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
2017-08-20 11:49:42	ga_s2bm_ard_3-2-1_50JMQ_2017-08-20_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50JNN_2017-11-05_final.stac-item
2017-11-14 12:13:08	ga_s2bm_ard_3-2-1_49KHQ_2017-11-14_final.stac-item
2017-11-24 12:13:09	ga_s2bm_ard_3-2-1_49KHP_2017-11-24_final.stac-item
2017-11-24 12:13:09	ga_s2bm_ard_3-2-1_49KHQ_2017-11-24_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_50JKR_2017-12-11_final.stac-item
2017-12-14 12:13:09	ga_s2bm_ard_3-2-1_49KHQ_2017-12-14_final.stac-item
2018-01-07 11:50:37	ga_s2bm_ard_3-2-1_50JMP_2018-01-07_final.stac-item
2018-01-27 11:50:39	ga_s2bm_ard_3-2-1_50JLS_2018-01-27_final.stac-item
2018-02-06 11:49:12	ga_s2bm_ard_3-2-1_50JMS_2018-02-06_final.stac-item
2018-02-09 12:02:42	ga_s2bm_ard_3-2-1_50JMS_2018-02-09_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50HQH_2018-02-13_final.stac-item
2018-02-16 11:50:39	ga_s2bm_ard_3-2-1_50JLS_2018-02-16_final.stac-item
2018-03-05 11:42:06	ga_s2bm_ard_3-2-1_50HQH_2018-03-05_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JLQ_2018-03-21_final.stac-item
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50JMR_2018-05-17_final.stac-item
2018-06-16 11:51:10	ga_s2bm_ard_3-2-1_50JLR_2018-06-16_final.stac-item
2018-07-29 12:02:46	ga_s2bm_ard_3-2-1_50JLS_2018-07-29_final.stac-item
2018-08-18 12:03:23	ga_s2bm_ard_3-2-1_50JLQ_2018-08-18_final.stac-item
2018-09-27 12:04:56	ga_s2bm_ard_3-2-1_50JLR_2018-09-27_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JLQ_2018-10-17_final.stac-item
2018-11-19 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2018-11-19_final.stac-item
2018-11-27 11:36:30	ga_s2bm_ard_3-2-1_50HQK_2018-11-27_final.stac-item
2018-12-26 12:04:55	ga_s2bm_ard_3-2-1_50JMR_2018-12-26_final.stac-item
2019-01-22 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2019-01-22_final.stac-item
2019-01-25 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_2019-01-25_final.stac-item
2019-03-16 12:04:52	ga_s2bm_ard_3-2-1_50JLS_2019-03-16_final.stac-item
2019-03-20 11:46:47	ga_s2bm_ard_3-2-1_50HMK_2019-03-20_final.stac-item
2019-04-08 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2019-04-08_final.stac-item
2019-06-14 12:05:31	ga_s2bm_ard_3-2-1_50JLQ_2019-06-14_final.stac-item
2019-07-14 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2019-07-14_final.stac-item
2019-07-17 12:14:30	ga_s2bm_ard_3-2-1_49KHP_2019-07-17_final.stac-item
2019-08-06 12:14:12	ga_s2bm_ard_3-2-1_49KHQ_2019-08-06_final.stac-item
2019-09-09 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2019-09-09_final.stac-item
2019-11-05 11:46:54	ga_s2bm_ard_3-2-1_50HQH_2019-11-05_final.stac-item
2019-11-08 11:54:58	ga_s2bm_ard_3-2-1_50JLS_2019-11-08_final.stac-item
2019-11-28 11:55:34	ga_s2bm_ard_3-2-1_50JMP_2019-11-28_final.stac-item
2019-12-08 11:55:33	ga_s2bm_ard_3-2-1_50JMP_2019-12-08_final.stac-item
2019-12-18 11:55:33	ga_s2bm_ard_3-2-1_50JMP_2019-12-18_final.stac-item
2020-02-26 11:55:07	ga_s2bm_ard_3-2-1_50JMR_2020-02-26_final.stac-item
2020-03-07 11:55:36	ga_s2bm_ard_3-2-1_50JMP_2020-03-07_final.stac-item
2020-04-06 11:55:36	ga_s2bm_ard_3-2-1_50JMP_2020-04-06_final.stac-item
2020-04-16 11:55:34	ga_s2bm_ard_3-2-1_50JMP_2020-04-16_final.stac-item
2020-05-12 12:14:07	ga_s2bm_ard_3-2-1_49KHQ_2020-05-12_final.stac-item
2020-05-16 11:55:38	ga_s2bm_ard_3-2-1_50JMP_2020-05-16_final.stac-item
2020-07-25 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2020-07-25_final.stac-item
2020-07-31 12:14:11	ga_s2bm_ard_3-2-1_49KHQ_2020-07-31_final.stac-item
2020-08-30 12:14:24	ga_s2bm_ard_3-2-1_49KHP_2020-08-30_final.stac-item
2020-09-03 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2020-09-03_final.stac-item
2020-10-03 11:54:48	ga_s2bm_ard_3-2-1_50JLT_2020-10-03_final.stac-item
2020-10-03 11:55:13	ga_s2bm_ard_3-2-1_50JMR_2020-10-03_final.stac-item
2020-11-05 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2020-11-05_final.stac-item
2020-11-22 11:55:39	ga_s2bm_ard_3-2-1_50JMP_2020-11-22_final.stac-item
2020-12-22 11:54:54	ga_s2bm_ard_3-2-1_50JLS_2020-12-22_final.stac-item
2020-12-25 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2020-12-25_final.stac-item
2021-01-08 11:46:52	ga_s2bm_ard_3-2-1_50HQH_2021-01-08_final.stac-item
2021-01-21 11:55:38	ga_s2bm_ard_3-2-1_50JMP_2021-01-21_final.stac-item
2021-03-15 12:05:11	ga_s2bm_ard_3-2-1_50JKR_2021-03-15_final.stac-item
2021-04-21 11:55:07	ga_s2bm_ard_3-2-1_50JLR_2021-04-21_final.stac-item
2021-05-14 12:04:38	ga_s2bm_ard_3-2-1_50JLT_2021-05-14_final.stac-item
2021-06-13 12:04:55	ga_s2bm_ard_3-2-1_50JLS_2021-06-13_final.stac-item
2021-08-26 11:47:19	ga_s2bm_ard_3-2-1_50HNG_2021-08-26_final
2021-09-21 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2021-09-21_final.stac-item
2021-10-01 12:04:22	ga_s2bm_ard_3-2-1_49KGP_2021-10-01_final.stac-item
2021-12-17 11:55:06	ga_s2bm_ard_3-2-1_50JLR_2021-12-17_final.stac-item
2021-12-20 12:05:03	ga_s2bm_ard_3-2-1_49JFM_2021-12-20_final.stac-item
2022-01-26 11:55:07	ga_s2bm_ard_3-2-1_50JLR_2022-01-26_final.stac-item
2022-01-29 12:05:02	ga_s2bm_ard_3-2-1_50JLR_2022-01-29_final.stac-item
2022-04-09 12:04:50	ga_s2bm_ard_3-2-1_50JLS_2022-04-09_final.stac-item
2022-05-06 11:55:05	ga_s2bm_ard_3-2-1_50JMR_2022-05-06_final.stac-item
2022-05-06 11:55:34	ga_s2bm_ard_3-2-1_50JMP_2022-05-06_final.stac-item
2022-10-23 11:55:34	ga_s2bm_ard_3-2-1_50JNP_2022-10-23_final.stac-item
2022-11-12 11:55:38	ga_s2bm_ard_3-2-1_50JMP_2022-11-12_final.stac-item
2022-12-02 11:54:42	ga_s2bm_ard_3-2-1_50JLT_2022-12-02_final.stac-item
2023-03-25 12:04:36	ga_s2bm_ard_3-2-1_49KHP_2023-03-25_final
2023-05-14 12:05:12	ga_s2bm_ard_3-2-1_49JFM_2023-05-14_final
2023-05-27 12:14:25	ga_s2bm_ard_3-2-1_49KHP_2023-05-27_final
2023-06-07 11:46:58	ga_s2bm_ard_3-2-1_50HQH_2023-06-07_final
2023-08-05 12:13:45	ga_s2bm_ard_3-2-1_49KHS_2023-08-05_final
2023-08-05 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-08-05_final
2023-08-15 12:13:45	ga_s2bm_ard_3-2-1_49KHS_2023-08-15_final
2023-09-04 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-09-04_final
2023-09-25 11:46:57	ga_s2bm_ard_3-2-1_50HQH_2023-09-25_final
2023-10-05 11:46:53	ga_s2bm_ard_3-2-1_50HQH_2023-10-05_final
2023-10-14 12:14:23	ga_s2bm_ard_3-2-1_49KHP_2023-10-14_final
2023-11-04 11:46:56	ga_s2bm_ard_3-2-1_50HQH_2023-11-04_final
2023-11-23 12:14:11	ga_s2bm_ard_3-2-1_49KFQ_2023-11-23_nrt
2023-11-30 12:04:51	ga_s2bm_ard_3-2-1_50JLS_2023-11-30_final
2023-11-30 12:05:01	ga_s2bm_ard_3-2-1_50JLR_2023-11-30_final
2023-12-07 11:55:35	ga_s2bm_ard_3-2-1_50JMP_2023-12-07_final
2023-12-17 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2023-12-17_final
2023-12-24 11:47:29	ga_s2bm_ard_3-2-1_50HLG_2023-12-24_final
2024-01-06 11:55:27	ga_s2bm_ard_3-2-1_50JLQ_2024-01-06_final
2024-03-16 11:54:39	ga_s2bm_ard_3-2-1_50JMT_2024-03-16_final
2024-03-19 12:05:11	ga_s2bm_ard_3-2-1_50JKR_2024-03-19_final
2024-03-22 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2024-03-22_final
2024-03-23 11:45:54	ga_s2bm_ard_3-2-1_50JNN_2024-03-23_final
2024-04-05 11:57:20	ga_s2bm_ard_3-2-1_50HLG_2024-04-05_final
2024-04-22 11:47:24	ga_s2bm_ard_3-2-1_50HMG_2024-04-22_final
2024-05-08 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2024-05-08_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