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
2018-05-23 12:13:19	ga_s2bm_ard_3-2-1_49KGQ_2018-05-23_final.stac-item
2018-06-12 12:13:19	ga_s2bm_ard_3-2-1_49KGR_2018-06-12_final.stac-item
2018-06-22 12:13:20	ga_s2bm_ard_3-2-1_49KGP_2018-06-22_final.stac-item
2018-06-22 12:13:20	ga_s2bm_ard_3-2-1_49KGQ_2018-06-22_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_49JHN_2018-09-27_final.stac-item
2018-09-30 12:13:16	ga_s2bm_ard_3-2-1_49KGP_2018-09-30_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JGN_2018-10-17_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JHM_2018-10-27_final.stac-item
2019-02-14 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2019-02-14_final.stac-item
2019-02-17 12:13:58	ga_s2bm_ard_3-2-1_49KGR_2019-02-17_final.stac-item
2019-02-24 12:04:30	ga_s2bm_ard_3-2-1_49KGP_2019-02-24_final.stac-item
2019-03-19 12:14:26	ga_s2bm_ard_3-2-1_49KGP_2019-03-19_final.stac-item
2019-04-18 12:14:04	ga_s2bm_ard_3-2-1_49KGR_2019-04-18_final.stac-item
2019-04-28 12:14:02	ga_s2bm_ard_3-2-1_49KGR_2019-04-28_final.stac-item
2019-05-05 12:04:26	ga_s2bm_ard_3-2-1_49KGQ_2019-05-05_final.stac-item
2019-05-08 12:14:14	ga_s2bm_ard_3-2-1_49KGR_2019-05-08_final.stac-item
2019-05-08 12:14:21	ga_s2bm_ard_3-2-1_49KGQ_2019-05-08_final.stac-item
2019-06-24 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-06-24_final.stac-item
2019-07-17 12:14:21	ga_s2bm_ard_3-2-1_49KGQ_2019-07-17_final.stac-item
2019-08-06 12:14:34	ga_s2bm_ard_3-2-1_49KGP_2019-08-06_final.stac-item
2019-08-26 12:14:05	ga_s2bm_ard_3-2-1_49KGR_2019-08-26_final.stac-item
2019-09-25 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-09-25_final.stac-item
2019-11-01 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2019-11-01_final.stac-item
2019-12-01 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2019-12-01_final.stac-item
2019-12-11 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2019-12-11_final.stac-item
2020-01-20 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2020-01-20_final.stac-item
2020-01-30 12:04:23	ga_s2bm_ard_3-2-1_49KGP_2020-01-30_final.stac-item
2020-02-02 12:14:20	ga_s2bm_ard_3-2-1_49KGP_2020-02-02_final.stac-item
2020-04-09 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2020-04-09_final.stac-item
2020-04-09 12:04:53	ga_s2bm_ard_3-2-1_49JHM_2020-04-09_final.stac-item
2020-05-02 12:14:03	ga_s2bm_ard_3-2-1_49KGQ_2020-05-02_final.stac-item
2020-07-18 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2020-07-18_final.stac-item
2020-07-21 12:14:43	ga_s2bm_ard_3-2-1_49JGN_2020-07-21_final.stac-item
2020-07-28 12:04:45	ga_s2bm_ard_3-2-1_49JHN_2020-07-28_final.stac-item
2020-07-28 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2020-07-28_final.stac-item
2020-09-06 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2020-09-06_final.stac-item
2020-09-06 12:04:52	ga_s2bm_ard_3-2-1_49JGN_2020-09-06_final.stac-item
2020-09-06 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2020-09-06_final.stac-item
2020-09-09 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2020-09-09_final.stac-item
2020-10-06 12:04:35	ga_s2bm_ard_3-2-1_49KGP_2020-10-06_final.stac-item
2021-04-07 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2021-04-07_final.stac-item
2021-04-17 12:13:54	ga_s2bm_ard_3-2-1_49KGR_2021-04-17_final.stac-item
2021-09-04 12:14:09	ga_s2bm_ard_3-2-1_49KGQ_2021-09-04_final.stac-item
2021-09-11 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2021-09-11_final.stac-item
2021-10-01 12:04:22	ga_s2bm_ard_3-2-1_49KGQ_2021-10-01_final.stac-item
2021-10-01 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2021-10-01_final.stac-item
2021-10-11 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2021-10-11_final.stac-item
2021-10-21 12:04:19	ga_s2bm_ard_3-2-1_49KGQ_2021-10-21_final.stac-item
2021-10-21 12:04:49	ga_s2bm_ard_3-2-1_49JHM_2021-10-21_final.stac-item
2021-11-30 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2021-11-30_final.stac-item
2021-12-10 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2021-12-10_final.stac-item
2021-12-20 12:04:51	ga_s2bm_ard_3-2-1_49JHM_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
2022-01-09 12:04:53	ga_s2bm_ard_3-2-1_49JHM_2022-01-09_final.stac-item
2022-01-12 12:14:23	ga_s2bm_ard_3-2-1_49KGP_2022-01-12_final.stac-item
2022-03-03 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2022-03-03_final.stac-item
2022-03-10 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2022-03-10_final.stac-item
2022-04-19 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2022-04-19_final.stac-item
2022-05-12 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2022-05-12_final.stac-item
2022-05-29 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2022-05-29_final.stac-item
2022-06-28 12:05:34	ga_s2bm_ard_3-2-1_49JGK_2022-06-28_final.stac-item
2022-07-08 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2022-07-08_final.stac-item
2022-07-08 12:05:20	ga_s2bm_ard_3-2-1_49JGL_2022-07-08_final.stac-item
2022-07-08 12:05:34	ga_s2bm_ard_3-2-1_49JGK_2022-07-08_final.stac-item
2022-07-11 12:15:04	ga_s2bm_ard_3-2-1_49JFM_2022-07-11_final.stac-item
2022-07-18 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2022-07-18_final.stac-item
2022-07-18 12:05:01	ga_s2bm_ard_3-2-1_49JHM_2022-07-18_final.stac-item
2022-07-21 12:14:03	ga_s2bm_ard_3-2-1_49KGR_2022-07-21_final.stac-item
2022-08-27 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2022-08-27_final.stac-item
2022-09-26 12:04:19	ga_s2bm_ard_3-2-1_49KGQ_2022-09-26_final.stac-item
2022-09-26 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2022-09-26_final.stac-item
2022-11-25 12:04:56	ga_s2bm_ard_3-2-1_49JHM_2022-11-25_final.stac-item
2022-12-15 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2022-12-15_final.stac-item
2023-01-14 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2023-01-14_final.stac-item
2023-01-24 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2023-01-24_final.stac-item
2023-02-23 12:04:46	ga_s2bm_ard_3-2-1_49JHN_2023-02-23_final
2023-03-25 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2023-03-25_final
2023-04-04 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2023-04-04_final
2023-05-14 12:05:00	ga_s2bm_ard_3-2-1_49JHM_2023-05-14_final
2023-05-17 12:14:03	ga_s2bm_ard_3-2-1_49KGR_2023-05-17_final
2023-06-03 12:04:22	ga_s2bm_ard_3-2-1_49KGQ_2023-06-03_final
2023-06-03 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2023-06-03_final
2023-06-13 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2023-06-13_final
2023-07-03 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2023-07-03_final
2023-07-03 12:04:33	ga_s2bm_ard_3-2-1_49KGP_2023-07-03_final
2023-07-23 12:05:03	ga_s2bm_ard_3-2-1_49JHM_2023-07-23_final
2023-08-22 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2023-08-22_final
2023-09-01 12:05:01	ga_s2bm_ard_3-2-1_49JHM_2023-09-01_final
2023-10-01 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2023-10-01_final
2023-10-01 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2023-10-01_final
2023-10-01 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2023-10-01_final
2023-10-21 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2023-10-21_final
2023-10-31 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2023-10-31_final
2023-10-31 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2023-10-31_final
2023-11-30 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2023-11-30_final
2023-12-03 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2023-12-03_final
2023-12-13 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2023-12-13_final
2024-01-29 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2024-01-29_final
2024-01-29 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2024-01-29_final
2024-03-29 12:04:27	ga_s2bm_ard_3-2-1_49KGP_2024-03-29_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

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