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
2021-11-06 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2021-11-06_final.stac-item
2021-11-19 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2021-11-19_final.stac-item
2021-12-06 10:44:08	ga_s2bm_ard_3-2-1_53JLN_2021-12-06_final.stac-item
2021-12-09 10:54:03	ga_s2bm_ard_3-2-1_53JLN_2021-12-09_final.stac-item
2021-12-16 10:44:06	ga_s2bm_ard_3-2-1_53JLN_2021-12-16_final.stac-item
2021-12-29 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2021-12-29_final.stac-item
2022-01-08 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2022-01-08_final.stac-item
2022-01-15 10:44:08	ga_s2bm_ard_3-2-1_53JLN_2022-01-15_final.stac-item
2022-01-18 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2022-01-18_final.stac-item
2022-01-25 10:44:07	ga_s2bm_ard_3-2-1_53JLN_2022-01-25_final.stac-item
2022-02-07 10:54:03	ga_s2bm_ard_3-2-1_53JLN_2022-02-07_final.stac-item
2022-02-24 10:44:08	ga_s2bm_ard_3-2-1_53JLN_2022-02-24_final.stac-item
2022-02-27 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2022-02-27_final.stac-item
2022-03-06 10:44:10	ga_s2bm_ard_3-2-1_53JLN_2022-03-06_final.stac-item
2022-03-09 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2022-03-09_final.stac-item
2022-03-16 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2022-03-16_final.stac-item
2022-03-19 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2022-03-19_final.stac-item
2022-03-26 10:44:10	ga_s2bm_ard_3-2-1_53JLN_2022-03-26_final.stac-item
2022-04-05 10:44:09	ga_s2bm_ard_3-2-1_53JLN_2022-04-05_final.stac-item
2022-04-08 10:54:05	ga_s2bm_ard_3-2-1_53JLN_2022-04-08_final.stac-item
2022-04-15 10:44:09	ga_s2bm_ard_3-2-1_53JLN_2022-04-15_final.stac-item
2022-04-18 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2022-04-18_final.stac-item
2022-04-25 10:44:07	ga_s2bm_ard_3-2-1_53JLN_2022-04-25_final.stac-item
2022-05-05 10:44:08	ga_s2bm_ard_3-2-1_53JLN_2022-05-05_final.stac-item
2022-05-08 10:54:05	ga_s2bm_ard_3-2-1_53JLN_2022-05-08_final.stac-item
2022-05-15 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2022-05-15_final.stac-item
2022-05-25 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2022-05-25_final.stac-item
2022-05-28 10:54:08	ga_s2bm_ard_3-2-1_53JLN_2022-05-28_final.stac-item
2022-06-04 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2022-06-04_final.stac-item
2022-06-07 10:54:09	ga_s2bm_ard_3-2-1_53JLN_2022-06-07_final.stac-item
2022-06-14 10:44:16	ga_s2bm_ard_3-2-1_53JLN_2022-06-14_final.stac-item
2022-06-17 10:54:12	ga_s2bm_ard_3-2-1_53JLN_2022-06-17_final.stac-item
2022-06-17 10:54:19	ga_s2bm_ard_3-2-1_53JLN_2022-06-17_final.stac-item
2022-06-24 10:44:17	ga_s2bm_ard_3-2-1_53JLN_2022-06-24_final.stac-item
2022-06-27 10:54:13	ga_s2bm_ard_3-2-1_53JLN_2022-06-27_final.stac-item
2022-06-27 10:54:20	ga_s2bm_ard_3-2-1_53JLN_2022-06-27_final.stac-item
2022-07-04 10:44:18	ga_s2bm_ard_3-2-1_53JLN_2022-07-04_final.stac-item
2022-07-07 10:54:13	ga_s2bm_ard_3-2-1_53JLN_2022-07-07_final.stac-item
2022-07-07 10:54:20	ga_s2bm_ard_3-2-1_53JLN_2022-07-07_final.stac-item
2022-07-14 10:44:17	ga_s2bm_ard_3-2-1_53JLN_2022-07-14_final.stac-item
2022-07-17 10:54:12	ga_s2bm_ard_3-2-1_53JLN_2022-07-17_final.stac-item
2022-07-17 10:54:19	ga_s2bm_ard_3-2-1_53JLN_2022-07-17_final.stac-item
2022-07-24 10:44:18	ga_s2bm_ard_3-2-1_53JLN_2022-07-24_final.stac-item
2022-07-27 10:54:13	ga_s2bm_ard_3-2-1_53JLN_2022-07-27_final.stac-item
2022-08-03 10:44:17	ga_s2bm_ard_3-2-1_53JLN_2022-08-03_final.stac-item
2022-08-06 10:54:12	ga_s2bm_ard_3-2-1_53JLN_2022-08-06_final.stac-item
2022-08-06 10:54:19	ga_s2bm_ard_3-2-1_53JLN_2022-08-06_final.stac-item
2022-08-13 10:44:16	ga_s2bm_ard_3-2-1_53JLN_2022-08-13_final.stac-item
2022-08-16 10:54:10	ga_s2bm_ard_3-2-1_53JLN_2022-08-16_final.stac-item
2022-08-16 10:54:17	ga_s2bm_ard_3-2-1_53JLN_2022-08-16_final.stac-item
2022-08-23 10:44:13	ga_s2bm_ard_3-2-1_53JLN_2022-08-23_final.stac-item
2022-08-26 10:54:08	ga_s2bm_ard_3-2-1_53JLN_2022-08-26_final.stac-item
2022-09-02 10:44:14	ga_s2bm_ard_3-2-1_53JLN_2022-09-02_final.stac-item
2022-09-05 10:54:10	ga_s2bm_ard_3-2-1_53JLN_2022-09-05_final.stac-item
2022-09-05 10:54:18	ga_s2bm_ard_3-2-1_53JLN_2022-09-05_final.stac-item
2022-09-12 10:44:15	ga_s2bm_ard_3-2-1_53JLN_2022-09-12_final.stac-item
2022-09-15 10:54:10	ga_s2bm_ard_3-2-1_53JLN_2022-09-15_final.stac-item
2022-09-15 10:54:17	ga_s2bm_ard_3-2-1_53JLN_2022-09-15_final.stac-item
2022-09-22 10:44:14	ga_s2bm_ard_3-2-1_53JLN_2022-09-22_final.stac-item
2022-09-25 10:54:09	ga_s2bm_ard_3-2-1_53JLN_2022-09-25_final.stac-item
2022-09-25 10:54:16	ga_s2bm_ard_3-2-1_53JLN_2022-09-25_final.stac-item
2022-10-02 10:44:12	ga_s2bm_ard_3-2-1_53JLN_2022-10-02_final.stac-item
2022-10-05 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2022-10-05_final.stac-item
2022-10-05 10:54:13	ga_s2bm_ard_3-2-1_53JLN_2022-10-05_final.stac-item
2022-10-12 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2022-10-12_final.stac-item
2022-10-15 10:54:07	ga_s2bm_ard_3-2-1_53JLN_2022-10-15_final.stac-item
2022-10-15 10:54:14	ga_s2bm_ard_3-2-1_53JLN_2022-10-15_final.stac-item
2022-10-22 10:44:12	ga_s2bm_ard_3-2-1_53JLN_2022-10-22_final.stac-item
2022-10-25 10:54:07	ga_s2bm_ard_3-2-1_53JLN_2022-10-25_final.stac-item
2022-10-25 10:54:14	ga_s2bm_ard_3-2-1_53JLN_2022-10-25_final.stac-item
2022-11-01 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2022-11-01_final.stac-item
2022-11-04 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2022-11-04_final.stac-item
2022-11-11 10:44:06	ga_s2bm_ard_3-2-1_53JLN_2022-11-11_final.stac-item
2022-11-11 10:44:14	ga_s2bm_ard_3-2-1_53JLN_2022-11-11_final.stac-item
2022-11-14 10:54:08	ga_s2bm_ard_3-2-1_53JLN_2022-11-14_final.stac-item
2022-11-21 10:44:12	ga_s2bm_ard_3-2-1_53JLN_2022-11-21_final.stac-item
2022-11-24 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2022-11-24_final.stac-item
2022-11-24 10:54:10	ga_s2bm_ard_3-2-1_53JLN_2022-11-24_final.stac-item
2022-12-01 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2022-12-01_final.stac-item
2022-12-04 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2022-12-04_final.stac-item
2022-12-11 10:44:10	ga_s2bm_ard_3-2-1_53JLN_2022-12-11_final.stac-item
2022-12-14 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2022-12-14_final.stac-item
2022-12-21 10:44:12	ga_s2bm_ard_3-2-1_53JLN_2022-12-21_final.stac-item
2022-12-24 10:54:07	ga_s2bm_ard_3-2-1_53JLN_2022-12-24_final.stac-item
2022-12-31 10:44:12	ga_s2bm_ard_3-2-1_53JLN_2022-12-31_final.stac-item
2023-01-03 10:54:07	ga_s2bm_ard_3-2-1_53JLN_2023-01-03_final.stac-item
2023-01-10 10:44:09	ga_s2bm_ard_3-2-1_53JLN_2023-01-10_final.stac-item
2023-01-13 10:54:04	ga_s2bm_ard_3-2-1_53JLN_2023-01-13_final.stac-item
2023-01-20 10:44:10	ga_s2bm_ard_3-2-1_53JLN_2023-01-20_final.stac-item
2023-01-23 10:54:06	ga_s2bm_ard_3-2-1_53JLN_2023-01-23_final.stac-item
2023-01-30 10:44:07	ga_s2bm_ard_3-2-1_53JLN_2023-01-30_final.stac-item
2023-01-30 10:44:14	ga_s2bm_ard_3-2-1_53JLN_2023-01-30_final.stac-item
2023-02-02 10:54:05	ga_s2bm_ard_3-2-1_53JLN_2023-02-02_final
2023-02-09 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2023-02-09_final.stac-item
2023-02-12 10:54:07	ga_s2bm_ard_3-2-1_53JLN_2023-02-12_final
2023-02-19 10:44:11	ga_s2bm_ard_3-2-1_53JLN_2023-02-19_final
2023-02-22 10:54:15	ga_s2bm_ard_3-2-1_53JLN_2023-02-22_final
2023-08-08 10:44:18	ga_s2bm_ard_3-2-1_53JLN_2023-08-08_final
2023-08-21 10:54:13	ga_s2bm_ard_3-2-1_53JLN_2023-08-21_final
2023-08-28 10:44:17	ga_s2bm_ard_3-2-1_53JLN_2023-08-28_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