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
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50HQH_2017-09-16_final.stac-item
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50HLH_2017-09-29_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50HLH_2017-10-19_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50HMH_2017-11-25_final.stac-item
2018-01-01 11:35:58	ga_s2bm_ard_3-2-1_50HPK_2018-01-01_final.stac-item
2018-01-04 11:37:43	ga_s2bm_ard_3-2-1_50HNJ_2018-01-04_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_49JGL_2018-01-20_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50HNK_2018-02-13_final.stac-item
2018-02-16 11:54:55	ga_s2bm_ard_3-2-1_50HMK_2018-02-16_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JKP_2018-04-07_final.stac-item
2018-05-10 12:02:48	ga_s2bm_ard_3-2-1_49JHN_2018-05-10_final.stac-item
2018-05-13 12:14:07	ga_s2bm_ard_3-2-1_49JGN_2018-05-13_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JKQ_2018-05-20_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JLM_2018-05-20_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_50JKR_2018-06-19_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_49KHR_2018-07-09_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50HLJ_2018-09-14_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50HMK_2018-09-21_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50HLH_2018-09-24_final.stac-item
2018-11-30 11:46:51	ga_s2bm_ard_3-2-1_50HMJ_2018-11-30_final.stac-item
2018-12-03 11:56:46	ga_s2bm_ard_3-2-1_50HMJ_2018-12-03_final.stac-item
2018-12-10 11:46:49	ga_s2bm_ard_3-2-1_50HMJ_2018-12-10_final.stac-item
2019-01-22 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2019-01-22_final.stac-item
2019-02-01 11:56:14	ga_s2bm_ard_3-2-1_50JKM_2019-02-01_final.stac-item
2019-02-27 12:14:55	ga_s2bm_ard_3-2-1_49JGM_2019-02-27_final.stac-item
2019-04-25 12:05:36	ga_s2bm_ard_3-2-1_49JGK_2019-04-25_final.stac-item
2019-04-25 12:06:11	ga_s2bm_ard_3-2-1_50JLM_2019-04-25_final.stac-item
2019-05-12 11:56:08	ga_s2bm_ard_3-2-1_50JKN_2019-05-12_final.stac-item
2019-06-21 11:56:38	ga_s2bm_ard_3-2-1_50HNK_2019-06-21_final.stac-item
2019-06-24 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-06-24_final.stac-item
2019-08-06 12:14:49	ga_s2bm_ard_3-2-1_49JGN_2019-08-06_final.stac-item
2019-09-25 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2019-09-25_final.stac-item
2019-10-09 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2019-10-09_final.stac-item
2019-10-09 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2019-10-09_final.stac-item
2019-11-08 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2019-11-08_final.stac-item
2019-11-15 11:47:05	ga_s2bm_ard_3-2-1_50HNH_2019-11-15_final.stac-item
2020-02-19 12:04:27	ga_s2bm_ard_3-2-1_49KGP_2020-02-19_final.stac-item
2020-03-27 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2020-03-27_final.stac-item
2020-04-03 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2020-04-03_final.stac-item
2020-04-03 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2020-04-03_final.stac-item
2020-04-06 11:56:08	ga_s2bm_ard_3-2-1_50JLM_2020-04-06_final.stac-item
2020-04-06 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2020-04-06_final.stac-item
2020-05-02 12:15:07	ga_s2bm_ard_3-2-1_49JGL_2020-05-02_final.stac-item
2020-05-20 11:36:52	ga_s2bm_ard_3-2-1_50HPJ_2020-05-20_final.stac-item
2020-05-22 12:13:59	ga_s2bm_ard_3-2-1_49KGR_2020-05-22_final.stac-item
2020-06-12 11:46:32	ga_s2bm_ard_3-2-1_50HQK_2020-06-12_final.stac-item
2020-06-18 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2020-06-18_final.stac-item
2020-07-28 12:06:12	ga_s2bm_ard_3-2-1_50JKM_2020-07-28_final.stac-item
2020-07-29 11:36:54	ga_s2bm_ard_3-2-1_50HPJ_2020-07-29_final.stac-item
2020-11-19 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2020-11-19_final.stac-item
2020-11-22 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2020-11-22_final.stac-item
2020-11-22 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2020-11-22_final.stac-item
2021-02-04 11:37:26	ga_s2bm_ard_3-2-1_50HNG_2021-02-04_final
2021-04-15 11:36:48	ga_s2bm_ard_3-2-1_50HPJ_2021-04-15_final.stac-item
2021-07-10 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2021-07-10_final.stac-item
2021-09-25 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2021-09-25_final.stac-item
2021-10-31 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2021-10-31_final.stac-item
2021-11-17 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2021-11-17_final.stac-item
2021-11-27 11:56:47	ga_s2bm_ard_3-2-1_50HMJ_2021-11-27_final.stac-item
2021-11-30 12:05:51	ga_s2bm_ard_3-2-1_50JKN_2021-11-30_final.stac-item
2021-12-30 12:03:40	ga_s2bm_ard_3-2-1_49KHS_2021-12-30_final
2022-01-16 11:55:55	ga_s2bm_ard_3-2-1_50JKN_2022-01-16_final.stac-item
2022-01-23 11:46:57	ga_s2bm_ard_3-2-1_50HMH_2022-01-23_final.stac-item
2022-02-09 11:36:46	ga_s2bm_ard_3-2-1_50HPJ_2022-02-09_final.stac-item
2022-04-06 11:56:48	ga_s2bm_ard_3-2-1_50HMJ_2022-04-06_final.stac-item
2022-04-23 11:46:50	ga_s2bm_ard_3-2-1_50HMJ_2022-04-23_final.stac-item
2022-04-26 11:56:59	ga_s2bm_ard_3-2-1_50HMH_2022-04-26_final.stac-item
2022-05-29 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2022-05-29_final.stac-item
2022-11-18 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2022-11-18_final.stac-item
2022-12-22 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2022-12-22_final.stac-item
2023-03-28 12:15:03	ga_s2bm_ard_3-2-1_49JFM_2023-03-28_final
2023-06-03 12:05:45	ga_s2bm_ard_3-2-1_50JKP_2023-06-03_final
2023-06-16 12:15:01	ga_s2bm_ard_3-2-1_49JGM_2023-06-16_final
2023-07-13 12:05:19	ga_s2bm_ard_3-2-1_49JGL_2023-07-13_final
2023-07-16 12:15:05	ga_s2bm_ard_3-2-1_49JFM_2023-07-16_final
2023-08-09 11:56:31	ga_s2bm_ard_3-2-1_50JLL_2023-08-09_final
2023-08-22 12:05:19	ga_s2bm_ard_3-2-1_49JGL_2023-08-22_final
2023-09-01 12:05:05	ga_s2bm_ard_3-2-1_49JGM_2023-09-01_final
2023-09-11 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-09-11_final
2023-09-21 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-09-21_final
2023-10-01 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2023-10-01_final
2023-10-04 12:13:59	ga_s2bm_ard_3-2-1_49KGR_2023-10-04_final
2023-10-08 11:57:20	ga_s2bm_ard_3-2-1_50HMG_2023-10-08_final
2023-10-28 11:56:38	ga_s2bm_ard_3-2-1_50HMK_2023-10-28_final
2023-11-03 12:15:13	ga_s2bm_ard_3-2-1_49JGL_2023-11-03_final
2023-11-13 12:13:59	ga_s2bm_ard_3-2-1_49KGR_2023-11-13_final
2023-11-24 11:47:01	ga_s2bm_ard_3-2-1_50HNH_2023-11-24_final
2023-11-30 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-11-30_final
2023-12-10 12:04:10	ga_s2bm_ard_3-2-1_49KHQ_2023-12-10_final
2023-12-14 11:46:36	ga_s2bm_ard_3-2-1_50HNK_2023-12-14_final
2024-01-02 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2024-01-02_final
2024-01-23 11:47:27	ga_s2bm_ard_3-2-1_50HLG_2024-01-23_final
2024-02-12 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2024-02-12_final
2024-02-18 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2024-02-18_final
2024-02-21 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2024-02-21_final
2024-02-28 12:05:13	ga_s2bm_ard_3-2-1_49JGL_2024-02-28_final
2024-03-16 11:56:35	ga_s2bm_ard_3-2-1_50HMK_2024-03-16_final
2024-03-19 12:05:55	ga_s2bm_ard_3-2-1_50JKN_2024-03-19_final
2024-03-26 11:56:14	ga_s2bm_ard_3-2-1_50JKM_2024-03-26_final
2024-04-05 11:56:28	ga_s2bm_ard_3-2-1_50HNK_2024-04-05_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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