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
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_49KGQ_2017-07-24_final.stac-item
2017-11-14 12:13:08	ga_s2bm_ard_3-2-1_49KHP_2017-11-14_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49KGQ_2017-12-21_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_49KHP_2017-12-31_final.stac-item
2018-01-13 12:13:13	ga_s2bm_ard_3-2-1_49KHP_2018-01-13_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_49KGQ_2018-01-20_final.stac-item
2018-01-30 12:02:42	ga_s2bm_ard_3-2-1_49KGQ_2018-01-30_final.stac-item
2018-01-30 12:02:42	ga_s2bm_ard_3-2-1_49KHQ_2018-01-30_final.stac-item
2018-02-12 12:13:14	ga_s2bm_ard_3-2-1_49KHP_2018-02-12_final.stac-item
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50HLK_2018-05-17_final.stac-item
2018-07-12 12:13:20	ga_s2bm_ard_3-2-1_49KHQ_2018-07-12_final.stac-item
2018-07-13 11:46:48	ga_s2bm_ard_3-2-1_50HMJ_2018-07-13_final.stac-item
2018-07-19 12:03:30	ga_s2bm_ard_3-2-1_49KHP_2018-07-19_final.stac-item
2018-09-20 12:13:14	ga_s2bm_ard_3-2-1_49KHR_2018-09-20_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49KGQ_2018-10-27_final.stac-item
2018-11-26 12:04:24	ga_s2bm_ard_3-2-1_49KHP_2018-11-26_final.stac-item
2018-12-06 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2018-12-06_final.stac-item
2019-02-24 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2019-02-24_final.stac-item
2019-03-09 12:14:02	ga_s2bm_ard_3-2-1_49KHQ_2019-03-09_final.stac-item
2019-03-16 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2019-03-16_final.stac-item
2019-06-21 11:57:14	ga_s2bm_ard_3-2-1_50HMH_2019-06-21_final.stac-item
2019-08-06 12:14:21	ga_s2bm_ard_3-2-1_49KGQ_2019-08-06_final.stac-item
2019-08-10 11:57:16	ga_s2bm_ard_3-2-1_50HLH_2019-08-10_final.stac-item
2019-08-26 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2019-08-26_final.stac-item
2019-12-28 11:56:35	ga_s2bm_ard_3-2-1_50HLK_2019-12-28_final.stac-item
2019-12-31 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2019-12-31_final.stac-item
2020-01-20 12:04:12	ga_s2bm_ard_3-2-1_49KGQ_2020-01-20_final.stac-item
2020-02-06 11:56:34	ga_s2bm_ard_3-2-1_50HLK_2020-02-06_final.stac-item
2020-02-09 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2020-02-09_final.stac-item
2020-05-03 11:46:52	ga_s2bm_ard_3-2-1_50HMJ_2020-05-03_final.stac-item
2020-05-19 12:04:18	ga_s2bm_ard_3-2-1_49KGQ_2020-05-19_final.stac-item
2020-05-29 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2020-05-29_final.stac-item
2020-07-31 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2020-07-31_final.stac-item
2020-08-01 11:46:58	ga_s2bm_ard_3-2-1_50HMJ_2020-08-01_final.stac-item
2020-08-17 12:04:22	ga_s2bm_ard_3-2-1_49KGQ_2020-08-17_final.stac-item
2020-08-20 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2020-08-20_final.stac-item
2020-08-31 11:46:59	ga_s2bm_ard_3-2-1_50HMJ_2020-08-31_final.stac-item
2020-10-06 12:04:53	ga_s2bm_ard_3-2-1_49JGN_2020-10-06_final.stac-item
2020-11-15 12:04:47	ga_s2bm_ard_3-2-1_49JGN_2020-11-15_final.stac-item
2020-12-08 12:14:19	ga_s2bm_ard_3-2-1_49KHP_2020-12-08_final.stac-item
2021-01-27 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2021-01-27_final.stac-item
2021-03-18 12:13:57	ga_s2bm_ard_3-2-1_49KGR_2021-03-18_final.stac-item
2021-03-28 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2021-03-28_final.stac-item
2021-04-04 12:04:11	ga_s2bm_ard_3-2-1_49KHQ_2021-04-04_final.stac-item
2021-07-26 12:14:23	ga_s2bm_ard_3-2-1_49KHP_2021-07-26_final.stac-item
2021-10-11 12:04:18	ga_s2bm_ard_3-2-1_49KGQ_2021-10-11_final.stac-item
2021-10-21 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2021-10-21_final.stac-item
2021-11-27 11:56:36	ga_s2bm_ard_3-2-1_50HLK_2021-11-27_final.stac-item
2022-01-09 12:04:09	ga_s2bm_ard_3-2-1_49KHQ_2022-01-09_final.stac-item
2022-01-19 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2022-01-19_final.stac-item
2022-01-26 11:56:34	ga_s2bm_ard_3-2-1_50HLK_2022-01-26_final.stac-item
2022-03-07 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-03-07_final.stac-item
2022-03-30 12:04:15	ga_s2bm_ard_3-2-1_49KGQ_2022-03-30_final.stac-item
2022-04-16 11:56:51	ga_s2bm_ard_3-2-1_50HLJ_2022-04-16_final.stac-item
2022-04-23 11:46:50	ga_s2bm_ard_3-2-1_50HMJ_2022-04-23_final.stac-item
2022-04-23 11:47:09	ga_s2bm_ard_3-2-1_50HLH_2022-04-23_final.stac-item
2022-05-09 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2022-05-09_final.stac-item
2022-05-26 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2022-05-26_final.stac-item
2022-06-01 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2022-06-01_final.stac-item
2022-06-05 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2022-06-05_final.stac-item
2022-08-14 11:56:58	ga_s2bm_ard_3-2-1_50HLJ_2022-08-14_final.stac-item
2022-08-24 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2022-08-24_final.stac-item
2022-08-24 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2022-08-24_final.stac-item
2022-08-31 11:46:56	ga_s2bm_ard_3-2-1_50HMJ_2022-08-31_final.stac-item
2022-09-23 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2022-09-23_final.stac-item
2022-09-26 12:04:19	ga_s2bm_ard_3-2-1_49KGQ_2022-09-26_final.stac-item
2022-09-30 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2022-09-30_final.stac-item
2022-10-06 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2022-10-06_final.stac-item
2022-10-29 12:14:07	ga_s2bm_ard_3-2-1_49KHQ_2022-10-29_final.stac-item
2022-11-15 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2022-11-15_final.stac-item
2022-12-15 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2022-12-15_final.stac-item
2022-12-19 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2022-12-19_final.stac-item
2022-12-25 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2022-12-25_final.stac-item
2022-12-29 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2022-12-29_final.stac-item
2023-01-04 12:04:26	ga_s2bm_ard_3-2-1_49KHP_2023-01-04_final.stac-item
2023-02-03 12:04:10	ga_s2bm_ard_3-2-1_49KHQ_2023-02-03_final.stac-item
2023-03-09 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2023-03-09_final
2023-05-04 12:04:16	ga_s2bm_ard_3-2-1_49KHQ_2023-05-04_final
2023-05-14 12:04:17	ga_s2bm_ard_3-2-1_49KHQ_2023-05-14_final
2023-06-27 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2023-06-27_final
2023-07-03 12:04:19	ga_s2bm_ard_3-2-1_49KHQ_2023-07-03_final
2023-07-03 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2023-07-03_final
2023-08-16 11:47:15	ga_s2bm_ard_3-2-1_50HMH_2023-08-16_final
2023-08-22 12:04:32	ga_s2bm_ard_3-2-1_49KHP_2023-08-22_final
2023-09-01 12:04:18	ga_s2bm_ard_3-2-1_49KHQ_2023-09-01_final
2023-09-11 12:04:17	ga_s2bm_ard_3-2-1_49KHQ_2023-09-11_final
2023-10-01 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2023-10-01_final
2023-10-04 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2023-10-04_final
2023-10-11 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2023-10-11_final
2023-10-15 11:47:30	ga_s2bm_ard_3-2-1_50HLG_2023-10-15_final
2023-10-31 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2023-10-31_final
2023-11-07 11:56:43	ga_s2bm_ard_3-2-1_50HLK_2023-11-07_final
2023-11-20 12:04:11	ga_s2bm_ard_3-2-1_49KHQ_2023-11-20_final
2023-12-20 12:04:28	ga_s2bm_ard_3-2-1_49KHP_2023-12-20_final
2024-01-06 11:57:19	ga_s2bm_ard_3-2-1_50HMG_2024-01-06_final
2024-02-18 12:04:14	ga_s2bm_ard_3-2-1_49KHQ_2024-02-18_final
2024-03-12 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2024-03-12_final
2024-03-16 11:57:18	ga_s2bm_ard_3-2-1_50HMG_2024-03-16_final
2024-03-29 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2024-03-29_final
2024-03-29 12:04:18	ga_s2bm_ard_3-2-1_49KGQ_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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