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
2018-05-03 12:13:20	ga_s2bm_ard_3-2-1_49KGQ_2018-05-03_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JGL_2018-10-20_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JHN_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49KHQ_2018-10-27_final.stac-item
2019-02-04 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2019-02-04_final.stac-item
2019-03-03 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2019-03-03_final.stac-item
2019-04-05 12:04:31	ga_s2bm_ard_3-2-1_49KHP_2019-04-05_final.stac-item
2019-06-14 12:04:06	ga_s2bm_ard_3-2-1_49KHR_2019-06-14_final.stac-item
2019-08-10 11:57:02	ga_s2bm_ard_3-2-1_50HLJ_2019-08-10_final.stac-item
2019-09-05 12:14:01	ga_s2bm_ard_3-2-1_49KGR_2019-09-05_final.stac-item
2019-09-19 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2019-09-19_final.stac-item
2019-09-22 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2019-09-22_final.stac-item
2019-09-22 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2019-09-22_final.stac-item
2019-09-25 12:14:09	ga_s2bm_ard_3-2-1_49KHQ_2019-09-25_final.stac-item
2019-10-02 12:04:19	ga_s2bm_ard_3-2-1_49KGQ_2019-10-02_final.stac-item
2020-04-02 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2020-04-02_final.stac-item
2020-04-09 12:04:15	ga_s2bm_ard_3-2-1_49KGQ_2020-04-09_final.stac-item
2020-04-29 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2020-04-29_final.stac-item
2020-05-13 11:46:52	ga_s2bm_ard_3-2-1_50HNJ_2020-05-13_final.stac-item
2020-06-08 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2020-06-08_final.stac-item
2020-07-11 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2020-07-11_final.stac-item
2020-07-21 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2020-07-21_final.stac-item
2020-07-21 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2020-07-21_final.stac-item
2020-07-28 12:04:02	ga_s2bm_ard_3-2-1_49KHR_2020-07-28_final.stac-item
2020-07-28 12:04:30	ga_s2bm_ard_3-2-1_49KHP_2020-07-28_final.stac-item
2020-08-24 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2020-08-24_final.stac-item
2020-09-23 11:56:53	ga_s2bm_ard_3-2-1_50HMJ_2020-09-23_final.stac-item
2020-09-23 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2020-09-23_final.stac-item
2020-10-03 11:56:58	ga_s2bm_ard_3-2-1_50HLJ_2020-10-03_final.stac-item
2021-04-01 11:56:49	ga_s2bm_ard_3-2-1_50HMJ_2021-04-01_final.stac-item
2021-05-07 12:13:52	ga_s2bm_ard_3-2-1_49KHR_2021-05-07_final.stac-item
2021-09-21 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2021-09-21_final.stac-item
2021-09-25 11:46:39	ga_s2bm_ard_3-2-1_50HMK_2021-09-25_final.stac-item
2021-10-08 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2021-10-08_final.stac-item
2021-11-04 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2021-11-04_final.stac-item
2021-11-04 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2021-11-04_final.stac-item
2022-01-03 11:47:02	ga_s2bm_ard_3-2-1_50HNH_2022-01-03_final.stac-item
2022-01-09 12:05:04	ga_s2bm_ard_3-2-1_49JFM_2022-01-09_final.stac-item
2022-01-13 11:47:02	ga_s2bm_ard_3-2-1_50HNH_2022-01-13_final.stac-item
2022-01-23 11:46:56	ga_s2bm_ard_3-2-1_50HNH_2022-01-23_final.stac-item
2022-02-02 11:46:56	ga_s2bm_ard_3-2-1_50HPH_2022-02-02_final.stac-item
2022-02-02 11:47:01	ga_s2bm_ard_3-2-1_50HNH_2022-02-02_final.stac-item
2022-02-12 11:47:02	ga_s2bm_ard_3-2-1_50HNH_2022-02-12_final.stac-item
2022-02-22 11:46:46	ga_s2bm_ard_3-2-1_50HNJ_2022-02-22_final.stac-item
2022-02-25 11:56:42	ga_s2bm_ard_3-2-1_50HLJ_2022-02-25_final.stac-item
2022-03-07 11:56:34	ga_s2bm_ard_3-2-1_50HMK_2022-03-07_final.stac-item
2022-04-06 11:56:52	ga_s2bm_ard_3-2-1_50HLJ_2022-04-06_final.stac-item
2022-04-16 11:56:26	ga_s2bm_ard_3-2-1_50HNK_2022-04-16_final.stac-item
2022-04-23 11:46:46	ga_s2bm_ard_3-2-1_50HNJ_2022-04-23_final.stac-item
2022-04-30 11:37:00	ga_s2bm_ard_3-2-1_50HPH_2022-04-30_final.stac-item
2022-05-02 12:13:52	ga_s2bm_ard_3-2-1_49KGR_2022-05-02_final.stac-item
2022-05-19 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2022-05-19_final.stac-item
2022-05-29 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2022-05-29_final.stac-item
2022-06-02 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2022-06-02_final.stac-item
2022-06-02 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2022-06-02_final.stac-item
2022-06-18 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-06-18_final.stac-item
2022-06-21 12:14:13	ga_s2bm_ard_3-2-1_49KHQ_2022-06-21_final.stac-item
2022-07-12 11:46:42	ga_s2bm_ard_3-2-1_50HNK_2022-07-12_final.stac-item
2022-07-21 12:14:13	ga_s2bm_ard_3-2-1_49KHQ_2022-07-21_final.stac-item
2022-08-07 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-08-07_final.stac-item
2022-08-11 11:46:44	ga_s2bm_ard_3-2-1_50HMK_2022-08-11_final.stac-item
2022-08-11 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2022-08-11_final.stac-item
2022-08-17 12:04:16	ga_s2bm_ard_3-2-1_49KHQ_2022-08-17_final.stac-item
2022-08-20 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2022-08-20_final.stac-item
2022-09-13 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2022-09-13_final.stac-item
2022-09-30 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2022-09-30_final.stac-item
2022-11-05 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2022-11-05_final.stac-item
2022-11-18 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2022-11-18_final.stac-item
2022-12-19 11:46:36	ga_s2bm_ard_3-2-1_50HNK_2022-12-19_final.stac-item
2022-12-28 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2022-12-28_final.stac-item
2023-01-08 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2023-01-08_final.stac-item
2023-01-28 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2023-01-28_final.stac-item
2023-04-28 11:46:57	ga_s2bm_ard_3-2-1_50HMJ_2023-04-28_final
2023-04-28 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2023-04-28_final
2023-05-18 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2023-05-18_final
2023-05-28 11:47:14	ga_s2bm_ard_3-2-1_50HMH_2023-05-28_final
2023-06-20 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2023-06-20_final
2023-06-27 11:47:00	ga_s2bm_ard_3-2-1_50HMJ_2023-06-27_final
2023-07-17 11:46:43	ga_s2bm_ard_3-2-1_50HNK_2023-07-17_final
2023-07-27 11:46:43	ga_s2bm_ard_3-2-1_50HNK_2023-07-27_final
2023-08-26 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2023-08-26_final
2023-09-08 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2023-09-08_final
2023-09-18 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2023-09-18_final
2023-10-08 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2023-10-08_final
2023-10-11 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2023-10-11_final
2023-10-14 12:14:15	ga_s2bm_ard_3-2-1_49KGQ_2023-10-14_final
2023-10-21 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2023-10-21_final
2023-11-03 12:13:57	ga_s2bm_ard_3-2-1_49KHR_2023-11-03_final
2023-11-10 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-11-10_final
2023-11-20 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2023-11-20_final
2023-11-23 12:14:08	ga_s2bm_ard_3-2-1_49KGQ_2023-11-23_final
2023-12-10 12:04:14	ga_s2bm_ard_3-2-1_49KGQ_2023-12-10_final
2023-12-13 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2023-12-13_final
2023-12-30 12:05:30	ga_s2bm_ard_3-2-1_49JGK_2023-12-30_final
2024-02-11 12:13:55	ga_s2bm_ard_3-2-1_49KHR_2024-02-11_final
2024-03-23 11:46:52	ga_s2bm_ard_3-2-1_50HNJ_2024-03-23_final
2024-04-02 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2024-04-02_final
2024-04-08 12:05:00	ga_s2bm_ard_3-2-1_49JGM_2024-04-08_final
2024-04-12 11:46:59	ga_s2bm_ard_3-2-1_50HNH_2024-04-12_final
2024-05-05 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2024-05-05_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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