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
2021-10-31 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2021-10-31_final.stac-item
2021-11-03 12:14:32	ga_s2bm_ard_3-2-1_49JHN_2021-11-03_final.stac-item
2021-11-13 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2021-11-13_final.stac-item
2021-11-20 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2021-11-20_final.stac-item
2021-11-30 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2021-11-30_final.stac-item
2021-12-03 12:14:26	ga_s2bm_ard_3-2-1_49JHN_2021-12-03_final.stac-item
2021-12-20 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2021-12-20_final.stac-item
2021-12-30 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2021-12-30_final.stac-item
2022-01-02 12:14:27	ga_s2bm_ard_3-2-1_49JHN_2022-01-02_final.stac-item
2022-01-29 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2022-01-29_final.stac-item
2022-02-01 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2022-02-01_final.stac-item
2022-02-11 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2022-02-11_final.stac-item
2022-02-28 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-02-28_final.stac-item
2022-03-03 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2022-03-03_final.stac-item
2022-03-13 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2022-03-13_final.stac-item
2022-03-20 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-03-20_final.stac-item
2022-03-23 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2022-03-23_final.stac-item
2022-03-30 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-03-30_final.stac-item
2022-04-02 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2022-04-02_final.stac-item
2022-04-12 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2022-04-12_final.stac-item
2022-04-19 12:04:35	ga_s2bm_ard_3-2-1_49JHN_2022-04-19_final.stac-item
2022-04-19 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-04-19_final.stac-item
2022-04-29 12:04:32	ga_s2bm_ard_3-2-1_49JHN_2022-04-29_final.stac-item
2022-04-29 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2022-04-29_final.stac-item
2022-05-02 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2022-05-02_final.stac-item
2022-05-09 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2022-05-09_final.stac-item
2022-05-09 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-05-09_final.stac-item
2022-05-12 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2022-05-12_final.stac-item
2022-05-19 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-05-19_final.stac-item
2022-05-22 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2022-05-22_final.stac-item
2022-05-29 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2022-05-29_final.stac-item
2022-05-29 12:04:46	ga_s2bm_ard_3-2-1_49JHN_2022-05-29_final.stac-item
2022-06-01 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2022-06-01_final.stac-item
2022-06-08 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2022-06-08_final.stac-item
2022-06-08 12:04:48	ga_s2bm_ard_3-2-1_49JHN_2022-06-08_final.stac-item
2022-06-18 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-06-18_final.stac-item
2022-06-18 12:04:50	ga_s2bm_ard_3-2-1_49JHN_2022-06-18_final.stac-item
2022-06-28 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2022-06-28_final.stac-item
2022-06-28 12:04:51	ga_s2bm_ard_3-2-1_49JHN_2022-06-28_final.stac-item
2022-07-08 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2022-07-08_final.stac-item
2022-07-08 12:04:51	ga_s2bm_ard_3-2-1_49JHN_2022-07-08_final.stac-item
2022-07-18 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2022-07-18_final.stac-item
2022-07-18 12:04:51	ga_s2bm_ard_3-2-1_49JHN_2022-07-18_final.stac-item
2022-07-21 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2022-07-21_final.stac-item
2022-07-28 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2022-07-28_final.stac-item
2022-07-31 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2022-07-31_final.stac-item
2022-08-07 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-08-07_final.stac-item
2022-08-07 12:04:50	ga_s2bm_ard_3-2-1_49JHN_2022-08-07_final.stac-item
2022-08-10 12:14:35	ga_s2bm_ard_3-2-1_49JHN_2022-08-10_final.stac-item
2022-08-17 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-08-17_final.stac-item
2022-08-17 12:04:49	ga_s2bm_ard_3-2-1_49JHN_2022-08-17_final.stac-item
2022-08-20 12:14:33	ga_s2bm_ard_3-2-1_49JHN_2022-08-20_final.stac-item
2022-08-27 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2022-08-27_final.stac-item
2022-08-27 12:04:46	ga_s2bm_ard_3-2-1_49JHN_2022-08-27_final.stac-item
2022-08-30 12:14:32	ga_s2bm_ard_3-2-1_49JHN_2022-08-30_final.stac-item
2022-09-06 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2022-09-06_final.stac-item
2022-09-06 12:04:48	ga_s2bm_ard_3-2-1_49JHN_2022-09-06_final.stac-item
2022-09-09 12:14:33	ga_s2bm_ard_3-2-1_49JHN_2022-09-09_final.stac-item
2022-09-16 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2022-09-16_final.stac-item
2022-09-16 12:04:48	ga_s2bm_ard_3-2-1_49JHN_2022-09-16_final.stac-item
2022-09-19 12:14:32	ga_s2bm_ard_3-2-1_49JHN_2022-09-19_final.stac-item
2022-09-26 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-09-26_final.stac-item
2022-09-26 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2022-09-26_final.stac-item
2022-09-29 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2022-09-29_final.stac-item
2022-10-06 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-10-06_final.stac-item
2022-10-09 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2022-10-09_final.stac-item
2022-10-16 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2022-10-16_final.stac-item
2022-10-16 12:04:45	ga_s2bm_ard_3-2-1_49JHN_2022-10-16_final.stac-item
2022-10-19 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-10-19_final.stac-item
2022-10-26 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-10-26_final.stac-item
2022-10-29 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-10-29_final.stac-item
2022-11-05 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-11-05_final.stac-item
2022-11-08 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-11-08_final.stac-item
2022-11-15 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-11-15_final.stac-item
2022-11-18 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-11-18_final.stac-item
2022-11-25 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-11-25_final.stac-item
2022-11-28 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-11-28_final.stac-item
2022-12-05 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-12-05_final.stac-item
2022-12-08 12:14:27	ga_s2bm_ard_3-2-1_49JHN_2022-12-08_final.stac-item
2022-12-15 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-12-15_final.stac-item
2022-12-18 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2022-12-18_final.stac-item
2022-12-25 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2022-12-25_final.stac-item
2022-12-28 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-12-28_final.stac-item
2023-01-04 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2023-01-04_final.stac-item
2023-01-07 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2023-01-07_final.stac-item
2023-01-14 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2023-01-14_final.stac-item
2023-01-17 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2023-01-17_final.stac-item
2023-01-24 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2023-01-24_final.stac-item
2023-01-27 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2023-01-27_final.stac-item
2023-02-03 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2023-02-03_final.stac-item
2023-02-06 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2023-02-06_final
2023-02-13 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2023-02-13_final
2023-02-16 12:14:29	ga_s2bm_ard_3-2-1_49JHN_2023-02-16_final
2023-08-02 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-08-02_final
2023-08-05 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2023-08-05_final
2023-08-12 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_49JHN_2023-08-12_final
2023-08-15 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2023-08-15_final
2023-08-22 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-08-22_final
2023-08-25 12:14:35	ga_s2bm_ard_3-2-1_49JHN_2023-08-25_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