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 12:04:34	ga_s2bm_ard_3-2-1_50JKS_2017-07-04_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_49JGN_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JKS_2017-07-14_final.stac-item
2017-08-03 12:04:41	ga_s2bm_ard_3-2-1_50JKS_2017-08-03_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLQ_2017-11-01_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HQK_2017-11-22_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_50JLQ_2017-12-21_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JLQ_2017-12-28_final.stac-item
2018-01-07 11:50:37	ga_s2bm_ard_3-2-1_50JLQ_2018-01-07_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49JGN_2018-01-10_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_50JLQ_2018-01-10_final.stac-item
2018-02-02 12:13:14	ga_s2bm_ard_3-2-1_49KHP_2018-02-02_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JLQ_2018-04-07_final.stac-item
2018-06-09 12:02:47	ga_s2bm_ard_3-2-1_50JKR_2018-06-09_final.stac-item
2018-06-29 12:02:48	ga_s2bm_ard_3-2-1_50JLQ_2018-06-29_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_50JLQ_2018-07-09_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_50JLR_2018-07-09_final.stac-item
2018-07-19 12:03:30	ga_s2bm_ard_3-2-1_50JKR_2018-07-19_final.stac-item
2018-07-29 12:02:46	ga_s2bm_ard_3-2-1_50JLR_2018-07-29_final.stac-item
2018-07-29 12:04:59	ga_s2bm_ard_3-2-1_50JLQ_2018-07-29_final.stac-item
2018-07-29 12:04:59	ga_s2bm_ard_3-2-1_50JLR_2018-07-29_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JKR_2018-08-08_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JLQ_2018-08-08_final.stac-item
2019-02-14 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2019-02-14_final.stac-item
2019-02-15 11:36:29	ga_s2bm_ard_3-2-1_50HQK_2019-02-15_final.stac-item
2019-02-24 12:05:22	ga_s2bm_ard_3-2-1_50JKQ_2019-02-24_final.stac-item
2019-02-25 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2019-02-25_final.stac-item
2019-03-16 12:04:40	ga_s2bm_ard_3-2-1_50JKT_2019-03-16_final.stac-item
2019-03-16 12:05:10	ga_s2bm_ard_3-2-1_50JKR_2019-03-16_final.stac-item
2019-03-26 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2019-03-26_final.stac-item
2019-04-25 12:05:15	ga_s2bm_ard_3-2-1_50JLR_2019-04-25_final.stac-item
2019-05-05 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-05-05_final.stac-item
2019-06-14 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-17 12:14:29	ga_s2bm_ard_3-2-1_49KHP_2019-06-17_final.stac-item
2019-08-03 12:05:30	ga_s2bm_ard_3-2-1_50JLQ_2019-08-03_final.stac-item
2019-09-12 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2019-09-12_final.stac-item
2019-09-23 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2019-09-23_final.stac-item
2019-09-29 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2019-09-29_final.stac-item
2019-10-09 11:55:28	ga_s2bm_ard_3-2-1_50JLQ_2019-10-09_final.stac-item
2019-11-12 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2019-11-12_final.stac-item
2019-12-08 11:55:21	ga_s2bm_ard_3-2-1_50JLQ_2019-12-08_final.stac-item
2019-12-12 11:36:36	ga_s2bm_ard_3-2-1_50HQJ_2019-12-12_final.stac-item
2019-12-15 11:46:18	ga_s2bm_ard_3-2-1_50HPK_2019-12-15_final.stac-item
2020-01-20 12:05:16	ga_s2bm_ard_3-2-1_50JLQ_2020-01-20_final.stac-item
2020-02-06 11:55:21	ga_s2bm_ard_3-2-1_50JLQ_2020-02-06_final.stac-item
2020-03-07 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2020-03-07_final.stac-item
2020-03-07 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2020-03-07_final.stac-item
2020-03-27 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2020-03-27_final.stac-item
2020-04-29 12:05:18	ga_s2bm_ard_3-2-1_50JLQ_2020-04-29_final.stac-item
2020-05-16 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2020-05-16_final.stac-item
2020-05-19 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2020-05-19_final.stac-item
2020-05-19 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2020-05-19_final.stac-item
2020-06-08 12:05:22	ga_s2bm_ard_3-2-1_49JGK_2020-06-08_final.stac-item
2020-07-18 12:05:21	ga_s2bm_ard_3-2-1_50JKQ_2020-07-18_final.stac-item
2020-07-25 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2020-07-25_final.stac-item
2020-07-25 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2020-07-25_final.stac-item
2020-07-28 12:05:14	ga_s2bm_ard_3-2-1_50JKR_2020-07-28_final.stac-item
2020-09-03 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2020-09-03_final.stac-item
2020-09-06 12:04:51	ga_s2bm_ard_3-2-1_50JKT_2020-09-06_final.stac-item
2020-09-06 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2020-09-06_final.stac-item
2021-03-22 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2021-03-22_final.stac-item
2021-04-04 12:04:20	ga_s2bm_ard_3-2-1_49KGP_2021-04-04_final.stac-item
2021-04-04 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2021-04-04_final.stac-item
2021-04-04 12:05:09	ga_s2bm_ard_3-2-1_50JKR_2021-04-04_final.stac-item
2021-09-05 11:47:24	ga_s2bm_ard_3-2-1_50HLG_2021-09-05_final
2021-09-08 11:55:24	ga_s2bm_ard_3-2-1_50JLQ_2021-09-08_final.stac-item
2021-09-21 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2021-09-21_final.stac-item
2022-01-03 11:46:20	ga_s2bm_ard_3-2-1_50HPK_2022-01-03_final.stac-item
2022-01-16 11:55:23	ga_s2bm_ard_3-2-1_50JLQ_2022-01-16_final.stac-item
2022-01-19 12:05:18	ga_s2bm_ard_3-2-1_50JLQ_2022-01-19_final.stac-item
2022-02-05 11:55:07	ga_s2bm_ard_3-2-1_50JLR_2022-02-05_final.stac-item
2022-02-05 11:55:22	ga_s2bm_ard_3-2-1_50JLQ_2022-02-05_final.stac-item
2022-02-08 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2022-02-08_final.stac-item
2022-03-17 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2022-03-17_final.stac-item
2022-05-09 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2022-05-09_final.stac-item
2022-09-23 11:55:28	ga_s2bm_ard_3-2-1_50JLQ_2022-09-23_final.stac-item
2022-11-12 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2022-11-12_final.stac-item
2023-01-14 12:05:19	ga_s2bm_ard_3-2-1_50JLQ_2023-01-14_final.stac-item
2023-02-27 11:47:28	ga_s2bm_ard_3-2-1_50HLG_2023-02-27_final
2023-05-04 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2023-05-04_final
2023-05-04 12:04:36	ga_s2bm_ard_3-2-1_50JKT_2023-05-04_final
2023-05-04 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-05-04_final
2023-05-11 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2023-05-11_final
2023-05-14 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2023-05-14_final
2023-06-10 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-06-10_final
2023-06-30 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-06-30_final
2023-07-13 12:05:16	ga_s2bm_ard_3-2-1_50JKR_2023-07-13_final
2023-08-09 11:55:33	ga_s2bm_ard_3-2-1_50JLQ_2023-08-09_final
2023-08-19 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-08-19_final
2023-08-22 12:05:16	ga_s2bm_ard_3-2-1_50JKR_2023-08-22_final
2023-08-29 11:55:17	ga_s2bm_ard_3-2-1_50JLR_2023-08-29_final
2023-09-01 12:05:32	ga_s2bm_ard_3-2-1_50JLQ_2023-09-01_final
2023-09-11 12:05:24	ga_s2bm_ard_3-2-1_50JKQ_2023-09-11_final
2023-10-01 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-10-01_final
2023-10-11 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2023-10-11_final
2023-10-31 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-10-31_final
2023-11-30 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2023-11-30_final
2024-01-26 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2024-01-26_final
2024-03-19 12:05:22	ga_s2bm_ard_3-2-1_50JLQ_2024-03-19_final
2024-03-29 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_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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