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
2017-10-15 12:14:28	ga_s2bm_ard_3-2-1_49JGM_2017-10-15_final.stac-item
2018-01-04 11:37:43	ga_s2bm_ard_3-2-1_50HMJ_2018-01-04_final.stac-item
2018-01-13 12:13:13	ga_s2bm_ard_3-2-1_49JGL_2018-01-13_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50HMJ_2018-01-27_final.stac-item
2018-02-16 11:54:55	ga_s2bm_ard_3-2-1_50HMJ_2018-02-16_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_49JGM_2018-03-01_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_49JGM_2018-03-21_final.stac-item
2018-04-21 11:33:07	ga_s2bm_ard_3-2-1_50HPJ_2018-04-21_final.stac-item
2018-06-03 11:40:10	ga_s2bm_ard_3-2-1_50HNK_2018-06-03_final.stac-item
2018-06-09 12:02:47	ga_s2bm_ard_3-2-1_49JGL_2018-06-09_final.stac-item
2018-07-26 11:52:57	ga_s2bm_ard_3-2-1_50HMK_2018-07-26_final.stac-item
2018-08-21 12:13:39	ga_s2bm_ard_3-2-1_49JGL_2018-08-21_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49KGQ_2018-10-20_final.stac-item
2018-12-23 11:56:25	ga_s2bm_ard_3-2-1_50HNK_2018-12-23_final.stac-item
2019-01-12 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2019-01-12_final.stac-item
2019-01-19 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-01-19_final.stac-item
2019-02-01 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-02-01_final.stac-item
2019-02-24 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2019-02-24_final.stac-item
2019-05-02 11:57:13	ga_s2bm_ard_3-2-1_50HMH_2019-05-02_final.stac-item
2019-08-13 12:04:38	ga_s2bm_ard_3-2-1_49KGP_2019-08-13_final.stac-item
2019-10-15 12:14:57	ga_s2bm_ard_3-2-1_49JGM_2019-10-15_final.stac-item
2020-01-13 12:13:49	ga_s2bm_ard_3-2-1_49KHR_2020-01-13_final.stac-item
2020-01-30 12:03:51	ga_s2bm_ard_3-2-1_49KHR_2020-01-30_final.stac-item
2020-02-03 11:47:03	ga_s2bm_ard_3-2-1_50HMH_2020-02-03_final.stac-item
2020-02-19 12:04:14	ga_s2bm_ard_3-2-1_49KGQ_2020-02-19_final.stac-item
2020-03-20 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2020-03-20_final.stac-item
2020-04-19 12:03:54	ga_s2bm_ard_3-2-1_49KHR_2020-04-19_final.stac-item
2020-04-29 12:05:11	ga_s2bm_ard_3-2-1_49JGL_2020-04-29_final.stac-item
2020-05-26 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2020-05-26_final.stac-item
2020-08-20 12:14:16	ga_s2bm_ard_3-2-1_49KGQ_2020-08-20_final.stac-item
2020-10-16 12:04:03	ga_s2bm_ard_3-2-1_49KHR_2020-10-16_final.stac-item
2020-10-26 12:04:34	ga_s2bm_ard_3-2-1_49KGP_2020-10-26_final.stac-item
2020-11-08 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2020-11-08_final.stac-item
2020-11-15 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2020-11-15_final.stac-item
2020-11-22 11:57:12	ga_s2bm_ard_3-2-1_50HMH_2020-11-22_final.stac-item
2020-11-25 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2020-11-25_final.stac-item
2020-12-16 11:36:48	ga_s2bm_ard_3-2-1_50HPJ_2020-12-16_final.stac-item
2020-12-28 12:14:54	ga_s2bm_ard_3-2-1_49JGM_2020-12-28_final.stac-item
2020-12-28 12:14:57	ga_s2bm_ard_3-2-1_49JFM_2020-12-28_final.stac-item
2020-12-29 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2020-12-29_final.stac-item
2021-01-21 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2021-01-21_final.stac-item
2021-03-08 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2021-03-08_final.stac-item
2021-04-18 11:47:16	ga_s2bm_ard_3-2-1_50HNG_2021-04-18_final
2021-04-24 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2021-04-24_final.stac-item
2021-05-28 11:47:28	ga_s2bm_ard_3-2-1_50HLG_2021-05-28_final
2021-06-07 11:47:07	ga_s2bm_ard_3-2-1_50HNH_2021-06-07_final.stac-item
2021-06-17 11:47:25	ga_s2bm_ard_3-2-1_50HMG_2021-06-17_final
2021-06-23 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2021-06-23_final.stac-item
2021-06-23 12:04:28	ga_s2bm_ard_3-2-1_49KHP_2021-06-23_final.stac-item
2021-06-24 11:37:07	ga_s2bm_ard_3-2-1_50HPH_2021-06-24_final.stac-item
2021-07-03 12:04:49	ga_s2bm_ard_3-2-1_49JHM_2021-07-03_final.stac-item
2021-08-03 11:37:08	ga_s2bm_ard_3-2-1_50HPH_2021-08-03_final.stac-item
2021-08-06 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2021-08-06_final.stac-item
2021-09-25 11:47:22	ga_s2bm_ard_3-2-1_50HMG_2021-09-25_final
2021-10-14 12:14:57	ga_s2bm_ard_3-2-1_49JGM_2021-10-14_final.stac-item
2021-10-15 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2021-10-15_final.stac-item
2021-11-10 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2021-11-10_final.stac-item
2021-12-04 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2021-12-04_final.stac-item
2021-12-07 11:56:35	ga_s2bm_ard_3-2-1_50HLK_2021-12-07_final.stac-item
2021-12-10 12:03:54	ga_s2bm_ard_3-2-1_49KHR_2021-12-10_final.stac-item
2022-02-01 12:14:50	ga_s2bm_ard_3-2-1_49JGM_2022-02-01_final.stac-item
2022-02-08 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2022-02-08_final.stac-item
2022-06-02 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2022-06-02_final.stac-item
2022-07-15 11:56:41	ga_s2bm_ard_3-2-1_50HMK_2022-07-15_final.stac-item
2022-08-20 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2022-08-20_final.stac-item
2022-10-06 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2022-10-06_final.stac-item
2022-10-19 12:14:59	ga_s2bm_ard_3-2-1_49JFM_2022-10-19_final.stac-item
2022-11-15 12:05:43	ga_s2bm_ard_3-2-1_49JGJ_2022-11-15_final.stac-item
2023-01-07 12:14:57	ga_s2bm_ard_3-2-1_49JFM_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 12:03:40	ga_s2bm_ard_3-2-1_49KHS_2023-01-14_final
2023-03-09 11:47:21	ga_s2bm_ard_3-2-1_50HPG_2023-03-09_final
2023-03-15 12:04:03	ga_s2bm_ard_3-2-1_49KHR_2023-03-15_final
2023-03-29 11:47:20	ga_s2bm_ard_3-2-1_50HPG_2023-03-29_final
2023-04-07 12:13:42	ga_s2bm_ard_3-2-1_49KHS_2023-04-07_final
2023-04-24 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2023-04-24_final
2023-06-14 11:37:12	ga_s2bm_ard_3-2-1_50HPH_2023-06-14_final
2023-07-04 11:37:26	ga_s2bm_ard_3-2-1_50HPG_2023-07-04_final
2023-09-11 12:03:48	ga_s2bm_ard_3-2-1_49KHS_2023-09-11_final
2023-10-01 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-01_final
2023-10-11 12:03:46	ga_s2bm_ard_3-2-1_49KHS_2023-10-11_final
2023-10-11 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-11_final
2023-10-15 11:47:26	ga_s2bm_ard_3-2-1_50HMG_2023-10-15_final
2023-10-25 11:47:18	ga_s2bm_ard_3-2-1_50HPG_2023-10-25_final
2023-10-31 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-31_final
2023-10-31 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-10-31_final
2023-10-31 12:05:46	ga_s2bm_ard_3-2-1_49JGJ_2023-10-31_final
2023-11-03 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2023-11-03_final
2023-11-07 11:56:53	ga_s2bm_ard_3-2-1_50HMJ_2023-11-07_final
2023-11-13 12:13:55	ga_s2bm_ard_3-2-1_49KHR_2023-11-13_final
2023-11-30 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2023-11-30_final
2023-12-11 11:37:18	ga_s2bm_ard_3-2-1_50HPG_2023-12-11_final
2023-12-24 11:47:22	ga_s2bm_ard_3-2-1_50HNG_2023-12-24_final
2023-12-30 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2023-12-30_final
2024-01-03 11:46:38	ga_s2bm_ard_3-2-1_50HNK_2024-01-03_final
2024-01-09 12:03:43	ga_s2bm_ard_3-2-1_49KHS_2024-01-09_final
2024-01-29 12:05:27	ga_s2bm_ard_3-2-1_49JGK_2024-01-29_final
2024-04-12 11:47:25	ga_s2bm_ard_3-2-1_50HMG_2024-04-12_final
2024-04-15 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2024-04-15_final
2024-04-25 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2024-04-25_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

All years