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_49JHM_2017-07-24_final.stac-item
2017-07-24 12:02:49	ga_s2bm_ard_3-2-1_49KHP_2017-07-24_final.stac-item
2017-09-15 12:13:36	ga_s2bm_ard_3-2-1_49KGP_2017-09-15_final.stac-item
2017-10-05 12:13:31	ga_s2bm_ard_3-2-1_49JGM_2017-10-05_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_49JGL_2017-12-31_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_49JHN_2017-12-31_final.stac-item
2018-05-03 12:13:20	ga_s2bm_ard_3-2-1_49JGN_2018-05-03_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_49KHP_2018-05-20_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_49KHP_2018-06-19_final.stac-item
2018-06-29 12:02:48	ga_s2bm_ard_3-2-1_49JGL_2018-06-29_final.stac-item
2018-06-29 12:02:48	ga_s2bm_ard_3-2-1_49KGP_2018-06-29_final.stac-item
2018-07-12 12:13:20	ga_s2bm_ard_3-2-1_49JGL_2018-07-12_final.stac-item
2018-07-19 12:03:30	ga_s2bm_ard_3-2-1_49KHR_2018-07-19_final.stac-item
2018-07-29 12:02:46	ga_s2bm_ard_3-2-1_49JGN_2018-07-29_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_49JGM_2018-08-08_final.stac-item
2018-09-10 12:13:12	ga_s2bm_ard_3-2-1_49JFM_2018-09-10_final.stac-item
2018-12-06 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2018-12-06_final.stac-item
2018-12-16 12:04:12	ga_s2bm_ard_3-2-1_49KGQ_2018-12-16_final.stac-item
2019-01-29 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-01-29_final.stac-item
2019-03-16 12:03:57	ga_s2bm_ard_3-2-1_49KHR_2019-03-16_final.stac-item
2019-04-02 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2019-04-02_final.stac-item
2019-04-05 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2019-04-05_final.stac-item
2019-04-09 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2019-04-09_final.stac-item
2019-07-07 12:14:07	ga_s2bm_ard_3-2-1_49KGR_2019-07-07_final.stac-item
2019-09-12 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2019-09-12_final.stac-item
2019-09-16 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2019-09-16_final.stac-item
2019-09-22 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2019-09-22_final.stac-item
2019-09-29 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2019-09-29_final.stac-item
2019-10-02 12:05:30	ga_s2bm_ard_3-2-1_49JGK_2019-10-02_final.stac-item
2019-10-09 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2019-10-09_final.stac-item
2019-10-22 12:05:45	ga_s2bm_ard_3-2-1_49JGJ_2019-10-22_final.stac-item
2019-11-08 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2019-11-08_final.stac-item
2019-12-18 11:56:31	ga_s2bm_ard_3-2-1_50HMK_2019-12-18_final.stac-item
2020-03-14 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2020-03-14_final.stac-item
2020-03-24 11:46:46	ga_s2bm_ard_3-2-1_50HMJ_2020-03-24_final.stac-item
2020-05-19 12:05:20	ga_s2bm_ard_3-2-1_49JGK_2020-05-19_final.stac-item
2020-12-22 11:56:51	ga_s2bm_ard_3-2-1_50HLJ_2020-12-22_final.stac-item
2021-02-26 12:15:09	ga_s2bm_ard_3-2-1_49JGL_2021-02-26_final.stac-item
2021-08-02 12:04:30	ga_s2bm_ard_3-2-1_49KHP_2021-08-02_final.stac-item
2021-08-02 12:04:51	ga_s2bm_ard_3-2-1_49JGN_2021-08-02_final.stac-item
2021-09-21 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2021-09-21_final.stac-item
2021-10-15 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2021-10-15_final.stac-item
2021-11-14 11:46:54	ga_s2bm_ard_3-2-1_50HMJ_2021-11-14_final.stac-item
2022-01-19 12:05:39	ga_s2bm_ard_3-2-1_49JGJ_2022-01-19_final.stac-item
2022-02-02 11:46:35	ga_s2bm_ard_3-2-1_50HMK_2022-02-02_final.stac-item
2022-02-02 11:47:01	ga_s2bm_ard_3-2-1_50HNH_2022-02-02_final.stac-item
2022-05-06 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2022-05-06_final.stac-item
2022-05-26 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2022-05-26_final.stac-item
2022-07-08 12:04:04	ga_s2bm_ard_3-2-1_49KHR_2022-07-08_final.stac-item
2022-09-09 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2022-09-09_final.stac-item
2022-09-19 12:14:29	ga_s2bm_ard_3-2-1_49KGP_2022-09-19_final.stac-item
2023-01-11 11:56:51	ga_s2bm_ard_3-2-1_50HLJ_2023-01-11_final.stac-item
2023-01-11 11:57:02	ga_s2bm_ard_3-2-1_50HMH_2023-01-11_final.stac-item
2023-01-18 11:46:38	ga_s2bm_ard_3-2-1_50HMK_2023-01-18_final.stac-item
2023-03-09 11:46:59	ga_s2bm_ard_3-2-1_50HMJ_2023-03-09_final
2023-05-04 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2023-05-04_final
2023-05-14 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-05-14_final
2023-05-18 11:47:14	ga_s2bm_ard_3-2-1_50HMH_2023-05-18_final
2023-05-24 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2023-05-24_final
2023-05-27 12:15:01	ga_s2bm_ard_3-2-1_49JGM_2023-05-27_final
2023-06-03 12:04:22	ga_s2bm_ard_3-2-1_49KGQ_2023-06-03_final
2023-06-03 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2023-06-03_final
2023-07-03 12:04:38	ga_s2bm_ard_3-2-1_49KHP_2023-07-03_final
2023-07-06 12:14:14	ga_s2bm_ard_3-2-1_49KHQ_2023-07-06_final
2023-07-16 12:14:14	ga_s2bm_ard_3-2-1_49KHQ_2023-07-16_final
2023-08-19 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2023-08-19_final
2023-08-22 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2023-08-22_final
2023-09-01 12:04:33	ga_s2bm_ard_3-2-1_49KHP_2023-09-01_final
2023-09-21 12:03:48	ga_s2bm_ard_3-2-1_49KHS_2023-09-21_final
2023-09-21 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2023-09-21_final
2023-09-24 12:13:58	ga_s2bm_ard_3-2-1_49KHR_2023-09-24_final
2023-09-24 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2023-09-24_final
2023-10-01 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2023-10-01_final
2023-10-11 12:04:32	ga_s2bm_ard_3-2-1_49KHP_2023-10-11_final
2023-10-24 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2023-10-24_final
2023-10-24 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2023-10-24_final
2023-10-25 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2023-10-25_final
2023-10-31 12:03:47	ga_s2bm_ard_3-2-1_49KHS_2023-10-31_final
2023-10-31 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-10-31_final
2023-11-10 12:03:46	ga_s2bm_ard_3-2-1_49KHS_2023-11-10_final
2023-11-30 12:05:12	ga_s2bm_ard_3-2-1_49JGL_2023-11-30_final
2023-12-10 12:04:53	ga_s2bm_ard_3-2-1_49JHM_2023-12-10_final
2023-12-20 12:04:14	ga_s2bm_ard_3-2-1_49KHQ_2023-12-20_final
2023-12-20 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2023-12-20_final
2024-01-19 12:04:56	ga_s2bm_ard_3-2-1_49JHM_2024-01-19_final
2024-01-29 12:04:11	ga_s2bm_ard_3-2-1_49KHQ_2024-01-29_final
2024-01-29 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2024-01-29_final
2024-02-08 12:05:00	ga_s2bm_ard_3-2-1_49JGM_2024-02-08_final
2024-02-08 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2024-02-08_final
2024-02-21 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2024-02-21_final
2024-02-28 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2024-02-28_final
2024-03-02 12:14:53	ga_s2bm_ard_3-2-1_49JGM_2024-03-02_final
2024-03-09 12:05:24	ga_s2bm_ard_3-2-1_49JGK_2024-03-09_final
2024-03-16 11:56:38	ga_s2bm_ard_3-2-1_50HLK_2024-03-16_final
2024-03-22 12:14:09	ga_s2bm_ard_3-2-1_49KHQ_2024-03-22_final
2024-04-01 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2024-04-01_final
2024-04-08 12:04:26	ga_s2bm_ard_3-2-1_49KGP_2024-04-08_final
2024-04-12 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2024-04-12_final
2024-04-18 12:05:02	ga_s2bm_ard_3-2-1_49JGM_2024-04-18_final
2024-04-28 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2024-04-28_nrt

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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