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
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50HMH_2018-05-17_final.stac-item
2018-06-03 11:40:10	ga_s2bm_ard_3-2-1_50HPH_2018-06-03_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50HLH_2018-06-23_final.stac-item
2018-08-01 12:13:25	ga_s2bm_ard_3-2-1_49KHP_2018-08-01_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50HNK_2018-09-24_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50HLJ_2018-10-04_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49KHQ_2018-10-10_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49KHP_2018-10-17_final.stac-item
2018-11-16 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2018-11-16_final.stac-item
2018-11-16 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2018-11-16_final.stac-item
2018-11-16 12:05:06	ga_s2bm_ard_3-2-1_49JFM_2018-11-16_final.stac-item
2019-07-31 11:57:03	ga_s2bm_ard_3-2-1_50HLJ_2019-07-31_final.stac-item
2019-08-03 12:04:26	ga_s2bm_ard_3-2-1_49KGQ_2019-08-03_final.stac-item
2019-08-06 12:14:06	ga_s2bm_ard_3-2-1_49KGR_2019-08-06_final.stac-item
2019-08-10 11:57:02	ga_s2bm_ard_3-2-1_50HLJ_2019-08-10_final.stac-item
2019-09-15 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2019-09-15_final.stac-item
2019-09-15 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-09-15_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
2019-11-08 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2019-11-08_final.stac-item
2019-12-04 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2019-12-04_final.stac-item
2019-12-12 11:36:38	ga_s2bm_ard_3-2-1_50HPJ_2019-12-12_final.stac-item
2020-04-22 12:13:49	ga_s2bm_ard_3-2-1_49KHR_2020-04-22_final.stac-item
2020-05-02 12:14:07	ga_s2bm_ard_3-2-1_49KHQ_2020-05-02_final.stac-item
2020-07-21 12:14:33	ga_s2bm_ard_3-2-1_49JHN_2020-07-21_final.stac-item
2020-08-30 12:14:02	ga_s2bm_ard_3-2-1_49KGR_2020-08-30_final.stac-item
2020-09-13 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2020-09-13_final.stac-item
2020-09-13 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2020-09-13_final.stac-item
2020-09-16 12:04:30	ga_s2bm_ard_3-2-1_49KHP_2020-09-16_final.stac-item
2020-09-16 12:04:50	ga_s2bm_ard_3-2-1_49JHM_2020-09-16_final.stac-item
2020-09-19 12:14:10	ga_s2bm_ard_3-2-1_49KHQ_2020-09-19_final.stac-item
2020-09-19 12:14:23	ga_s2bm_ard_3-2-1_49KHP_2020-09-19_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
2020-11-12 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2020-11-12_final.stac-item
2020-11-15 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2020-11-15_final.stac-item
2020-11-15 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2020-11-15_final.stac-item
2021-01-21 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2021-01-21_final.stac-item
2021-03-02 11:56:35	ga_s2bm_ard_3-2-1_50HMK_2021-03-02_final.stac-item
2021-08-29 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2021-08-29_final.stac-item
2021-09-04 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2021-09-04_final.stac-item
2021-10-28 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2021-10-28_final.stac-item
2021-11-07 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2021-11-07_final.stac-item
2021-11-23 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2021-11-23_final.stac-item
2021-11-24 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2021-11-24_final.stac-item
2021-11-27 11:56:36	ga_s2bm_ard_3-2-1_50HLK_2021-11-27_final.stac-item
2021-12-24 11:46:43	ga_s2bm_ard_3-2-1_50HPJ_2021-12-24_final.stac-item
2022-01-16 11:56:32	ga_s2bm_ard_3-2-1_50HMK_2022-01-16_final.stac-item
2022-01-22 12:14:04	ga_s2bm_ard_3-2-1_49KHQ_2022-01-22_final.stac-item
2022-01-23 11:46:43	ga_s2bm_ard_3-2-1_50HPJ_2022-01-23_final.stac-item
2022-01-23 11:46:56	ga_s2bm_ard_3-2-1_50HNH_2022-01-23_final.stac-item
2022-02-01 12:14:15	ga_s2bm_ard_3-2-1_49KHP_2022-02-01_final.stac-item
2022-02-02 11:46:46	ga_s2bm_ard_3-2-1_50HNJ_2022-02-02_final.stac-item
2022-02-08 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2022-02-08_final.stac-item
2022-03-03 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2022-03-03_final.stac-item
2022-03-03 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2022-03-03_final.stac-item
2022-03-14 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2022-03-14_final.stac-item
2022-03-17 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2022-03-17_final.stac-item
2022-04-06 11:56:33	ga_s2bm_ard_3-2-1_50HMK_2022-04-06_final.stac-item
2022-05-06 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2022-05-06_final.stac-item
2022-05-16 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2022-05-16_final.stac-item
2022-05-26 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2022-05-26_final.stac-item
2022-06-01 12:13:58	ga_s2bm_ard_3-2-1_49KGR_2022-06-01_final.stac-item
2022-06-01 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_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
2022-06-21 12:14:03	ga_s2bm_ard_3-2-1_49KGR_2022-06-21_final.stac-item
2022-06-25 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2022-06-25_final.stac-item
2022-06-25 11:56:56	ga_s2bm_ard_3-2-1_50HMJ_2022-06-25_final.stac-item
2022-07-12 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2022-07-12_final.stac-item
2022-08-11 11:47:13	ga_s2bm_ard_3-2-1_50HMH_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
2022-08-24 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2022-08-24_final.stac-item
2022-09-23 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2022-09-23_final.stac-item
2022-12-12 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2022-12-12_final.stac-item
2022-12-22 11:56:36	ga_s2bm_ard_3-2-1_50HMK_2022-12-22_final.stac-item
2023-01-31 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2023-01-31_final.stac-item
2023-02-06 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2023-02-06_final
2023-04-21 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2023-04-21_final
2023-04-21 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2023-04-21_final
2023-05-08 11:47:05	ga_s2bm_ard_3-2-1_50HPH_2023-05-08_final
2023-05-11 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2023-05-11_final
2023-05-11 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2023-05-11_final
2023-05-14 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2023-05-14_final
2023-05-18 11:47:14	ga_s2bm_ard_3-2-1_50HMH_2023-05-18_final
2023-05-21 11:57:14	ga_s2bm_ard_3-2-1_50HLH_2023-05-21_final
2023-06-27 11:47:00	ga_s2bm_ard_3-2-1_50HMJ_2023-06-27_final
2023-06-30 11:56:42	ga_s2bm_ard_3-2-1_50HMK_2023-06-30_final
2023-08-26 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2023-08-26_final
2023-08-29 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2023-08-29_final
2023-10-05 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2023-10-05_final
2023-10-05 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2023-10-05_final
2023-10-18 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2023-10-18_final
2023-10-25 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2023-10-25_final
2023-11-17 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2023-11-17_final
2023-11-21 11:37:03	ga_s2bm_ard_3-2-1_50HPH_2023-11-21_final
2023-12-24 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2023-12-24_final
2024-01-20 11:37:06	ga_s2bm_ard_3-2-1_50HPH_2024-01-20_final
2024-02-11 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2024-02-11_final
2024-03-26 11:57:21	ga_s2bm_ard_3-2-1_50HLG_2024-03-26_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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