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_50HPJ_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50HQJ_2017-09-16_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_49JGJ_2017-11-01_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_49JGJ_2018-01-20_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_49JGJ_2018-05-20_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49KGQ_2018-10-07_final.stac-item
2018-10-11 11:41:47	ga_s2bm_ard_3-2-1_50HPH_2018-10-11_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JGL_2018-10-20_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49KHQ_2018-10-20_final.stac-item
2018-11-10 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2018-11-10_final.stac-item
2018-11-20 11:46:59	ga_s2bm_ard_3-2-1_50HPH_2018-11-20_final.stac-item
2018-11-29 12:14:04	ga_s2bm_ard_3-2-1_49KHQ_2018-11-29_final.stac-item
2018-11-29 12:14:56	ga_s2bm_ard_3-2-1_49JFM_2018-11-29_final.stac-item
2018-12-16 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2018-12-16_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 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2019-09-15_final.stac-item
2019-12-04 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2019-12-04_final.stac-item
2019-12-14 12:14:03	ga_s2bm_ard_3-2-1_49KHQ_2019-12-14_final.stac-item
2020-01-10 12:05:38	ga_s2bm_ard_3-2-1_49JGJ_2020-01-10_final.stac-item
2020-02-19 12:04:14	ga_s2bm_ard_3-2-1_49KGQ_2020-02-19_final.stac-item
2020-03-04 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2020-03-04_final.stac-item
2020-08-11 11:46:37	ga_s2bm_ard_3-2-1_50HPK_2020-08-11_final.stac-item
2020-09-06 12:04:09	ga_s2bm_ard_3-2-1_49KHR_2020-09-06_final.stac-item
2020-09-29 12:15:13	ga_s2bm_ard_3-2-1_49JGL_2020-09-29_final.stac-item
2020-09-30 11:47:05	ga_s2bm_ard_3-2-1_50HPH_2020-09-30_final.stac-item
2021-09-25 11:46:39	ga_s2bm_ard_3-2-1_50HMK_2021-09-25_final.stac-item
2021-09-28 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2021-09-28_final.stac-item
2021-10-22 11:37:08	ga_s2bm_ard_3-2-1_50HPH_2021-10-22_final.stac-item
2021-10-25 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2021-10-25_final.stac-item
2021-10-31 12:05:30	ga_s2bm_ard_3-2-1_49JGK_2021-10-31_final.stac-item
2021-11-10 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2021-11-10_final.stac-item
2021-11-21 11:36:45	ga_s2bm_ard_3-2-1_50HQJ_2021-11-21_final.stac-item
2021-12-21 11:36:43	ga_s2bm_ard_3-2-1_50HQJ_2021-12-21_final.stac-item
2022-01-13 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2022-01-13_final.stac-item
2022-01-16 11:56:36	ga_s2bm_ard_3-2-1_50HLK_2022-01-16_final.stac-item
2022-02-02 11:46:37	ga_s2bm_ard_3-2-1_50HQJ_2022-02-02_final.stac-item
2022-02-11 12:14:39	ga_s2bm_ard_3-2-1_49JFN_2022-02-11_final.stac-item
2022-03-07 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-03-07_final.stac-item
2022-03-11 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2022-03-11_final.stac-item
2022-03-14 11:46:41	ga_s2bm_ard_3-2-1_50HQJ_2022-03-14_final.stac-item
2022-03-24 11:46:41	ga_s2bm_ard_3-2-1_50HQJ_2022-03-24_final.stac-item
2022-03-27 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2022-03-27_final.stac-item
2022-04-06 11:56:27	ga_s2bm_ard_3-2-1_50HNK_2022-04-06_final.stac-item
2022-04-16 11:56:36	ga_s2bm_ard_3-2-1_50HLK_2022-04-16_final.stac-item
2022-05-26 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2022-05-26_final.stac-item
2022-06-02 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2022-06-02_final.stac-item
2022-06-05 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2022-06-05_final.stac-item
2022-06-05 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2022-06-05_final.stac-item
2022-06-19 11:37:11	ga_s2bm_ard_3-2-1_50HPH_2022-06-19_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
2022-07-02 11:46:48	ga_s2bm_ard_3-2-1_50HQJ_2022-07-02_final.stac-item
2022-07-15 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2022-07-15_final.stac-item
2022-07-19 11:37:11	ga_s2bm_ard_3-2-1_50HPH_2022-07-19_final.stac-item
2022-07-25 11:56:56	ga_s2bm_ard_3-2-1_50HMJ_2022-07-25_final.stac-item
2022-08-04 11:56:55	ga_s2bm_ard_3-2-1_50HMJ_2022-08-04_final.stac-item
2022-08-14 11:56:43	ga_s2bm_ard_3-2-1_50HLK_2022-08-14_final.stac-item
2022-09-23 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2022-09-23_final.stac-item
2022-10-20 11:46:51	ga_s2bm_ard_3-2-1_50HNJ_2022-10-20_final.stac-item
2022-10-27 11:36:51	ga_s2bm_ard_3-2-1_50HPJ_2022-10-27_final.stac-item
2022-11-02 11:56:34	ga_s2bm_ard_3-2-1_50HMK_2022-11-02_final.stac-item
2022-12-02 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2022-12-02_final.stac-item
2022-12-09 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2022-12-09_final.stac-item
2022-12-16 11:37:01	ga_s2bm_ard_3-2-1_50HQH_2022-12-16_final.stac-item
2022-12-19 11:46:42	ga_s2bm_ard_3-2-1_50HQJ_2022-12-19_final.stac-item
2022-12-26 11:37:06	ga_s2bm_ard_3-2-1_50HPH_2022-12-26_final.stac-item
2023-01-01 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2023-01-01_final.stac-item
2023-01-05 11:36:46	ga_s2bm_ard_3-2-1_50HQJ_2023-01-05_final.stac-item
2023-01-21 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2023-01-21_final.stac-item
2023-01-31 11:56:27	ga_s2bm_ard_3-2-1_50HNK_2023-01-31_final.stac-item
2023-02-17 11:46:41	ga_s2bm_ard_3-2-1_50HQJ_2023-02-17_final
2023-02-20 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2023-02-20_final
2023-03-06 11:36:55	ga_s2bm_ard_3-2-1_50HPJ_2023-03-06_final
2023-03-25 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2023-03-25_final
2023-04-11 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2023-04-11_final
2023-04-15 11:36:53	ga_s2bm_ard_3-2-1_50HPJ_2023-04-15_final
2023-04-21 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2023-04-21_final
2023-04-25 11:36:54	ga_s2bm_ard_3-2-1_50HPJ_2023-04-25_final
2023-04-25 11:37:05	ga_s2bm_ard_3-2-1_50HQH_2023-04-25_final
2023-04-28 11:46:50	ga_s2bm_ard_3-2-1_50HPJ_2023-04-28_final
2023-05-08 11:46:45	ga_s2bm_ard_3-2-1_50HQJ_2023-05-08_final
2023-05-11 11:56:39	ga_s2bm_ard_3-2-1_50HMK_2023-05-11_final
2023-05-11 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2023-05-11_final
2023-06-04 11:37:11	ga_s2bm_ard_3-2-1_50HPH_2023-06-04_final
2023-06-04 11:37:21	ga_s2bm_ard_3-2-1_50HQG_2023-06-04_final
2023-06-07 11:46:48	ga_s2bm_ard_3-2-1_50HQJ_2023-06-07_final
2023-06-07 11:46:56	ga_s2bm_ard_3-2-1_50HNJ_2023-06-07_final
2023-06-07 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2023-06-07_final
2023-06-20 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2023-06-20_final
2023-06-27 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2023-06-27_final
2023-07-10 11:57:11	ga_s2bm_ard_3-2-1_50HMH_2023-07-10_final
2023-08-06 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-08-06_final
2023-08-23 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2023-08-23_final
2023-08-26 11:46:47	ga_s2bm_ard_3-2-1_50HQJ_2023-08-26_final
2023-09-08 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2023-09-08_final
2023-10-25 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2023-10-25_final
2023-11-10 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2023-11-10_final
2023-11-21 11:37:03	ga_s2bm_ard_3-2-1_50HPH_2023-11-21_final
2024-01-06 11:56:29	ga_s2bm_ard_3-2-1_50HNK_2024-01-06_final
2024-04-02 11:46:42	ga_s2bm_ard_3-2-1_50HQJ_2024-04-02_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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