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
2017-09-15 12:13:36	ga_s2bm_ard_3-2-1_49JGM_2017-09-15_final.stac-item
2017-10-15 12:14:28	ga_s2bm_ard_3-2-1_49JGM_2017-10-15_final.stac-item
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50HLH_2017-12-15_final.stac-item
2018-01-07 11:56:02	ga_s2bm_ard_3-2-1_50HMJ_2018-01-07_final.stac-item
2018-03-08 11:51:37	ga_s2bm_ard_3-2-1_50HLH_2018-03-08_final.stac-item
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50HLJ_2018-05-07_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_49JGN_2018-06-19_final.stac-item
2018-07-26 11:52:57	ga_s2bm_ard_3-2-1_50HLJ_2018-07-26_final.stac-item
2018-08-08 12:02:45	ga_s2bm_ard_3-2-1_49JHN_2018-08-08_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_49JGM_2018-09-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49KHR_2018-10-27_final.stac-item
2018-10-31 11:46:25	ga_s2bm_ard_3-2-1_50HMJ_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
2018-11-16 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2018-11-16_final.stac-item
2018-11-29 12:13:50	ga_s2bm_ard_3-2-1_49KHR_2018-11-29_final.stac-item
2018-12-03 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2018-12-03_final.stac-item
2019-04-12 11:57:13	ga_s2bm_ard_3-2-1_50HMH_2019-04-12_final.stac-item
2019-06-24 12:04:07	ga_s2bm_ard_3-2-1_49KHR_2019-06-24_final.stac-item
2019-08-10 11:56:47	ga_s2bm_ard_3-2-1_50HLK_2019-08-10_final.stac-item
2019-09-22 12:05:43	ga_s2bm_ard_3-2-1_49JGJ_2019-09-22_final.stac-item
2019-10-15 12:14:57	ga_s2bm_ard_3-2-1_49JGM_2019-10-15_final.stac-item
2019-11-04 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-11-04_final.stac-item
2019-11-25 11:47:11	ga_s2bm_ard_3-2-1_50HLH_2019-11-25_final.stac-item
2019-11-28 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2019-11-28_final.stac-item
2019-12-01 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2019-12-01_final.stac-item
2019-12-25 11:46:50	ga_s2bm_ard_3-2-1_50HMJ_2019-12-25_final.stac-item
2020-01-07 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2020-01-07_final.stac-item
2020-01-13 12:14:50	ga_s2bm_ard_3-2-1_49JGM_2020-01-13_final.stac-item
2020-01-20 12:04:54	ga_s2bm_ard_3-2-1_49JGM_2020-01-20_final.stac-item
2020-02-29 12:03:56	ga_s2bm_ard_3-2-1_49KHR_2020-02-29_final.stac-item
2020-03-14 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2020-03-14_final.stac-item
2020-03-27 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2020-03-27_final.stac-item
2020-08-17 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2020-08-17_final.stac-item
2020-10-10 11:47:13	ga_s2bm_ard_3-2-1_50HMH_2020-10-10_final.stac-item
2020-10-13 11:57:09	ga_s2bm_ard_3-2-1_50HMH_2020-10-13_final.stac-item
2020-10-16 12:05:33	ga_s2bm_ard_3-2-1_49JGK_2020-10-16_final.stac-item
2020-10-29 12:14:30	ga_s2bm_ard_3-2-1_49KGP_2020-10-29_final.stac-item
2020-11-09 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2020-11-09_final.stac-item
2021-01-18 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2021-01-18_final.stac-item
2021-01-24 12:03:44	ga_s2bm_ard_3-2-1_49KHS_2021-01-24_final
2021-03-12 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2021-03-12_final.stac-item
2021-04-27 12:14:08	ga_s2bm_ard_3-2-1_49KGQ_2021-04-27_final.stac-item
2021-05-08 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2021-05-08_final.stac-item
2021-06-13 12:04:49	ga_s2bm_ard_3-2-1_49JHN_2021-06-13_final.stac-item
2021-08-15 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2021-08-15_final.stac-item
2021-10-18 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2021-10-18_final.stac-item
2021-11-14 11:46:54	ga_s2bm_ard_3-2-1_50HMJ_2021-11-14_final.stac-item
2021-11-14 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2021-11-14_final.stac-item
2021-11-27 11:56:47	ga_s2bm_ard_3-2-1_50HMJ_2021-11-27_final.stac-item
2021-11-27 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2021-11-27_final.stac-item
2021-12-20 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2021-12-20_final.stac-item
2022-01-02 12:14:37	ga_s2bm_ard_3-2-1_49JGN_2022-01-02_final.stac-item
2022-01-02 12:14:52	ga_s2bm_ard_3-2-1_49JGM_2022-01-02_final.stac-item
2022-01-02 12:15:06	ga_s2bm_ard_3-2-1_49JGL_2022-01-02_final.stac-item
2022-01-12 12:13:50	ga_s2bm_ard_3-2-1_49KHR_2022-01-12_final.stac-item
2022-01-29 12:03:53	ga_s2bm_ard_3-2-1_49KHR_2022-01-29_final.stac-item
2022-02-01 12:14:50	ga_s2bm_ard_3-2-1_49JGM_2022-02-01_final.stac-item
2022-04-19 12:03:55	ga_s2bm_ard_3-2-1_49KHR_2022-04-19_final.stac-item
2022-04-22 12:14:03	ga_s2bm_ard_3-2-1_49KHQ_2022-04-22_final.stac-item
2022-08-10 12:15:00	ga_s2bm_ard_3-2-1_49JGM_2022-08-10_final.stac-item
2022-08-20 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2022-08-20_final.stac-item
2022-09-06 12:05:46	ga_s2bm_ard_3-2-1_49JGJ_2022-09-06_final.stac-item
2022-10-26 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2022-10-26_final.stac-item
2022-10-29 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2022-10-29_final.stac-item
2022-12-08 12:13:51	ga_s2bm_ard_3-2-1_49KHR_2022-12-08_final.stac-item
2022-12-12 11:56:52	ga_s2bm_ard_3-2-1_50HLJ_2022-12-12_final.stac-item
2022-12-12 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2022-12-12_final.stac-item
2022-12-15 12:03:57	ga_s2bm_ard_3-2-1_49KHR_2022-12-15_final.stac-item
2023-01-04 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2023-01-04_final.stac-item
2023-01-07 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2023-01-07_final.stac-item
2023-01-11 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2023-01-11_final.stac-item
2023-01-14 12:03:55	ga_s2bm_ard_3-2-1_49KHR_2023-01-14_final.stac-item
2023-02-13 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2023-02-13_final
2023-02-20 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2023-02-20_final
2023-04-14 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2023-04-14_final
2023-05-01 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2023-05-01_final
2023-05-27 12:15:04	ga_s2bm_ard_3-2-1_49JFM_2023-05-27_final
2023-06-17 11:47:29	ga_s2bm_ard_3-2-1_50HMG_2023-06-17_final
2023-07-17 11:47:29	ga_s2bm_ard_3-2-1_50HMG_2023-07-17_final
2023-07-23 12:05:50	ga_s2bm_ard_3-2-1_49JGJ_2023-07-23_final
2023-08-22 12:04:04	ga_s2bm_ard_3-2-1_49KHR_2023-08-22_final
2023-09-18 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2023-09-18_final
2023-09-24 12:14:02	ga_s2bm_ard_3-2-1_49KGR_2023-09-24_final
2023-09-24 12:14:59	ga_s2bm_ard_3-2-1_49JGM_2023-09-24_final
2023-10-21 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-21_final
2023-10-21 12:05:46	ga_s2bm_ard_3-2-1_49JGJ_2023-10-21_final
2023-10-24 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2023-10-24_final
2023-10-31 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-10-31_final
2023-11-27 11:57:02	ga_s2bm_ard_3-2-1_50HMH_2023-11-27_final
2023-12-04 11:46:52	ga_s2bm_ard_3-2-1_50HMJ_2023-12-04_final
2023-12-17 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2023-12-17_final
2024-01-16 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2024-01-16_final
2024-01-19 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2024-01-19_final
2024-01-23 11:47:13	ga_s2bm_ard_3-2-1_50HLH_2024-01-23_final
2024-02-11 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2024-02-11_final
2024-02-21 12:15:11	ga_s2bm_ard_3-2-1_49JGL_2024-02-21_final
2024-04-15 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2024-04-15_final
2024-04-28 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2024-04-28_final
2024-05-08 12:03:45	ga_s2bm_ard_3-2-1_49KHS_2024-05-08_final
2024-05-08 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2024-05-08_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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