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
2021-09-25 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2021-09-25_final.stac-item
2021-10-08 10:16:00	ga_s2bm_ard_3-2-1_54HXJ_2021-10-08_final.stac-item
2021-10-18 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2021-10-18_final.stac-item
2021-10-25 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2021-10-25_final.stac-item
2021-11-24 10:06:06	ga_s2bm_ard_3-2-1_54HXJ_2021-11-24_final.stac-item
2021-12-07 10:15:55	ga_s2bm_ard_3-2-1_54HXJ_2021-12-07_final.stac-item
2021-12-24 10:06:05	ga_s2bm_ard_3-2-1_54HXJ_2021-12-24_final.stac-item
2021-12-27 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2021-12-27_final.stac-item
2022-01-03 10:06:03	ga_s2bm_ard_3-2-1_54HXJ_2022-01-03_final.stac-item
2022-01-03 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-01-03_final.stac-item
2022-01-06 10:15:55	ga_s2bm_ard_3-2-1_54HXJ_2022-01-06_final.stac-item
2022-01-06 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2022-01-06_final.stac-item
2022-01-13 10:06:06	ga_s2bm_ard_3-2-1_54HXJ_2022-01-13_final.stac-item
2022-01-16 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2022-01-16_final.stac-item
2022-01-23 10:05:56	ga_s2bm_ard_3-2-1_54HXJ_2022-01-23_final.stac-item
2022-01-23 10:06:05	ga_s2bm_ard_3-2-1_54HXJ_2022-01-23_final.stac-item
2022-01-26 10:15:54	ga_s2bm_ard_3-2-1_54HXJ_2022-01-26_final.stac-item
2022-02-02 10:06:04	ga_s2bm_ard_3-2-1_54HXJ_2022-02-02_final.stac-item
2022-02-05 10:15:55	ga_s2bm_ard_3-2-1_54HXJ_2022-02-05_final.stac-item
2022-02-12 10:06:04	ga_s2bm_ard_3-2-1_54HXJ_2022-02-12_final.stac-item
2022-02-15 10:15:54	ga_s2bm_ard_3-2-1_54HXJ_2022-02-15_final.stac-item
2022-02-25 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2022-02-25_final.stac-item
2022-03-17 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2022-03-17_final.stac-item
2022-03-24 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2022-03-24_final.stac-item
2022-04-03 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2022-04-03_final.stac-item
2022-04-06 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-04-06_final.stac-item
2022-04-13 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2022-04-13_final.stac-item
2022-04-16 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2022-04-16_final.stac-item
2022-04-23 10:06:05	ga_s2bm_ard_3-2-1_54HXJ_2022-04-23_final.stac-item
2022-04-26 10:15:54	ga_s2bm_ard_3-2-1_54HXJ_2022-04-26_final.stac-item
2022-04-26 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2022-04-26_final.stac-item
2022-05-03 10:06:05	ga_s2bm_ard_3-2-1_54HXJ_2022-05-03_final.stac-item
2022-05-06 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2022-05-06_final.stac-item
2022-05-06 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2022-05-06_final.stac-item
2022-05-13 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2022-05-13_final.stac-item
2022-05-16 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-05-16_final.stac-item
2022-05-16 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2022-05-16_final.stac-item
2022-05-23 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2022-05-23_final.stac-item
2022-05-26 10:16:00	ga_s2bm_ard_3-2-1_54HXJ_2022-05-26_final.stac-item
2022-05-26 10:16:02	ga_s2bm_ard_3-2-1_54HXJ_2022-05-26_final.stac-item
2022-06-02 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2022-06-02_final.stac-item
2022-06-05 10:16:00	ga_s2bm_ard_3-2-1_54HXJ_2022-06-05_final.stac-item
2022-06-05 10:16:02	ga_s2bm_ard_3-2-1_54HXJ_2022-06-05_final.stac-item
2022-06-12 10:06:13	ga_s2bm_ard_3-2-1_54HXJ_2022-06-12_final.stac-item
2022-06-15 10:16:03	ga_s2bm_ard_3-2-1_54HXJ_2022-06-15_final.stac-item
2022-06-22 10:06:15	ga_s2bm_ard_3-2-1_54HXJ_2022-06-22_final.stac-item
2022-06-25 10:16:05	ga_s2bm_ard_3-2-1_54HXJ_2022-06-25_final.stac-item
2022-07-02 10:06:15	ga_s2bm_ard_3-2-1_54HXJ_2022-07-02_final.stac-item
2022-07-05 10:16:05	ga_s2bm_ard_3-2-1_54HXJ_2022-07-05_final.stac-item
2022-07-12 10:06:14	ga_s2bm_ard_3-2-1_54HXJ_2022-07-12_final.stac-item
2022-07-15 10:16:04	ga_s2bm_ard_3-2-1_54HXJ_2022-07-15_final.stac-item
2022-07-22 10:06:15	ga_s2bm_ard_3-2-1_54HXJ_2022-07-22_final.stac-item
2022-07-25 10:16:05	ga_s2bm_ard_3-2-1_54HXJ_2022-07-25_final.stac-item
2022-08-01 10:06:15	ga_s2bm_ard_3-2-1_54HXJ_2022-08-01_final.stac-item
2022-08-04 10:16:05	ga_s2bm_ard_3-2-1_54HXJ_2022-08-04_final.stac-item
2022-08-11 10:06:14	ga_s2bm_ard_3-2-1_54HXJ_2022-08-11_final.stac-item
2022-08-14 10:16:03	ga_s2bm_ard_3-2-1_54HXJ_2022-08-14_final.stac-item
2022-08-21 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2022-08-21_final.stac-item
2022-08-24 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2022-08-24_final.stac-item
2022-08-31 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2022-08-31_final.stac-item
2022-09-03 10:16:02	ga_s2bm_ard_3-2-1_54HXJ_2022-09-03_final.stac-item
2022-09-10 10:06:12	ga_s2bm_ard_3-2-1_54HXJ_2022-09-10_final.stac-item
2022-09-13 10:16:02	ga_s2bm_ard_3-2-1_54HXJ_2022-09-13_final.stac-item
2022-09-20 10:06:12	ga_s2bm_ard_3-2-1_54HXJ_2022-09-20_final.stac-item
2022-09-23 10:16:01	ga_s2bm_ard_3-2-1_54HXJ_2022-09-23_final.stac-item
2022-09-30 10:06:10	ga_s2bm_ard_3-2-1_54HXJ_2022-09-30_final.stac-item
2022-10-03 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-10-03_final.stac-item
2022-10-10 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2022-10-10_final.stac-item
2022-10-13 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-10-13_final.stac-item
2022-10-20 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-10-20_final.stac-item
2022-10-23 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-10-23_final.stac-item
2022-10-30 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-10-30_final.stac-item
2022-11-02 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2022-11-02_final.stac-item
2022-11-09 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-11-09_final.stac-item
2022-11-12 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-11-12_final.stac-item
2022-11-19 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2022-11-19_final.stac-item
2022-11-19 10:06:13	ga_s2bm_ard_3-2-1_54HXJ_2022-11-19_final.stac-item
2022-11-22 10:16:00	ga_s2bm_ard_3-2-1_54HXJ_2022-11-22_final.stac-item
2022-11-29 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-11-29_final.stac-item
2022-12-02 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2022-12-02_final.stac-item
2022-12-09 10:06:06	ga_s2bm_ard_3-2-1_54HXJ_2022-12-09_final.stac-item
2022-12-12 10:15:57	ga_s2bm_ard_3-2-1_54HXJ_2022-12-12_final.stac-item
2022-12-19 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-12-19_final.stac-item
2022-12-22 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2022-12-22_final.stac-item
2022-12-29 10:06:09	ga_s2bm_ard_3-2-1_54HXJ_2022-12-29_final.stac-item
2023-01-01 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2023-01-01_final.stac-item
2023-01-08 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2023-01-08_final.stac-item
2023-01-11 10:15:56	ga_s2bm_ard_3-2-1_54HXJ_2023-01-11_final.stac-item
2023-01-18 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2023-01-18_final.stac-item
2023-01-21 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2023-01-21_final.stac-item
2023-01-28 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2023-01-28_final.stac-item
2023-01-31 10:15:58	ga_s2bm_ard_3-2-1_54HXJ_2023-01-31_final.stac-item
2023-02-07 10:06:08	ga_s2bm_ard_3-2-1_54HXJ_2023-02-07_final
2023-02-10 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2023-02-10_final.stac-item
2023-02-20 10:15:59	ga_s2bm_ard_3-2-1_54HXJ_2023-02-20_final
2023-08-06 10:06:15	ga_s2bm_ard_3-2-1_54HXJ_2023-08-06_final
2023-08-09 10:16:05	ga_s2bm_ard_3-2-1_54HXJ_2023-08-09_final
2023-08-16 10:06:15	ga_s2bm_ard_3-2-1_54HXJ_2023-08-16_final
2023-08-19 10:16:05	ga_s2bm_ard_3-2-1_54HXJ_2023-08-19_final
2023-08-26 10:06:14	ga_s2bm_ard_3-2-1_54HXJ_2023-08-26_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