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
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JKQ_2017-07-14_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_50JLR_2017-10-02_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKR_2017-11-01_final.stac-item
2018-01-04 11:37:43	ga_s2bm_ard_3-2-1_50HQH_2018-01-04_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLR_2018-03-21_final.stac-item
2018-03-28 11:51:53	ga_s2bm_ard_3-2-1_50JLR_2018-03-28_final.stac-item
2018-04-20 12:04:00	ga_s2bm_ard_3-2-1_50JKR_2018-04-20_final.stac-item
2018-07-12 12:13:20	ga_s2bm_ard_3-2-1_49KHP_2018-07-12_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JKR_2018-08-08_final.stac-item
2018-09-20 12:13:54	ga_s2bm_ard_3-2-1_49KHP_2018-09-20_final.stac-item
2019-01-08 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2019-01-08_final.stac-item
2019-02-11 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2019-02-11_final.stac-item
2019-02-14 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2019-02-14_final.stac-item
2019-05-08 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2019-05-08_final.stac-item
2019-05-08 12:14:29	ga_s2bm_ard_3-2-1_49KHP_2019-05-08_final.stac-item
2019-06-04 12:05:16	ga_s2bm_ard_3-2-1_50JLR_2019-06-04_final.stac-item
2019-09-12 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2019-09-12_final.stac-item
2019-09-22 12:05:22	ga_s2bm_ard_3-2-1_50JLQ_2019-09-22_final.stac-item
2019-09-29 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2019-09-29_final.stac-item
2019-11-18 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2019-11-18_final.stac-item
2019-11-21 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2019-11-21_final.stac-item
2019-12-21 12:05:07	ga_s2bm_ard_3-2-1_50JKR_2019-12-21_final.stac-item
2020-01-20 12:05:02	ga_s2bm_ard_3-2-1_50JLR_2020-01-20_final.stac-item
2020-02-03 11:46:47	ga_s2bm_ard_3-2-1_50HQH_2020-02-03_final.stac-item
2020-04-09 12:05:16	ga_s2bm_ard_3-2-1_50JLQ_2020-04-09_final.stac-item
2020-05-13 11:46:52	ga_s2bm_ard_3-2-1_50HQH_2020-05-13_final.stac-item
2020-07-25 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2020-07-25_final.stac-item
2020-09-06 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2020-09-06_final.stac-item
2020-10-13 11:55:31	ga_s2bm_ard_3-2-1_50JLQ_2020-10-13_final.stac-item
2020-10-26 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2020-10-26_final.stac-item
2020-11-05 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2020-11-05_final.stac-item
2020-12-25 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2020-12-25_final.stac-item
2020-12-25 12:05:09	ga_s2bm_ard_3-2-1_50JKR_2020-12-25_final.stac-item
2021-01-01 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2021-01-01_final.stac-item
2021-01-27 12:13:40	ga_s2bm_ard_3-2-1_49KHS_2021-01-27_final
2021-02-26 12:14:30	ga_s2bm_ard_3-2-1_49JGN_2021-02-26_final.stac-item
2021-03-05 12:04:46	ga_s2bm_ard_3-2-1_49JHM_2021-03-05_final.stac-item
2021-05-28 11:46:54	ga_s2bm_ard_3-2-1_50HQH_2021-05-28_final.stac-item
2021-07-03 12:04:24	ga_s2bm_ard_3-2-1_49KGP_2021-07-03_final.stac-item
2021-08-06 11:47:29	ga_s2bm_ard_3-2-1_50HLG_2021-08-06_final
2021-08-12 12:04:23	ga_s2bm_ard_3-2-1_49KGP_2021-08-12_final.stac-item
2021-08-12 12:04:48	ga_s2bm_ard_3-2-1_49JHM_2021-08-12_final.stac-item
2021-08-12 12:05:12	ga_s2bm_ard_3-2-1_50JKR_2021-08-12_final.stac-item
2021-10-18 11:55:29	ga_s2bm_ard_3-2-1_50JLQ_2021-10-18_final.stac-item
2021-10-21 12:04:49	ga_s2bm_ard_3-2-1_50JKS_2021-10-21_final.stac-item
2021-11-10 12:03:44	ga_s2bm_ard_3-2-1_49KHS_2021-11-10_final
2021-11-30 12:03:40	ga_s2bm_ard_3-2-1_49KHS_2021-11-30_final
2021-12-23 12:14:16	ga_s2bm_ard_3-2-1_49KHP_2021-12-23_final.stac-item
2021-12-30 12:05:04	ga_s2bm_ard_3-2-1_50JLR_2021-12-30_final.stac-item
2022-01-02 12:14:17	ga_s2bm_ard_3-2-1_49KHP_2022-01-02_final.stac-item
2022-01-06 11:55:09	ga_s2bm_ard_3-2-1_50JLR_2022-01-06_final.stac-item
2022-01-06 11:55:23	ga_s2bm_ard_3-2-1_50JLQ_2022-01-06_final.stac-item
2022-01-09 12:04:50	ga_s2bm_ard_3-2-1_50JLS_2022-01-09_final.stac-item
2022-01-12 12:14:17	ga_s2bm_ard_3-2-1_49KHP_2022-01-12_final.stac-item
2022-01-19 12:04:49	ga_s2bm_ard_3-2-1_50JLS_2022-01-19_final.stac-item
2022-01-29 12:05:06	ga_s2bm_ard_3-2-1_50JKR_2022-01-29_final.stac-item
2022-02-01 12:14:15	ga_s2bm_ard_3-2-1_49KHP_2022-02-01_final.stac-item
2022-02-08 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2022-02-08_final.stac-item
2022-03-10 12:05:21	ga_s2bm_ard_3-2-1_50JLQ_2022-03-10_final.stac-item
2022-03-17 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2022-03-17_final.stac-item
2022-03-20 12:04:52	ga_s2bm_ard_3-2-1_50JLS_2022-03-20_final.stac-item
2022-04-19 12:05:07	ga_s2bm_ard_3-2-1_50JKR_2022-04-19_final.stac-item
2022-05-09 12:04:51	ga_s2bm_ard_3-2-1_50JLS_2022-05-09_final.stac-item
2022-07-25 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2022-07-25_final.stac-item
2022-08-14 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2022-08-14_final.stac-item
2022-09-26 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2022-09-26_final.stac-item
2022-10-23 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-10-23_final.stac-item
2022-11-02 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2022-11-02_final.stac-item
2022-12-22 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2022-12-22_final.stac-item
2022-12-25 12:04:53	ga_s2bm_ard_3-2-1_50JLS_2022-12-25_final.stac-item
2023-01-08 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2023-01-08_final.stac-item
2023-01-08 11:47:14	ga_s2bm_ard_3-2-1_50HPG_2023-01-08_final
2023-01-24 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2023-01-24_final.stac-item
2023-03-08 12:14:24	ga_s2bm_ard_3-2-1_49KHP_2023-03-08_final
2023-04-21 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2023-04-21_final
2023-05-17 12:14:25	ga_s2bm_ard_3-2-1_49KHP_2023-05-17_final
2023-05-21 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-05-21_final
2023-05-27 12:14:25	ga_s2bm_ard_3-2-1_49KHP_2023-05-27_final
2023-06-30 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-06-30_final
2023-08-02 12:03:49	ga_s2bm_ard_3-2-1_49KHS_2023-08-02_final
2023-08-12 12:04:53	ga_s2bm_ard_3-2-1_50JLS_2023-08-12_final
2023-08-15 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-08-15_final
2023-08-22 12:03:49	ga_s2bm_ard_3-2-1_49KHS_2023-08-22_final
2023-08-22 12:04:58	ga_s2bm_ard_3-2-1_50JLS_2023-08-22_final
2023-08-22 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_2023-08-22_final
2023-08-22 12:05:24	ga_s2bm_ard_3-2-1_50JKR_2023-08-22_final
2023-09-01 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-09-01_final
2023-09-11 12:05:22	ga_s2bm_ard_3-2-1_50JLQ_2023-09-11_final
2023-09-25 11:47:30	ga_s2bm_ard_3-2-1_50HLG_2023-09-25_final
2023-10-15 11:46:56	ga_s2bm_ard_3-2-1_50HQH_2023-10-15_final
2023-10-24 12:14:18	ga_s2bm_ard_3-2-1_49KHQ_2023-10-24_final
2023-10-31 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2023-10-31_final
2023-11-17 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2023-11-17_final
2023-11-30 12:05:07	ga_s2bm_ard_3-2-1_50JLR_2023-11-30_final
2023-12-20 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2023-12-20_final
2024-01-06 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2024-01-06_final
2024-02-05 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2024-02-05_final
2024-02-18 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2024-02-18_final
2024-03-12 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2024-03-12_final
2024-04-01 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2024-04-01_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

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