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
2017-12-24 12:13:09	ga_s2bm_ard_3-2-1_49JGL_2017-12-24_final.stac-item
2018-03-04 12:13:52	ga_s2bm_ard_3-2-1_49JHN_2018-03-04_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_49JHM_2018-06-19_final.stac-item
2018-06-22 12:14:14	ga_s2bm_ard_3-2-1_49JGN_2018-06-22_final.stac-item
2018-08-11 12:13:16	ga_s2bm_ard_3-2-1_49JGN_2018-08-11_final.stac-item
2018-12-06 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2018-12-06_final.stac-item
2018-12-26 12:05:11	ga_s2bm_ard_3-2-1_49JGL_2018-12-26_final.stac-item
2019-01-18 12:14:56	ga_s2bm_ard_3-2-1_49JGM_2019-01-18_final.stac-item
2019-05-08 12:15:08	ga_s2bm_ard_3-2-1_49JFM_2019-05-08_final.stac-item
2019-06-17 12:14:49	ga_s2bm_ard_3-2-1_49JGN_2019-06-17_final.stac-item
2019-07-14 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-07-14_final.stac-item
2019-07-14 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-14_final.stac-item
2019-07-17 12:14:50	ga_s2bm_ard_3-2-1_49JGN_2019-07-17_final.stac-item
2019-08-16 12:15:02	ga_s2bm_ard_3-2-1_49JGM_2019-08-16_final.stac-item
2019-09-02 12:04:49	ga_s2bm_ard_3-2-1_49JGN_2019-09-02_final.stac-item
2019-09-12 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2019-09-12_final.stac-item
2019-10-02 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-10-02_final.stac-item
2019-10-05 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2019-10-05_final.stac-item
2019-10-22 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2019-10-22_final.stac-item
2019-10-25 12:15:11	ga_s2bm_ard_3-2-1_49JGL_2019-10-25_final.stac-item
2019-12-21 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2019-12-21_final.stac-item
2019-12-21 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2019-12-21_final.stac-item
2020-01-20 12:05:08	ga_s2bm_ard_3-2-1_49JGL_2020-01-20_final.stac-item
2020-01-30 12:05:07	ga_s2bm_ard_3-2-1_49JGL_2020-01-30_final.stac-item
2020-02-02 12:15:03	ga_s2bm_ard_3-2-1_49JGL_2020-02-02_final.stac-item
2020-03-03 12:14:39	ga_s2bm_ard_3-2-1_49JGN_2020-03-03_final.stac-item
2020-03-23 12:14:39	ga_s2bm_ard_3-2-1_49JGN_2020-03-23_final.stac-item
2020-03-30 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2020-03-30_final.stac-item
2020-04-09 12:05:26	ga_s2bm_ard_3-2-1_49JGK_2020-04-09_final.stac-item
2020-04-19 12:04:41	ga_s2bm_ard_3-2-1_49JGN_2020-04-19_final.stac-item
2020-05-09 12:05:13	ga_s2bm_ard_3-2-1_49JGL_2020-05-09_final.stac-item
2020-06-11 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2020-06-11_final.stac-item
2020-06-21 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2020-06-21_final.stac-item
2020-07-28 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2020-07-28_final.stac-item
2020-08-17 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2020-08-17_final.stac-item
2020-08-27 12:05:00	ga_s2bm_ard_3-2-1_49JHM_2020-08-27_final.stac-item
2020-09-26 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2020-09-26_final.stac-item
2020-12-05 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2020-12-05_final.stac-item
2021-01-24 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2021-01-24_final.stac-item
2021-03-05 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2021-03-05_final.stac-item
2021-03-05 12:04:56	ga_s2bm_ard_3-2-1_49JHM_2021-03-05_final.stac-item
2021-03-18 12:14:55	ga_s2bm_ard_3-2-1_49JGM_2021-03-18_final.stac-item
2021-03-28 12:14:58	ga_s2bm_ard_3-2-1_49JFM_2021-03-28_final.stac-item
2021-04-04 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2021-04-04_final.stac-item
2021-04-17 12:14:37	ga_s2bm_ard_3-2-1_49JGN_2021-04-17_final.stac-item
2021-05-17 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2021-05-17_final.stac-item
2021-09-01 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2021-09-01_final.stac-item
2021-09-21 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2021-09-21_final.stac-item
2021-12-13 12:14:50	ga_s2bm_ard_3-2-1_49JGM_2021-12-13_final.stac-item
2021-12-13 12:15:05	ga_s2bm_ard_3-2-1_49JGL_2021-12-13_final.stac-item
2022-01-09 12:04:42	ga_s2bm_ard_3-2-1_49JGN_2022-01-09_final.stac-item
2022-03-10 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2022-03-10_final.stac-item
2022-03-30 12:04:38	ga_s2bm_ard_3-2-1_49JGN_2022-03-30_final.stac-item
2022-04-19 12:04:36	ga_s2bm_ard_3-2-1_49JGN_2022-04-19_final.stac-item
2022-04-19 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2022-04-19_final.stac-item
2022-04-29 12:04:34	ga_s2bm_ard_3-2-1_49JGN_2022-04-29_final.stac-item
2022-04-29 12:04:41	ga_s2bm_ard_3-2-1_49JGN_2022-04-29_final.stac-item
2022-05-19 12:05:00	ga_s2bm_ard_3-2-1_49JGM_2022-05-19_final.stac-item
2022-07-08 12:05:05	ga_s2bm_ard_3-2-1_49JGM_2022-07-08_final.stac-item
2022-08-07 12:04:52	ga_s2bm_ard_3-2-1_49JGN_2022-08-07_final.stac-item
2022-09-06 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2022-09-06_final.stac-item
2022-09-16 12:05:02	ga_s2bm_ard_3-2-1_49JGM_2022-09-16_final.stac-item
2022-11-05 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2022-11-05_final.stac-item
2023-03-25 12:05:03	ga_s2bm_ard_3-2-1_49JGM_2023-03-25_final
2023-04-04 12:04:49	ga_s2bm_ard_3-2-1_49JGN_2023-04-04_final
2023-04-07 12:14:59	ga_s2bm_ard_3-2-1_49JGM_2023-04-07_final
2023-04-14 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2023-04-14_final
2023-05-04 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2023-05-04_final
2023-05-04 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-05-04_final
2023-05-14 12:04:49	ga_s2bm_ard_3-2-1_49JGN_2023-05-14_final
2023-05-24 12:04:51	ga_s2bm_ard_3-2-1_49JGN_2023-05-24_final
2023-06-03 12:04:50	ga_s2bm_ard_3-2-1_49JGN_2023-06-03_final
2023-06-03 12:05:19	ga_s2bm_ard_3-2-1_49JGL_2023-06-03_final
2023-06-13 12:05:13	ga_s2bm_ard_3-2-1_49JFM_2023-06-13_final
2023-07-13 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-07-13_final
2023-07-16 12:14:46	ga_s2bm_ard_3-2-1_49JGN_2023-07-16_final
2023-08-05 12:14:46	ga_s2bm_ard_3-2-1_49JGN_2023-08-05_final
2023-08-12 12:05:49	ga_s2bm_ard_3-2-1_49JGJ_2023-08-12_final
2023-09-21 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-09-21_final
2023-09-24 12:14:59	ga_s2bm_ard_3-2-1_49JGM_2023-09-24_final
2023-10-04 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2023-10-04_final
2023-10-11 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2023-10-11_final
2023-10-14 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2023-10-14_final
2023-10-31 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2023-10-31_final
2023-11-03 12:14:59	ga_s2bm_ard_3-2-1_49JGM_2023-11-03_final
2023-11-10 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2023-11-10_final
2023-11-23 12:15:06	ga_s2bm_ard_3-2-1_49JGL_2023-11-23_final
2023-11-30 12:04:43	ga_s2bm_ard_3-2-1_49JGN_2023-11-30_final
2023-12-10 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2023-12-10_final
2023-12-23 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2023-12-23_final
2024-01-29 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2024-01-29_final
2024-02-08 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2024-02-08_final
2024-02-18 12:04:47	ga_s2bm_ard_3-2-1_49JGN_2024-02-18_final
2024-02-28 12:04:44	ga_s2bm_ard_3-2-1_49JGN_2024-02-28_final
2024-03-09 12:04:41	ga_s2bm_ard_3-2-1_49JGN_2024-03-09_final
2024-03-09 12:05:10	ga_s2bm_ard_3-2-1_49JGL_2024-03-09_final
2024-03-12 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2024-03-12_final
2024-03-12 12:14:56	ga_s2bm_ard_3-2-1_49JFM_2024-03-12_final
2024-04-21 12:14:42	ga_s2bm_ard_3-2-1_49JGN_2024-04-21_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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