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
2021-10-21 10:24:22	ga_s2bm_ard_3-2-1_54JWR_2021-10-21_final.stac-item
2021-10-31 10:24:22	ga_s2bm_ard_3-2-1_54JWR_2021-10-31_final.stac-item
2021-11-07 10:14:28	ga_s2bm_ard_3-2-1_54JWR_2021-11-07_final.stac-item
2021-11-10 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2021-11-10_final.stac-item
2021-11-20 10:24:18	ga_s2bm_ard_3-2-1_54JWR_2021-11-20_final.stac-item
2021-12-27 10:14:24	ga_s2bm_ard_3-2-1_54JWR_2021-12-27_final.stac-item
2021-12-30 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2021-12-30_final.stac-item
2022-01-06 10:14:24	ga_s2bm_ard_3-2-1_54JWR_2022-01-06_final.stac-item
2022-01-09 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2022-01-09_final.stac-item
2022-01-16 10:14:24	ga_s2bm_ard_3-2-1_54JWR_2022-01-16_final.stac-item
2022-01-26 10:14:22	ga_s2bm_ard_3-2-1_54JWR_2022-01-26_final.stac-item
2022-02-05 10:14:22	ga_s2bm_ard_3-2-1_54JWR_2022-02-05_final.stac-item
2022-02-25 10:14:24	ga_s2bm_ard_3-2-1_54JWR_2022-02-25_final.stac-item
2022-02-28 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2022-02-28_final.stac-item
2022-03-07 10:14:25	ga_s2bm_ard_3-2-1_54JWR_2022-03-07_final.stac-item
2022-03-10 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2022-03-10_final.stac-item
2022-03-20 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2022-03-20_final.stac-item
2022-04-16 10:14:24	ga_s2bm_ard_3-2-1_54JWR_2022-04-16_final.stac-item
2022-04-19 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2022-04-19_final.stac-item
2022-04-26 10:14:22	ga_s2bm_ard_3-2-1_54JWR_2022-04-26_final.stac-item
2022-04-29 10:24:14	ga_s2bm_ard_3-2-1_54JWR_2022-04-29_final.stac-item
2022-05-09 10:24:18	ga_s2bm_ard_3-2-1_54JWR_2022-05-09_final.stac-item
2022-05-16 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2022-05-16_final.stac-item
2022-05-19 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2022-05-19_final.stac-item
2022-05-26 10:14:28	ga_s2bm_ard_3-2-1_54JWR_2022-05-26_final.stac-item
2022-05-29 10:24:21	ga_s2bm_ard_3-2-1_54JWR_2022-05-29_final.stac-item
2022-06-05 10:14:29	ga_s2bm_ard_3-2-1_54JWR_2022-06-05_final.stac-item
2022-06-15 10:14:31	ga_s2bm_ard_3-2-1_54JWR_2022-06-15_final.stac-item
2022-06-18 10:24:22	ga_s2bm_ard_3-2-1_54JWR_2022-06-18_final.stac-item
2022-06-18 10:24:26	ga_s2bm_ard_3-2-1_54JWR_2022-06-18_final.stac-item
2022-06-25 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2022-06-25_final.stac-item
2022-06-28 10:24:23	ga_s2bm_ard_3-2-1_54JWR_2022-06-28_final.stac-item
2022-06-28 10:24:27	ga_s2bm_ard_3-2-1_54JWR_2022-06-28_final.stac-item
2022-07-08 10:24:23	ga_s2bm_ard_3-2-1_54JWR_2022-07-08_final.stac-item
2022-07-08 10:24:27	ga_s2bm_ard_3-2-1_54JWR_2022-07-08_final.stac-item
2022-07-15 10:14:32	ga_s2bm_ard_3-2-1_54JWR_2022-07-15_final.stac-item
2022-07-18 10:24:23	ga_s2bm_ard_3-2-1_54JWR_2022-07-18_final.stac-item
2022-07-18 10:24:27	ga_s2bm_ard_3-2-1_54JWR_2022-07-18_final.stac-item
2022-07-25 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2022-07-25_final.stac-item
2022-07-28 10:24:23	ga_s2bm_ard_3-2-1_54JWR_2022-07-28_final.stac-item
2022-07-28 10:24:27	ga_s2bm_ard_3-2-1_54JWR_2022-07-28_final.stac-item
2022-08-04 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2022-08-04_final.stac-item
2022-08-07 10:24:22	ga_s2bm_ard_3-2-1_54JWR_2022-08-07_final.stac-item
2022-08-07 10:24:26	ga_s2bm_ard_3-2-1_54JWR_2022-08-07_final.stac-item
2022-08-14 10:14:31	ga_s2bm_ard_3-2-1_54JWR_2022-08-14_final.stac-item
2022-08-17 10:24:21	ga_s2bm_ard_3-2-1_54JWR_2022-08-17_final.stac-item
2022-08-17 10:24:25	ga_s2bm_ard_3-2-1_54JWR_2022-08-17_final.stac-item
2022-08-24 10:14:28	ga_s2bm_ard_3-2-1_54JWR_2022-08-24_final.stac-item
2022-08-27 10:24:18	ga_s2bm_ard_3-2-1_54JWR_2022-08-27_final.stac-item
2022-08-27 10:24:23	ga_s2bm_ard_3-2-1_54JWR_2022-08-27_final.stac-item
2022-09-03 10:14:29	ga_s2bm_ard_3-2-1_54JWR_2022-09-03_final.stac-item
2022-09-06 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2022-09-06_final.stac-item
2022-09-06 10:24:24	ga_s2bm_ard_3-2-1_54JWR_2022-09-06_final.stac-item
2022-09-13 10:14:30	ga_s2bm_ard_3-2-1_54JWR_2022-09-13_final.stac-item
2022-09-16 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2022-09-16_final.stac-item
2022-09-16 10:24:24	ga_s2bm_ard_3-2-1_54JWR_2022-09-16_final.stac-item
2022-09-23 10:14:29	ga_s2bm_ard_3-2-1_54JWR_2022-09-23_final.stac-item
2022-09-26 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2022-09-26_final.stac-item
2022-09-26 10:24:23	ga_s2bm_ard_3-2-1_54JWR_2022-09-26_final.stac-item
2022-10-03 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2022-10-03_final.stac-item
2022-10-06 10:24:16	ga_s2bm_ard_3-2-1_54JWR_2022-10-06_final.stac-item
2022-10-06 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2022-10-06_final.stac-item
2022-10-13 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2022-10-13_final.stac-item
2022-10-16 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2022-10-16_final.stac-item
2022-10-16 10:24:21	ga_s2bm_ard_3-2-1_54JWR_2022-10-16_final.stac-item
2022-10-23 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2022-10-23_final.stac-item
2022-10-26 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2022-10-26_final.stac-item
2022-10-26 10:24:24	ga_s2bm_ard_3-2-1_54JWR_2022-10-26_final.stac-item
2022-11-02 10:14:26	ga_s2bm_ard_3-2-1_54JWR_2022-11-02_final.stac-item
2022-11-05 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2022-11-05_final.stac-item
2022-11-12 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2022-11-12_final.stac-item
2022-11-15 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2022-11-15_final.stac-item
2022-11-22 10:14:28	ga_s2bm_ard_3-2-1_54JWR_2022-11-22_final.stac-item
2022-11-25 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2022-11-25_final.stac-item
2022-12-02 10:14:26	ga_s2bm_ard_3-2-1_54JWR_2022-12-02_final.stac-item
2022-12-05 10:24:18	ga_s2bm_ard_3-2-1_54JWR_2022-12-05_final.stac-item
2022-12-12 10:14:25	ga_s2bm_ard_3-2-1_54JWR_2022-12-12_final.stac-item
2022-12-15 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2022-12-15_final.stac-item
2022-12-22 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2022-12-22_final.stac-item
2023-01-01 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2023-01-01_final.stac-item
2023-01-04 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2023-01-04_final.stac-item
2023-01-11 10:14:24	ga_s2bm_ard_3-2-1_54JWR_2023-01-11_final.stac-item
2023-01-11 10:14:32	ga_s2bm_ard_3-2-1_54JWR_2023-01-11_final.stac-item
2023-01-14 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2023-01-14_final.stac-item
2023-01-21 10:14:26	ga_s2bm_ard_3-2-1_54JWR_2023-01-21_final.stac-item
2023-01-24 10:24:19	ga_s2bm_ard_3-2-1_54JWR_2023-01-24_final.stac-item
2023-01-31 10:14:25	ga_s2bm_ard_3-2-1_54JWR_2023-01-31_final.stac-item
2023-02-03 10:24:18	ga_s2bm_ard_3-2-1_54JWR_2023-02-03_final.stac-item
2023-02-10 10:14:26	ga_s2bm_ard_3-2-1_54JWR_2023-02-10_final.stac-item
2023-02-13 10:24:17	ga_s2bm_ard_3-2-1_54JWR_2023-02-13_nrt.stac-item
2023-02-13 10:24:21	ga_s2bm_ard_3-2-1_54JWR_2023-02-13_final
2023-02-20 10:14:27	ga_s2bm_ard_3-2-1_54JWR_2023-02-20_final
2023-08-02 10:24:22	ga_s2bm_ard_3-2-1_54JWR_2023-08-02_final
2023-08-02 10:24:26	ga_s2bm_ard_3-2-1_54JWR_2023-08-02_final
2023-08-09 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2023-08-09_final
2023-08-09 10:14:41	ga_s2bm_ard_3-2-1_54JWR_2023-08-09_final
2023-08-12 10:24:26	ga_s2bm_ard_3-2-1_54JWR_2023-08-12_final
2023-08-19 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2023-08-19_final
2023-08-22 10:24:25	ga_s2bm_ard_3-2-1_54JWR_2023-08-22_final
2023-08-29 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2023-08-29_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