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
2017-07-04 11:59:31	ga_s2bm_ard_3-2-1_49JHN_2017-07-04_final.stac-item
2017-07-04 11:59:31	ga_s2bm_ard_3-2-1_49KHR_2017-07-04_final.stac-item
2017-07-04 12:04:34	ga_s2bm_ard_3-2-1_49JHM_2017-07-04_final.stac-item
2017-07-17 12:13:21	ga_s2bm_ard_3-2-1_49KHQ_2017-07-17_final.stac-item
2017-10-05 12:13:31	ga_s2bm_ard_3-2-1_49KHR_2017-10-05_final.stac-item
2017-10-22 12:04:28	ga_s2bm_ard_3-2-1_49JHM_2017-10-22_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49KHP_2017-12-21_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_49JGM_2017-12-31_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49JGM_2018-01-10_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49KHP_2018-01-10_final.stac-item
2018-06-09 12:02:47	ga_s2bm_ard_3-2-1_49JGM_2018-06-09_final.stac-item
2018-06-22 12:14:14	ga_s2bm_ard_3-2-1_49KGP_2018-06-22_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_49KGP_2018-07-09_final.stac-item
2018-07-12 12:13:20	ga_s2bm_ard_3-2-1_49KHQ_2018-07-12_final.stac-item
2018-07-22 12:13:59	ga_s2bm_ard_3-2-1_49JGL_2018-07-22_final.stac-item
2018-08-01 12:13:25	ga_s2bm_ard_3-2-1_49JGM_2018-08-01_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_49JGM_2018-08-08_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_49JGL_2018-09-07_final.stac-item
2019-02-04 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-02-04_final.stac-item
2019-04-28 12:14:09	ga_s2bm_ard_3-2-1_49KGR_2019-04-28_final.stac-item
2019-05-08 12:15:04	ga_s2bm_ard_3-2-1_49JGM_2019-05-08_final.stac-item
2019-05-08 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-08_final.stac-item
2019-05-15 12:05:52	ga_s2bm_ard_3-2-1_49JGJ_2019-05-15_final.stac-item
2019-05-28 12:14:07	ga_s2bm_ard_3-2-1_49KGR_2019-05-28_final.stac-item
2019-06-17 12:14:34	ga_s2bm_ard_3-2-1_49KGP_2019-06-17_final.stac-item
2019-06-17 12:14:49	ga_s2bm_ard_3-2-1_49JGN_2019-06-17_final.stac-item
2019-06-24 12:04:36	ga_s2bm_ard_3-2-1_49KHP_2019-06-24_final.stac-item
2019-07-17 12:14:07	ga_s2bm_ard_3-2-1_49KGR_2019-07-17_final.stac-item
2019-09-02 12:04:17	ga_s2bm_ard_3-2-1_49KHQ_2019-09-02_final.stac-item
2019-09-22 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2019-09-22_final.stac-item
2019-10-12 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2019-10-12_final.stac-item
2019-10-19 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2019-10-19_final.stac-item
2020-01-20 12:04:54	ga_s2bm_ard_3-2-1_49JGM_2020-01-20_final.stac-item
2020-02-09 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2020-02-09_final.stac-item
2020-03-30 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2020-03-30_final.stac-item
2020-04-02 12:14:07	ga_s2bm_ard_3-2-1_49KHQ_2020-04-02_final.stac-item
2020-04-09 12:03:56	ga_s2bm_ard_3-2-1_49KHR_2020-04-09_final.stac-item
2020-04-12 12:15:07	ga_s2bm_ard_3-2-1_49JGL_2020-04-12_final.stac-item
2020-04-29 12:05:40	ga_s2bm_ard_3-2-1_49JGJ_2020-04-29_final.stac-item
2020-05-22 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2020-05-22_final.stac-item
2020-05-22 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2020-05-22_final.stac-item
2020-06-01 12:14:43	ga_s2bm_ard_3-2-1_49JGN_2020-06-01_final.stac-item
2020-06-08 12:05:22	ga_s2bm_ard_3-2-1_49JGL_2020-06-08_final.stac-item
2020-07-11 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2020-07-11_final.stac-item
2020-07-11 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2020-07-11_final.stac-item
2020-07-18 12:05:22	ga_s2bm_ard_3-2-1_49JGL_2020-07-18_final.stac-item
2020-07-28 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2020-07-28_final.stac-item
2021-02-17 11:47:24	ga_s2bm_ard_3-2-1_50HLG_2021-02-17_final
2021-04-04 12:04:11	ga_s2bm_ard_3-2-1_49KHQ_2021-04-04_final.stac-item
2021-04-04 12:04:19	ga_s2bm_ard_3-2-1_49KHQ_2021-04-04_final.stac-item
2021-06-03 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2021-06-03_final.stac-item
2021-06-03 12:05:30	ga_s2bm_ard_3-2-1_49JGK_2021-06-03_final.stac-item
2021-07-23 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2021-07-23_final.stac-item
2021-07-26 12:14:58	ga_s2bm_ard_3-2-1_49JGM_2021-07-26_final.stac-item
2021-08-02 12:04:24	ga_s2bm_ard_3-2-1_49KGQ_2021-08-02_final.stac-item
2021-08-02 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2021-08-02_final.stac-item
2021-09-01 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2021-09-01_final.stac-item
2021-09-18 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2021-09-18_final.stac-item
2021-10-11 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2021-10-11_final.stac-item
2021-10-18 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2021-10-18_final.stac-item
2021-12-20 12:03:54	ga_s2bm_ard_3-2-1_49KHR_2021-12-20_final.stac-item
2021-12-23 12:14:51	ga_s2bm_ard_3-2-1_49JGM_2021-12-23_final.stac-item
2022-02-11 12:13:52	ga_s2bm_ard_3-2-1_49KGR_2022-02-11_final.stac-item
2022-02-28 12:05:11	ga_s2bm_ard_3-2-1_49JGL_2022-02-28_final.stac-item
2022-04-26 11:57:03	ga_s2bm_ard_3-2-1_50HLH_2022-04-26_final.stac-item
2022-05-09 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2022-05-09_final.stac-item
2022-06-21 12:14:03	ga_s2bm_ard_3-2-1_49KGR_2022-06-21_final.stac-item
2022-07-18 12:05:19	ga_s2bm_ard_3-2-1_49JGL_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
2022-07-28 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2022-07-28_final.stac-item
2022-09-06 12:05:02	ga_s2bm_ard_3-2-1_49JGM_2022-09-06_final.stac-item
2022-09-26 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2022-09-26_final.stac-item
2023-04-04 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2023-04-04_final
2023-04-24 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-04-24_final
2023-05-17 12:14:25	ga_s2bm_ard_3-2-1_49KHP_2023-05-17_final
2023-07-16 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-07-16_final
2023-08-15 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-08-15_final
2023-08-16 11:47:32	ga_s2bm_ard_3-2-1_50HLG_2023-08-16_final
2023-08-22 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2023-08-22_final
2023-08-22 12:04:50	ga_s2bm_ard_3-2-1_49JGN_2023-08-22_final
2023-09-21 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2023-09-21_final
2023-10-04 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2023-10-04_final
2023-10-14 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2023-10-14_final
2023-10-24 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2023-10-24_final
2023-12-03 12:13:55	ga_s2bm_ard_3-2-1_49KGR_2023-12-03_final
2023-12-03 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2023-12-03_final
2023-12-10 12:04:42	ga_s2bm_ard_3-2-1_49JGN_2023-12-10_final
2023-12-20 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2023-12-20_final
2023-12-20 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2023-12-20_final
2023-12-30 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2023-12-30_final
2024-01-12 12:15:08	ga_s2bm_ard_3-2-1_49JGL_2024-01-12_final
2024-02-01 12:13:51	ga_s2bm_ard_3-2-1_49KHR_2024-02-01_final
2024-02-01 12:14:10	ga_s2bm_ard_3-2-1_49KGQ_2024-02-01_final
2024-02-08 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2024-02-08_final
2024-02-21 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2024-02-21_final
2024-02-28 12:04:24	ga_s2bm_ard_3-2-1_49KGP_2024-02-28_final
2024-02-28 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2024-02-28_final
2024-04-01 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2024-04-01_final
2024-04-11 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2024-04-11_final
2024-04-21 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2024-04-21_nrt

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

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