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
2019-01-07 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2019-01-06_final.stac-item
2019-01-17 09:23:39	ga_s2bm_ard_3-2-1_56JNT_2019-01-16_final.stac-item
2019-02-06 09:23:40	ga_s2bm_ard_3-2-1_56JNT_2019-02-05_final.stac-item
2019-03-01 09:33:34	ga_s2bm_ard_3-2-1_56JNT_2019-03-01_final.stac-item
2019-03-18 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2019-03-17_final.stac-item
2019-04-17 09:23:45	ga_s2bm_ard_3-2-1_56JNT_2019-04-16_final.stac-item
2019-05-07 09:23:48	ga_s2bm_ard_3-2-1_56JNT_2019-05-06_final.stac-item
2019-06-29 09:33:44	ga_s2bm_ard_3-2-1_56JNT_2019-06-29_final.stac-item
2019-07-06 09:23:48	ga_s2bm_ard_3-2-1_56JNT_2019-07-05_final.stac-item
2019-07-16 09:23:48	ga_s2bm_ard_3-2-1_56JNT_2019-07-15_final.stac-item
2019-08-05 09:23:47	ga_s2bm_ard_3-2-1_56JNT_2019-08-04_final.stac-item
2019-08-08 09:33:43	ga_s2bm_ard_3-2-1_56JNT_2019-08-08_final.stac-item
2019-08-15 09:23:46	ga_s2bm_ard_3-2-1_56JNT_2019-08-14_final.stac-item
2019-08-18 09:33:41	ga_s2bm_ard_3-2-1_56JNT_2019-08-18_final.stac-item
2019-08-25 09:23:44	ga_s2bm_ard_3-2-1_56JNT_2019-08-24_final.stac-item
2019-08-28 09:33:40	ga_s2bm_ard_3-2-1_56JNT_2019-08-28_final.stac-item
2019-09-04 09:23:42	ga_s2bm_ard_3-2-1_56JNT_2019-09-03_final.stac-item
2019-09-07 09:33:37	ga_s2bm_ard_3-2-1_56JNT_2019-09-07_final.stac-item
2019-09-14 09:23:40	ga_s2bm_ard_3-2-1_56JNT_2019-09-13_final.stac-item
2019-09-17 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2019-09-17_final.stac-item
2019-09-24 09:23:39	ga_s2bm_ard_3-2-1_56JNT_2019-09-23_final.stac-item
2019-09-27 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2019-09-27_final.stac-item
2019-10-04 09:23:40	ga_s2bm_ard_3-2-1_56JNT_2019-10-03_final.stac-item
2019-10-07 09:33:36	ga_s2bm_ard_3-2-1_56JNT_2019-10-07_final.stac-item
2019-10-14 09:23:41	ga_s2bm_ard_3-2-1_56JNT_2019-10-13_final.stac-item
2019-10-17 09:33:37	ga_s2bm_ard_3-2-1_56JNT_2019-10-17_final.stac-item
2019-10-24 09:23:41	ga_s2bm_ard_3-2-1_56JNT_2019-10-23_final.stac-item
2019-10-27 09:33:36	ga_s2bm_ard_3-2-1_56JNT_2019-10-27_final.stac-item
2019-11-03 09:23:40	ga_s2bm_ard_3-2-1_56JNT_2019-11-02_final.stac-item
2019-11-06 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2019-11-06_final.stac-item
2019-11-13 09:23:39	ga_s2bm_ard_3-2-1_56JNT_2019-11-12_final.stac-item
2019-11-16 09:33:34	ga_s2bm_ard_3-2-1_56JNT_2019-11-16_final.stac-item
2019-11-23 09:23:37	ga_s2bm_ard_3-2-1_56JNT_2019-11-22_final.stac-item
2019-12-03 09:23:34	ga_s2bm_ard_3-2-1_56JNT_2019-12-02_final.stac-item
2019-12-06 09:33:29	ga_s2bm_ard_3-2-1_56JNT_2019-12-06_final.stac-item
2019-12-13 09:23:34	ga_s2bm_ard_3-2-1_56JNT_2019-12-12_final.stac-item
2019-12-16 09:33:30	ga_s2bm_ard_3-2-1_56JNT_2019-12-16_final.stac-item
2019-12-23 09:23:35	ga_s2bm_ard_3-2-1_56JNT_2019-12-22_final.stac-item
2019-12-26 09:33:31	ga_s2bm_ard_3-2-1_56JNT_2019-12-26_final.stac-item
2020-01-02 09:23:35	ga_s2bm_ard_3-2-1_56JNT_2020-01-01_final.stac-item
2020-01-05 09:33:30	ga_s2bm_ard_3-2-1_56JNT_2020-01-05_final.stac-item
2020-01-12 09:23:34	ga_s2bm_ard_3-2-1_56JNT_2020-01-11_final.stac-item
2020-01-15 09:33:30	ga_s2bm_ard_3-2-1_56JNT_2020-01-15_final.stac-item
2020-01-22 09:23:33	ga_s2bm_ard_3-2-1_56JNT_2020-01-21_final.stac-item
2020-01-25 09:33:28	ga_s2bm_ard_3-2-1_56JNT_2020-01-25_final.stac-item
2020-02-04 09:33:29	ga_s2bm_ard_3-2-1_56JNT_2020-02-04_final.stac-item
2020-02-11 09:23:35	ga_s2bm_ard_3-2-1_56JNT_2020-02-10_final.stac-item
2020-02-14 09:33:31	ga_s2bm_ard_3-2-1_56JNT_2020-02-14_final.stac-item
2020-02-21 09:23:36	ga_s2bm_ard_3-2-1_56JNT_2020-02-20_final.stac-item
2020-02-24 09:33:32	ga_s2bm_ard_3-2-1_56JNT_2020-02-24_final.stac-item
2020-03-02 09:23:37	ga_s2bm_ard_3-2-1_56JNT_2020-03-01_final.stac-item
2020-03-05 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2020-03-05_final.stac-item
2020-03-12 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2020-03-11_final.stac-item
2020-03-15 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2020-03-15_final.stac-item
2020-03-22 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2020-03-21_final.stac-item
2020-03-25 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2020-03-25_final.stac-item
2020-04-01 09:23:37	ga_s2bm_ard_3-2-1_56JNT_2020-03-31_final.stac-item
2020-04-04 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2020-04-04_final.stac-item
2020-04-21 09:23:34	ga_s2bm_ard_3-2-1_56JNT_2020-04-20_final.stac-item
2020-04-24 09:33:28	ga_s2bm_ard_3-2-1_56JNT_2020-04-24_final.stac-item
2020-04-24 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2020-04-24_final.stac-item
2020-05-11 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2020-05-10_final.stac-item
2020-05-24 09:33:36	ga_s2bm_ard_3-2-1_56JNT_2020-05-24_final.stac-item
2020-06-03 09:33:37	ga_s2bm_ard_3-2-1_56JNT_2020-06-03_final.stac-item
2020-06-13 09:33:38	ga_s2bm_ard_3-2-1_56JNT_2020-06-13_final.stac-item
2020-06-20 09:23:42	ga_s2bm_ard_3-2-1_56JNT_2020-06-19_final.stac-item
2020-06-30 09:23:42	ga_s2bm_ard_3-2-1_56JNT_2020-06-29_final.stac-item
2020-07-13 09:33:37	ga_s2bm_ard_3-2-1_56JNT_2020-07-13_final.stac-item
2020-07-23 09:33:37	ga_s2bm_ard_3-2-1_56JNT_2020-07-23_final.stac-item
2020-08-02 09:33:38	ga_s2bm_ard_3-2-1_56JNT_2020-08-02_final.stac-item
2020-08-19 09:23:43	ga_s2bm_ard_3-2-1_56JNT_2020-08-18_final.stac-item
2020-08-29 09:23:43	ga_s2bm_ard_3-2-1_56JNT_2020-08-28_final.stac-item
2020-09-11 09:33:38	ga_s2bm_ard_3-2-1_56JNT_2020-09-11_final.stac-item
2020-09-18 09:23:41	ga_s2bm_ard_3-2-1_56JNT_2020-09-17_final.stac-item
2020-09-21 09:33:38	ga_s2bm_ard_3-2-1_56JNT_2020-09-21_final.stac-item
2020-09-28 09:23:43	ga_s2bm_ard_3-2-1_56JNT_2020-09-27_final.stac-item
2020-10-01 09:33:39	ga_s2bm_ard_3-2-1_56JNT_2020-10-01_final.stac-item
2020-10-31 09:33:38	ga_s2bm_ard_3-2-1_56JNT_2020-10-31_final.stac-item
2020-11-07 09:23:42	ga_s2bm_ard_3-2-1_56JNT_2020-11-06_final.stac-item
2020-11-20 09:33:36	ga_s2bm_ard_3-2-1_56JNT_2020-11-20_final.stac-item
2022-10-21 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2022-10-21_final.stac-item
2022-11-10 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2022-11-10_final.stac-item
2022-12-07 09:23:36	ga_s2bm_ard_3-2-1_56JNT_2022-12-06_final.stac-item
2022-12-30 09:33:35	ga_s2bm_ard_3-2-1_56JNT_2022-12-30_final.stac-item
2023-01-06 09:23:37	ga_s2bm_ard_3-2-1_56JNT_2023-01-05_final.stac-item
2023-01-09 09:33:32	ga_s2bm_ard_3-2-1_56JNT_2023-01-09_final.stac-item
2023-01-16 09:23:36	ga_s2bm_ard_3-2-1_56JNT_2023-01-15_final.stac-item
2023-01-19 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2023-01-19_final.stac-item
2023-01-26 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2023-01-25_final.stac-item
2023-01-29 09:33:33	ga_s2bm_ard_3-2-1_56JNT_2023-01-29_final.stac-item
2023-02-05 09:23:37	ga_s2bm_ard_3-2-1_56JNT_2023-02-04_final.stac-item
2023-02-08 09:33:34	ga_s2bm_ard_3-2-1_56JNT_2023-02-08_final
2023-02-15 09:23:38	ga_s2bm_ard_3-2-1_56JNT_2023-02-14_final
2023-02-18 09:33:34	ga_s2bm_ard_3-2-1_56JNT_2023-02-18_final
2023-08-04 09:23:44	ga_s2bm_ard_3-2-1_56JNT_2023-08-03_final
2023-08-07 09:33:41	ga_s2bm_ard_3-2-1_56JNT_2023-08-07_final
2023-08-14 09:23:45	ga_s2bm_ard_3-2-1_56JNT_2023-08-13_final
2023-08-17 09:33:41	ga_s2bm_ard_3-2-1_56JNT_2023-08-17_final
2023-08-24 09:23:44	ga_s2bm_ard_3-2-1_56JNT_2023-08-23_final
2023-08-27 09:33:40	ga_s2bm_ard_3-2-1_56JNT_2023-08-27_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