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
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_49JGM_2017-07-24_final.stac-item
2017-11-04 12:13:08	ga_s2bm_ard_3-2-1_49KHR_2017-11-04_final.stac-item
2017-12-24 12:13:09	ga_s2bm_ard_3-2-1_49JGL_2017-12-24_final.stac-item
2017-12-24 12:13:09	ga_s2bm_ard_3-2-1_49JGN_2017-12-24_final.stac-item
2017-12-24 12:13:09	ga_s2bm_ard_3-2-1_49KGP_2017-12-24_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49KHR_2018-01-10_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50HLJ_2018-01-27_final.stac-item
2018-02-02 12:13:14	ga_s2bm_ard_3-2-1_49JGN_2018-02-02_final.stac-item
2018-02-16 11:54:55	ga_s2bm_ard_3-2-1_50HLJ_2018-02-16_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_49JGK_2018-03-11_final.stac-item
2018-05-23 12:13:19	ga_s2bm_ard_3-2-1_49KGR_2018-05-23_final.stac-item
2018-06-09 12:02:47	ga_s2bm_ard_3-2-1_49JGM_2018-06-09_final.stac-item
2018-07-29 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2018-07-29_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50HLK_2018-09-14_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_49JGM_2018-09-27_final.stac-item
2018-11-10 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2018-11-10_final.stac-item
2018-12-09 12:14:15	ga_s2bm_ard_3-2-1_49KHP_2018-12-09_final.stac-item
2019-01-15 12:04:17	ga_s2bm_ard_3-2-1_49KGQ_2019-01-15_final.stac-item
2019-01-18 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-01-18_final.stac-item
2019-03-26 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2019-03-26_final.stac-item
2019-04-25 12:04:06	ga_s2bm_ard_3-2-1_49KHR_2019-04-25_final.stac-item
2019-05-22 11:57:18	ga_s2bm_ard_3-2-1_50HLH_2019-05-22_final.stac-item
2019-06-27 12:14:07	ga_s2bm_ard_3-2-1_49KGR_2019-06-27_final.stac-item
2019-08-26 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2019-08-26_final.stac-item
2019-09-25 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2019-09-25_final.stac-item
2019-10-12 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2019-10-12_final.stac-item
2019-12-11 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2019-12-11_final.stac-item
2019-12-21 12:04:13	ga_s2bm_ard_3-2-1_49KGQ_2019-12-21_final.stac-item
2020-01-07 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2020-01-07_final.stac-item
2020-02-06 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2020-02-06_final.stac-item
2020-03-03 12:15:08	ga_s2bm_ard_3-2-1_49JGL_2020-03-03_final.stac-item
2020-04-19 12:04:56	ga_s2bm_ard_3-2-1_49JGM_2020-04-19_final.stac-item
2020-05-02 12:13:51	ga_s2bm_ard_3-2-1_49KHR_2020-05-02_final.stac-item
2020-06-02 11:47:16	ga_s2bm_ard_3-2-1_50HLH_2020-06-02_final.stac-item
2020-07-31 12:15:13	ga_s2bm_ard_3-2-1_49JGL_2020-07-31_final.stac-item
2020-08-14 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2020-08-14_final.stac-item
2020-08-17 12:04:45	ga_s2bm_ard_3-2-1_49JHN_2020-08-17_final.stac-item
2020-08-20 12:14:00	ga_s2bm_ard_3-2-1_49KHR_2020-08-20_final.stac-item
2020-09-16 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2020-09-16_final.stac-item
2020-09-26 12:04:34	ga_s2bm_ard_3-2-1_49KGP_2020-09-26_final.stac-item
2020-10-13 11:56:44	ga_s2bm_ard_3-2-1_50HLK_2020-10-13_final.stac-item
2020-11-05 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2020-11-05_final.stac-item
2020-11-08 12:14:10	ga_s2bm_ard_3-2-1_49KHQ_2020-11-08_final.stac-item
2020-12-19 11:47:06	ga_s2bm_ard_3-2-1_50HMH_2020-12-19_final.stac-item
2020-12-25 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2020-12-25_final.stac-item
2021-01-24 12:03:44	ga_s2bm_ard_3-2-1_49KHS_2021-01-24_final
2021-01-24 12:04:18	ga_s2bm_ard_3-2-1_49KGQ_2021-01-24_final.stac-item
2021-01-31 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2021-01-31_final.stac-item
2021-03-05 12:04:20	ga_s2bm_ard_3-2-1_49KHP_2021-03-05_final.stac-item
2021-04-07 12:14:57	ga_s2bm_ard_3-2-1_49JFM_2021-04-07_final.stac-item
2021-05-07 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2021-05-07_final.stac-item
2021-05-07 12:15:08	ga_s2bm_ard_3-2-1_49JGL_2021-05-07_final.stac-item
2021-07-03 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2021-07-03_final.stac-item
2021-07-03 12:04:49	ga_s2bm_ard_3-2-1_49JHM_2021-07-03_final.stac-item
2021-07-27 11:47:26	ga_s2bm_ard_3-2-1_50HMG_2021-07-27_final
2021-08-22 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2021-08-22_final.stac-item
2021-08-22 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2021-08-22_final.stac-item
2021-10-04 12:14:56	ga_s2bm_ard_3-2-1_49JGM_2021-10-04_final.stac-item
2021-12-20 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2021-12-20_final.stac-item
2021-12-24 11:47:05	ga_s2bm_ard_3-2-1_50HMH_2021-12-24_final.stac-item
2022-01-22 12:13:49	ga_s2bm_ard_3-2-1_49KHR_2022-01-22_final.stac-item
2022-02-05 11:57:00	ga_s2bm_ard_3-2-1_50HMH_2022-02-05_final.stac-item
2022-03-23 12:14:54	ga_s2bm_ard_3-2-1_49JGM_2022-03-23_final.stac-item
2022-06-28 12:04:04	ga_s2bm_ard_3-2-1_49KHR_2022-06-28_final.stac-item
2022-07-01 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2022-07-01_final.stac-item
2022-08-20 12:14:58	ga_s2bm_ard_3-2-1_49JGM_2022-08-20_final.stac-item
2022-08-20 12:15:12	ga_s2bm_ard_3-2-1_49JGL_2022-08-20_final.stac-item
2022-09-09 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2022-09-09_final.stac-item
2022-10-19 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2022-10-19_final.stac-item
2022-11-22 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2022-11-22_final.stac-item
2022-12-25 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2022-12-25_final.stac-item
2022-12-29 11:47:13	ga_s2bm_ard_3-2-1_50HLH_2022-12-29_final.stac-item
2023-01-07 12:13:52	ga_s2bm_ard_3-2-1_49KHR_2023-01-07_final.stac-item
2023-01-11 11:56:36	ga_s2bm_ard_3-2-1_50HLK_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
2023-02-10 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2023-02-10_final.stac-item
2023-02-13 12:03:43	ga_s2bm_ard_3-2-1_49KHS_2023-02-13_final
2023-02-23 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2023-02-23_final
2023-03-15 12:04:03	ga_s2bm_ard_3-2-1_49KHR_2023-03-15_final
2023-05-07 12:14:32	ga_s2bm_ard_3-2-1_49KGP_2023-05-07_final
2023-05-27 12:14:31	ga_s2bm_ard_3-2-1_49KGP_2023-05-27_final
2023-06-23 12:04:03	ga_s2bm_ard_3-2-1_49KHR_2023-06-23_final
2023-07-23 12:05:06	ga_s2bm_ard_3-2-1_49JGM_2023-07-23_final
2023-08-29 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2023-08-29_final
2023-09-18 11:57:13	ga_s2bm_ard_3-2-1_50HLH_2023-09-18_final
2023-10-11 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-11_final
2023-10-14 12:14:58	ga_s2bm_ard_3-2-1_49JGM_2023-10-14_final
2023-10-15 11:47:26	ga_s2bm_ard_3-2-1_50HMG_2023-10-15_final
2023-10-24 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2023-10-24_final
2024-01-19 12:03:44	ga_s2bm_ard_3-2-1_49KHS_2024-01-19_final
2024-01-26 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2024-01-26_final
2024-03-02 12:15:08	ga_s2bm_ard_3-2-1_49JGL_2024-03-02_final
2024-03-09 12:05:24	ga_s2bm_ard_3-2-1_49JGK_2024-03-09_final
2024-03-16 11:57:04	ga_s2bm_ard_3-2-1_50HMH_2024-03-16_final
2024-03-23 11:47:10	ga_s2bm_ard_3-2-1_50HMH_2024-03-23_final
2024-03-29 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2024-03-29_final
2024-03-29 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2024-03-29_final
2024-04-01 12:13:57	ga_s2bm_ard_3-2-1_49KGR_2024-04-01_final
2024-04-01 12:14:55	ga_s2bm_ard_3-2-1_49JGM_2024-04-01_final
2024-04-25 11:57:18	ga_s2bm_ard_3-2-1_50HMG_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