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
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLQ_2017-11-01_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JLR_2017-11-11_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50HQH_2017-12-25_final.stac-item
2018-05-10 12:05:05	ga_s2bm_ard_3-2-1_50JLQ_2018-05-10_final.stac-item
2018-06-22 12:13:20	ga_s2bm_ard_3-2-1_49KHP_2018-06-22_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_49KHP_2018-09-27_final.stac-item
2018-09-27 12:02:43	ga_s2bm_ard_3-2-1_50JKR_2018-09-27_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JKR_2018-10-17_final.stac-item
2018-10-21 11:45:13	ga_s2bm_ard_3-2-1_50HQK_2018-10-21_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50HLK_2018-11-03_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50JLR_2018-11-03_final.stac-item
2018-11-16 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2018-11-16_final.stac-item
2019-02-04 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_2019-02-04_final.stac-item
2019-02-08 11:46:54	ga_s2bm_ard_3-2-1_50HQH_2019-02-08_final.stac-item
2019-03-19 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2019-03-19_final.stac-item
2019-06-17 12:14:29	ga_s2bm_ard_3-2-1_49KHP_2019-06-17_final.stac-item
2019-08-03 12:05:30	ga_s2bm_ard_3-2-1_50JLQ_2019-08-03_final.stac-item
2019-10-15 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2019-10-15_final.stac-item
2019-11-08 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2019-11-08_final.stac-item
2019-11-18 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2019-11-18_final.stac-item
2019-11-21 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2019-11-21_final.stac-item
2019-11-28 11:55:08	ga_s2bm_ard_3-2-1_50JLR_2019-11-28_final.stac-item
2019-11-28 11:55:23	ga_s2bm_ard_3-2-1_50JLQ_2019-11-28_final.stac-item
2019-12-12 11:36:36	ga_s2bm_ard_3-2-1_50HQJ_2019-12-12_final.stac-item
2019-12-15 11:46:17	ga_s2bm_ard_3-2-1_50HQK_2019-12-15_final.stac-item
2020-05-02 12:14:01	ga_s2bm_ard_3-2-1_49KHQ_2020-05-02_final.stac-item
2020-05-22 12:14:05	ga_s2bm_ard_3-2-1_49KHQ_2020-05-22_final.stac-item
2020-05-22 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2020-05-22_final.stac-item
2020-07-28 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2020-07-28_final.stac-item
2020-08-07 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2020-08-07_final.stac-item
2020-09-06 12:05:00	ga_s2bm_ard_3-2-1_50JKS_2020-09-06_final.stac-item
2020-09-06 12:05:29	ga_s2bm_ard_3-2-1_50JKQ_2020-09-06_final.stac-item
2020-09-19 12:14:23	ga_s2bm_ard_3-2-1_49KHP_2020-09-19_final.stac-item
2020-10-03 11:55:31	ga_s2bm_ard_3-2-1_50JLQ_2020-10-03_final.stac-item
2020-11-25 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2020-11-25_final.stac-item
2020-12-12 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2020-12-12_final.stac-item
2021-01-21 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2021-01-21_final.stac-item
2021-01-31 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2021-01-31_final.stac-item
2021-09-11 12:04:19	ga_s2bm_ard_3-2-1_49KGP_2021-09-11_final.stac-item
2021-09-11 12:06:01	ga_s2bm_ard_3-2-1_50JLM_2021-09-11_final.stac-item
2021-09-21 12:05:09	ga_s2bm_ard_3-2-1_50JKR_2021-09-21_final.stac-item
2021-09-28 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2021-09-28_final.stac-item
2021-10-18 11:56:38	ga_s2bm_ard_3-2-1_50HMK_2021-10-18_final.stac-item
2021-11-10 12:05:11	ga_s2bm_ard_3-2-1_50JKR_2021-11-10_final.stac-item
2021-11-20 12:05:09	ga_s2bm_ard_3-2-1_50JKR_2021-11-20_final.stac-item
2021-12-03 12:14:16	ga_s2bm_ard_3-2-1_49KHP_2021-12-03_final.stac-item
2021-12-13 12:14:15	ga_s2bm_ard_3-2-1_49KHP_2021-12-13_final.stac-item
2021-12-23 12:14:16	ga_s2bm_ard_3-2-1_49KHP_2021-12-23_final.stac-item
2021-12-30 12:05:08	ga_s2bm_ard_3-2-1_50JKR_2021-12-30_final.stac-item
2022-01-03 11:46:19	ga_s2bm_ard_3-2-1_50HQK_2022-01-03_final.stac-item
2022-02-01 12:14:03	ga_s2bm_ard_3-2-1_49KHQ_2022-02-01_final.stac-item
2022-02-05 11:55:22	ga_s2bm_ard_3-2-1_50JLQ_2022-02-05_final.stac-item
2022-03-07 11:55:10	ga_s2bm_ard_3-2-1_50JLR_2022-03-07_final.stac-item
2022-05-06 11:55:08	ga_s2bm_ard_3-2-1_50JLR_2022-05-06_final.stac-item
2022-05-09 12:05:09	ga_s2bm_ard_3-2-1_50JKR_2022-05-09_final.stac-item
2022-05-26 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2022-05-26_final.stac-item
2022-06-01 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2022-06-01_final.stac-item
2022-07-08 12:05:17	ga_s2bm_ard_3-2-1_50JKR_2022-07-08_final.stac-item
2022-08-07 12:05:27	ga_s2bm_ard_3-2-1_50JLQ_2022-08-07_final.stac-item
2022-09-16 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2022-09-16_final.stac-item
2022-09-23 11:54:59	ga_s2bm_ard_3-2-1_50JLS_2022-09-23_final.stac-item
2022-10-03 11:54:56	ga_s2bm_ard_3-2-1_50JLS_2022-10-03_final.stac-item
2022-10-13 11:56:35	ga_s2bm_ard_3-2-1_50HMK_2022-10-13_final.stac-item
2022-11-22 11:54:57	ga_s2bm_ard_3-2-1_50JLS_2022-11-22_final.stac-item
2022-11-22 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2022-11-22_final.stac-item
2022-12-12 11:54:55	ga_s2bm_ard_3-2-1_50JLS_2022-12-12_final.stac-item
2023-01-04 12:04:52	ga_s2bm_ard_3-2-1_50JLS_2023-01-04_final.stac-item
2023-01-04 12:05:10	ga_s2bm_ard_3-2-1_50JKR_2023-01-04_final.stac-item
2023-02-03 12:05:08	ga_s2bm_ard_3-2-1_50JKR_2023-02-03_final.stac-item
2023-02-10 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2023-02-10_final.stac-item
2023-02-13 12:05:10	ga_s2bm_ard_3-2-1_50JKR_2023-02-13_final
2023-02-20 11:54:57	ga_s2bm_ard_3-2-1_50JLS_2023-02-20_final
2023-03-08 12:14:24	ga_s2bm_ard_3-2-1_49KHP_2023-03-08_final
2023-05-04 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2023-05-04_final
2023-05-08 11:47:30	ga_s2bm_ard_3-2-1_50HLG_2023-05-08_final
2023-05-21 11:57:27	ga_s2bm_ard_3-2-1_50HLG_2023-05-21_final
2023-06-10 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-06-10_final
2023-06-10 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-06-10_final
2023-06-13 12:05:13	ga_s2bm_ard_3-2-1_49JFM_2023-06-13_final
2023-07-06 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-07-06_final
2023-07-10 11:55:18	ga_s2bm_ard_3-2-1_50JLR_2023-07-10_final
2023-07-10 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-07-10_final
2023-08-22 12:05:24	ga_s2bm_ard_3-2-1_50JKR_2023-08-22_final
2023-08-29 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-08-29_final
2023-09-01 12:04:58	ga_s2bm_ard_3-2-1_50JLS_2023-09-01_final
2023-09-08 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-09-08_final
2023-09-11 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2023-09-11_final
2023-10-05 11:46:53	ga_s2bm_ard_3-2-1_50HQH_2023-10-05_final
2023-11-30 12:05:02	ga_s2bm_ard_3-2-1_50JKR_2023-11-30_final
2023-12-04 11:46:50	ga_s2bm_ard_3-2-1_50HQH_2023-12-04_final
2023-12-30 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2023-12-30_final
2024-01-16 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2024-01-16_final
2024-01-26 11:55:11	ga_s2bm_ard_3-2-1_50JLR_2024-01-26_final
2024-02-11 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2024-02-11_final
2024-02-21 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2024-02-21_final
2024-03-19 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2024-03-19_final
2024-03-19 12:05:22	ga_s2bm_ard_3-2-1_50JLQ_2024-03-19_final
2024-04-01 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2024-04-01_final
2024-04-08 12:05:07	ga_s2bm_ard_3-2-1_50JLR_2024-04-08_final
2024-04-18 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2024-04-18_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