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_49JGM_2017-07-04_final.stac-item
2017-07-18 11:45:05	ga_s2bm_ard_3-2-1_50HNJ_2017-07-18_final.stac-item
2017-09-03 11:30:07	ga_s2bm_ard_3-2-1_50HPK_2017-09-03_final.stac-item
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50HNJ_2017-10-06_final.stac-item
2017-10-25 12:13:08	ga_s2bm_ard_3-2-1_49JGM_2017-10-25_final.stac-item
2017-10-25 12:13:08	ga_s2bm_ard_3-2-1_49KGQ_2017-10-25_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50HMH_2017-12-25_final.stac-item
2018-01-24 11:37:42	ga_s2bm_ard_3-2-1_50HPH_2018-01-24_final.stac-item
2018-02-12 12:13:14	ga_s2bm_ard_3-2-1_49KGR_2018-02-12_final.stac-item
2018-03-28 11:51:53	ga_s2bm_ard_3-2-1_50HLK_2018-03-28_final.stac-item
2018-04-03 12:13:18	ga_s2bm_ard_3-2-1_49KGQ_2018-04-03_final.stac-item
2018-06-13 11:43:22	ga_s2bm_ard_3-2-1_50HPK_2018-06-13_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50HMH_2018-08-05_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50JKP_2018-10-14_final.stac-item
2018-10-31 11:39:52	ga_s2bm_ard_3-2-1_50HPK_2018-10-31_final.stac-item
2018-11-06 12:05:27	ga_s2bm_ard_3-2-1_49JGK_2018-11-06_final.stac-item
2018-11-23 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2018-11-23_final.stac-item
2018-12-09 12:14:35	ga_s2bm_ard_3-2-1_49JGN_2018-12-09_final.stac-item
2019-01-05 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2019-01-05_final.stac-item
2019-01-08 12:13:57	ga_s2bm_ard_3-2-1_49KGR_2019-01-08_final.stac-item
2019-01-08 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2019-01-08_final.stac-item
2019-02-01 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-02-01_final.stac-item
2019-05-15 12:06:04	ga_s2bm_ard_3-2-1_50JKN_2019-05-15_final.stac-item
2019-05-25 12:04:51	ga_s2bm_ard_3-2-1_49JHN_2019-05-25_final.stac-item
2019-05-28 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-28_final.stac-item
2019-07-11 11:56:08	ga_s2bm_ard_3-2-1_50JKN_2019-07-11_final.stac-item
2019-10-15 12:14:57	ga_s2bm_ard_3-2-1_49JGM_2019-10-15_final.stac-item
2019-11-01 12:05:27	ga_s2bm_ard_3-2-1_50JKQ_2019-11-01_final.stac-item
2019-11-11 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2019-11-11_final.stac-item
2019-11-21 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2019-11-21_final.stac-item
2020-01-13 12:14:21	ga_s2bm_ard_3-2-1_49KGP_2020-01-13_final.stac-item
2020-02-02 12:14:53	ga_s2bm_ard_3-2-1_49JFM_2020-02-02_final.stac-item
2020-02-19 12:04:14	ga_s2bm_ard_3-2-1_49KGQ_2020-02-19_final.stac-item
2020-02-23 11:46:34	ga_s2bm_ard_3-2-1_50HNK_2020-02-23_final.stac-item
2020-04-09 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2020-04-09_final.stac-item
2020-04-23 11:47:04	ga_s2bm_ard_3-2-1_50HMH_2020-04-23_final.stac-item
2020-08-17 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2020-08-17_final.stac-item
2020-08-27 12:04:02	ga_s2bm_ard_3-2-1_49KHR_2020-08-27_final.stac-item
2020-08-27 12:05:47	ga_s2bm_ard_3-2-1_49JGJ_2020-08-27_final.stac-item
2020-09-13 11:56:01	ga_s2bm_ard_3-2-1_50JKN_2020-09-13_final.stac-item
2020-10-16 12:05:33	ga_s2bm_ard_3-2-1_49JGK_2020-10-16_final.stac-item
2020-11-15 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2020-11-15_final.stac-item
2020-11-15 12:05:42	ga_s2bm_ard_3-2-1_50JKP_2020-11-15_final.stac-item
2020-12-18 12:14:34	ga_s2bm_ard_3-2-1_49JGN_2020-12-18_final.stac-item
2020-12-29 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2020-12-29_final.stac-item
2021-02-10 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2021-02-10_final.stac-item
2021-04-14 12:06:06	ga_s2bm_ard_3-2-1_50JKM_2021-04-14_final.stac-item
2021-07-10 11:57:22	ga_s2bm_ard_3-2-1_50HMG_2021-07-10_final
2021-07-17 11:47:04	ga_s2bm_ard_3-2-1_50HPH_2021-07-17_final.stac-item
2021-08-29 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2021-08-29_final.stac-item
2021-10-02 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2021-10-02_final.stac-item
2021-10-31 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2021-10-31_final.stac-item
2021-11-01 11:36:39	ga_s2bm_ard_3-2-1_50HPK_2021-11-01_final.stac-item
2021-11-20 12:05:12	ga_s2bm_ard_3-2-1_49JGL_2021-11-20_final.stac-item
2021-11-24 11:47:13	ga_s2bm_ard_3-2-1_50HPG_2021-11-24_final
2021-11-27 11:55:55	ga_s2bm_ard_3-2-1_50JKN_2021-11-27_final.stac-item
2021-12-10 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2021-12-10_final.stac-item
2021-12-30 12:04:56	ga_s2bm_ard_3-2-1_49JGM_2021-12-30_final.stac-item
2022-01-29 12:05:35	ga_s2bm_ard_3-2-1_50JKP_2022-01-29_final.stac-item
2022-01-29 12:05:58	ga_s2bm_ard_3-2-1_50JLM_2022-01-29_final.stac-item
2022-04-22 12:14:51	ga_s2bm_ard_3-2-1_49JGM_2022-04-22_final.stac-item
2022-04-26 11:56:19	ga_s2bm_ard_3-2-1_50JLL_2022-04-26_final.stac-item
2022-05-29 12:05:41	ga_s2bm_ard_3-2-1_50JKP_2022-05-29_final.stac-item
2022-09-06 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2022-09-06_final.stac-item
2022-09-30 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2022-09-30_final.stac-item
2022-10-23 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2022-10-23_final.stac-item
2022-12-09 11:47:03	ga_s2bm_ard_3-2-1_50HNH_2022-12-09_final.stac-item
2022-12-25 12:05:40	ga_s2bm_ard_3-2-1_50JKP_2022-12-25_final.stac-item
2023-01-01 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2023-01-01_final.stac-item
2023-01-21 11:56:09	ga_s2bm_ard_3-2-1_50JLM_2023-01-21_final.stac-item
2023-01-31 11:56:52	ga_s2bm_ard_3-2-1_50HLJ_2023-01-31_final.stac-item
2023-03-05 12:05:43	ga_s2bm_ard_3-2-1_50JKP_2023-03-05_final
2023-04-07 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2023-04-07_final
2023-04-11 11:55:48	ga_s2bm_ard_3-2-1_50JKP_2023-04-11_final
2023-04-15 11:37:04	ga_s2bm_ard_3-2-1_50HQH_2023-04-15_final
2023-04-15 11:37:18	ga_s2bm_ard_3-2-1_50HQG_2023-04-15_final
2023-05-15 11:37:21	ga_s2bm_ard_3-2-1_50HQG_2023-05-15_final
2023-05-27 12:15:04	ga_s2bm_ard_3-2-1_49JFM_2023-05-27_final
2023-08-16 11:47:26	ga_s2bm_ard_3-2-1_50HNG_2023-08-16_final
2023-10-02 11:36:50	ga_s2bm_ard_3-2-1_50HQJ_2023-10-02_final
2023-10-22 11:37:04	ga_s2bm_ard_3-2-1_50HQH_2023-10-22_final
2023-10-25 11:47:18	ga_s2bm_ard_3-2-1_50HPG_2023-10-25_final
2023-11-17 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2023-11-17_final
2023-11-23 12:15:06	ga_s2bm_ard_3-2-1_49JGL_2023-11-23_final
2023-11-27 11:56:47	ga_s2bm_ard_3-2-1_50HMJ_2023-11-27_final
2023-12-04 11:47:03	ga_s2bm_ard_3-2-1_50HNH_2023-12-04_final
2023-12-10 12:05:37	ga_s2bm_ard_3-2-1_50JKP_2023-12-10_final
2023-12-11 11:37:18	ga_s2bm_ard_3-2-1_50HPG_2023-12-11_final
2023-12-14 11:47:15	ga_s2bm_ard_3-2-1_50HPG_2023-12-14_final
2023-12-20 12:05:41	ga_s2bm_ard_3-2-1_50JKP_2023-12-20_final
2023-12-24 11:47:22	ga_s2bm_ard_3-2-1_50HNG_2023-12-24_final
2024-01-16 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2024-01-16_final
2024-01-29 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2024-01-29_final
2024-02-05 11:56:28	ga_s2bm_ard_3-2-1_50HNK_2024-02-05_final
2024-02-08 12:03:59	ga_s2bm_ard_3-2-1_49KHR_2024-02-08_final
2024-02-15 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2024-02-15_final
2024-02-15 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2024-02-15_final
2024-03-19 12:05:40	ga_s2bm_ard_3-2-1_50JKP_2024-03-19_final
2024-03-26 11:56:30	ga_s2bm_ard_3-2-1_50HNK_2024-03-26_final
2024-04-28 12:05:40	ga_s2bm_ard_3-2-1_50JKP_2024-04-28_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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