final.stac-item
2021-06-25 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2021-06-25_final.stac-item
2021-07-05 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2021-07-05_final.stac-item
2021-07-15 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2021-07-15_final.stac-item
2021-07-25 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2021-07-25_final.stac-item
2021-08-04 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2021-08-04_final.stac-item
2021-09-03 11:03:27	ga_s2bm_ard_3-2-1_52KFA_2021-09-03_final.stac-item
2021-09-13 11:03:27	ga_s2bm_ard_3-2-1_52KFA_2021-09-13_final.stac-item
2021-09-23 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2021-09-23_final.stac-item
2021-10-03 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2021-10-03_final.stac-item
2021-10-13 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2021-10-13_final.stac-item
2021-10-23 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2021-10-23_final.stac-item
2021-11-02 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2021-11-02_final.stac-item
2021-11-12 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2021-11-12_final.stac-item
2021-11-22 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2021-11-22_final.stac-item
2021-12-12 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2021-12-12_final.stac-item
2021-12-22 11:03:26	ga_s2bm_ard_3-2-1_52KFA_2021-12-22_final.stac-item
2022-01-01 11:03:27	ga_s2bm_ard_3-2-1_52KFA_2022-01-01_final.stac-item
2022-01-11 11:03:27	ga_s2bm_ard_3-2-1_52KFA_2022-01-11_final.stac-item
2022-01-21 11:03:26	ga_s2bm_ard_3-2-1_52KFA_2022-01-21_final.stac-item
2022-01-31 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2022-01-31_final.stac-item
2022-02-10 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2022-02-10_final.stac-item
2022-02-20 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2022-02-20_final.stac-item
2022-03-02 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2022-03-02_final.stac-item
2022-03-12 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2022-03-12_final.stac-item
2022-03-22 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2022-03-22_final.stac-item
2022-04-01 11:03:27	ga_s2bm_ard_3-2-1_52KFA_2022-04-01_final.stac-item
2022-04-11 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2022-04-11_final.stac-item
2022-04-21 11:03:26	ga_s2bm_ard_3-2-1_52KFA_2022-04-21_final.stac-item
2022-05-01 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2022-05-01_final.stac-item
2022-05-11 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2022-05-11_final.stac-item
2022-05-21 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2022-05-21_final.stac-item
2022-05-31 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2022-05-31_final.stac-item
2022-06-10 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2022-06-10_final.stac-item
2022-06-20 11:03:35	ga_s2bm_ard_3-2-1_52KFA_2022-06-20_final.stac-item
2022-06-30 11:03:36	ga_s2bm_ard_3-2-1_52KFA_2022-06-30_final.stac-item
2022-07-10 11:03:36	ga_s2bm_ard_3-2-1_52KFA_2022-07-10_final.stac-item
2022-07-20 11:03:36	ga_s2bm_ard_3-2-1_52KFA_2022-07-20_final.stac-item
2022-07-30 11:03:36	ga_s2bm_ard_3-2-1_52KFA_2022-07-30_final.stac-item
2022-08-09 11:03:35	ga_s2bm_ard_3-2-1_52KFA_2022-08-09_final.stac-item
2022-08-19 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2022-08-19_final.stac-item
2022-08-29 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2022-08-29_final.stac-item
2022-09-08 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2022-09-08_final.stac-item
2022-09-18 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2022-09-18_final.stac-item
2022-09-28 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2022-09-28_final.stac-item
2022-10-08 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2022-10-08_final.stac-item
2022-10-18 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2022-10-18_final.stac-item
2022-10-28 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2022-10-28_final.stac-item
2022-10-28 11:03:34	ga_s2bm_ard_3-2-1_52KFA_2022-10-28_final.stac-item
2022-11-07 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2022-11-07_final.stac-item
2022-11-17 11:03:31	ga_s2bm_ard_3-2-1_52KFA_2022-11-17_final.stac-item
2022-11-27 11:03:30	ga_s2bm_ard_3-2-1_52KFA_2022-11-27_final.stac-item
2022-12-07 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2022-12-07_final.stac-item
2022-12-17 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2022-12-17_final.stac-item
2022-12-17 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2022-12-17_final.stac-item
2022-12-27 11:03:26	ga_s2bm_ard_3-2-1_52KFA_2022-12-27_final.stac-item
2022-12-27 11:03:33	ga_s2bm_ard_3-2-1_52KFA_2022-12-27_final.stac-item
2023-01-06 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2023-01-06_final.stac-item
2023-01-16 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2023-01-16_final.stac-item
2023-01-26 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2023-01-26_final.stac-item
2023-02-05 11:03:28	ga_s2bm_ard_3-2-1_52KFA_2023-02-05_final
2023-02-15 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2023-02-15_final
2023-08-04 11:03:36	ga_s2bm_ard_3-2-1_52KFA_2023-08-04_final
2023-08-14 11:03:37	ga_s2bm_ard_3-2-1_52KFA_2023-08-14_final
2023-08-24 11:03:35	ga_s2bm_ard_3-2-1_52KFA_2023-08-24_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years