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
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_49JFM_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JKQ_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JLQ_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JLR_2017-07-14_final.stac-item
2017-08-03 12:04:41	ga_s2bm_ard_3-2-1_49JHN_2017-08-03_final.stac-item
2017-08-03 12:04:41	ga_s2bm_ard_3-2-1_50JKQ_2017-08-03_final.stac-item
2017-08-03 12:04:41	ga_s2bm_ard_3-2-1_50JLQ_2017-08-03_final.stac-item
2017-09-12 12:04:33	ga_s2bm_ard_3-2-1_50JKT_2017-09-12_final.stac-item
2017-09-15 12:13:36	ga_s2bm_ard_3-2-1_49KHP_2017-09-15_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_49JHN_2017-10-02_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_50JLQ_2017-10-02_final.stac-item
2017-10-05 12:13:31	ga_s2bm_ard_3-2-1_49KHP_2017-10-05_final.stac-item
2017-10-22 12:04:28	ga_s2bm_ard_3-2-1_50JKT_2017-10-22_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLR_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
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_50JLR_2017-11-21_final.stac-item
2017-12-01 12:02:38	ga_s2bm_ard_3-2-1_50JLR_2017-12-01_final.stac-item
2018-09-04 11:52:51	ga_s2bm_ard_3-2-1_50JKN_2018-09-04_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JLR_2018-10-17_final.stac-item
2018-11-06 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2018-11-06_final.stac-item
2018-11-26 12:05:04	ga_s2bm_ard_3-2-1_50JLR_2018-11-26_final.stac-item
2019-02-01 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2019-02-01_final.stac-item
2019-02-04 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2019-02-04_final.stac-item
2019-02-11 11:55:21	ga_s2bm_ard_3-2-1_50JLQ_2019-02-11_final.stac-item
2019-02-24 12:05:07	ga_s2bm_ard_3-2-1_50JLR_2019-02-24_final.stac-item
2019-03-16 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2019-03-16_final.stac-item
2019-03-16 12:05:19	ga_s2bm_ard_3-2-1_50JKQ_2019-03-16_final.stac-item
2019-03-26 12:05:18	ga_s2bm_ard_3-2-1_50JLQ_2019-03-26_final.stac-item
2019-04-05 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2019-04-05_final.stac-item
2019-04-25 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2019-04-25_final.stac-item
2019-04-25 12:05:31	ga_s2bm_ard_3-2-1_50JLQ_2019-04-25_final.stac-item
2019-05-02 11:55:35	ga_s2bm_ard_3-2-1_50JLQ_2019-05-02_final.stac-item
2019-05-05 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-05_final.stac-item
2019-05-15 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-15_final.stac-item
2019-09-12 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2019-09-12_final.stac-item
2019-09-29 11:55:28	ga_s2bm_ard_3-2-1_50JLQ_2019-09-29_final.stac-item
2020-03-10 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2020-03-10_final.stac-item
2020-03-10 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2020-03-10_final.stac-item
2020-04-09 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2020-04-09_final.stac-item
2020-04-09 12:05:16	ga_s2bm_ard_3-2-1_50JLQ_2020-04-09_final.stac-item
2020-04-09 12:05:18	ga_s2bm_ard_3-2-1_50JKQ_2020-04-09_final.stac-item
2020-05-19 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2020-05-19_final.stac-item
2020-05-19 12:05:12	ga_s2bm_ard_3-2-1_50JKR_2020-05-19_final.stac-item
2020-05-19 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2020-05-19_final.stac-item
2020-05-19 12:05:20	ga_s2bm_ard_3-2-1_49JGK_2020-05-19_final.stac-item
2020-06-08 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2020-06-08_final.stac-item
2020-06-08 12:05:19	ga_s2bm_ard_3-2-1_50JLQ_2020-06-08_final.stac-item
2020-07-08 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2020-07-08_final.stac-item
2020-07-08 12:05:14	ga_s2bm_ard_3-2-1_50JKR_2020-07-08_final.stac-item
2020-07-08 12:05:21	ga_s2bm_ard_3-2-1_50JLQ_2020-07-08_final.stac-item
2020-07-18 12:05:21	ga_s2bm_ard_3-2-1_50JKQ_2020-07-18_final.stac-item
2020-07-28 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2020-07-28_final.stac-item
2020-08-27 12:04:51	ga_s2bm_ard_3-2-1_50JKS_2020-08-27_final.stac-item
2020-08-27 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2020-08-27_final.stac-item
2020-09-13 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2020-09-13_final.stac-item
2020-09-16 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2020-09-16_final.stac-item
2020-09-23 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2020-09-23_final.stac-item
2020-10-06 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2020-10-06_final.stac-item
2020-10-16 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2020-10-16_final.stac-item
2020-10-16 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2020-10-16_final.stac-item
2021-02-10 11:55:23	ga_s2bm_ard_3-2-1_50JLQ_2021-02-10_final.stac-item
2021-02-17 11:47:24	ga_s2bm_ard_3-2-1_50HLG_2021-02-17_final
2021-03-09 11:47:27	ga_s2bm_ard_3-2-1_50HLG_2021-03-09_final
2021-04-14 12:04:19	ga_s2bm_ard_3-2-1_49KGP_2021-04-14_final.stac-item
2021-04-14 12:04:44	ga_s2bm_ard_3-2-1_49JHM_2021-04-14_final.stac-item
2021-04-24 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2021-04-24_final.stac-item
2021-04-24 12:05:06	ga_s2bm_ard_3-2-1_50JKR_2021-04-24_final.stac-item
2021-07-30 11:57:25	ga_s2bm_ard_3-2-1_50HLG_2021-07-30_final
2022-01-19 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2022-01-19_final.stac-item
2022-03-10 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2022-03-10_final.stac-item
2022-03-10 12:05:21	ga_s2bm_ard_3-2-1_50JLQ_2022-03-10_final.stac-item
2022-03-17 11:55:25	ga_s2bm_ard_3-2-1_50JLQ_2022-03-17_final.stac-item
2022-05-09 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2022-05-09_final.stac-item
2022-05-09 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2022-05-09_final.stac-item
2022-06-28 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2022-06-28_final.stac-item
2022-07-05 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2022-07-05_final.stac-item
2022-07-08 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2022-07-08_final.stac-item
2022-07-08 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2022-07-08_final.stac-item
2022-07-15 11:55:02	ga_s2bm_ard_3-2-1_50JLS_2022-07-15_final.stac-item
2022-08-14 11:55:01	ga_s2bm_ard_3-2-1_50JLS_2022-08-14_final.stac-item
2022-08-24 11:54:58	ga_s2bm_ard_3-2-1_50JLS_2022-08-24_final.stac-item
2023-01-11 11:57:16	ga_s2bm_ard_3-2-1_50HMG_2023-01-11_final
2023-02-13 12:05:07	ga_s2bm_ard_3-2-1_50JLR_2023-02-13_final
2023-02-20 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2023-02-20_final
2023-03-15 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2023-03-15_final
2023-03-29 11:47:31	ga_s2bm_ard_3-2-1_50HLG_2023-03-29_final
2023-04-04 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2023-04-04_final
2023-05-04 12:04:36	ga_s2bm_ard_3-2-1_50JKT_2023-05-04_final
2023-05-18 11:47:31	ga_s2bm_ard_3-2-1_50HLG_2023-05-18_final
2023-05-21 11:57:27	ga_s2bm_ard_3-2-1_50HLG_2023-05-21_final
2023-06-13 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2023-06-13_final
2023-07-03 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2023-07-03_final
2023-07-23 12:05:29	ga_s2bm_ard_3-2-1_50JLQ_2023-07-23_final
2023-08-22 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_2023-08-22_final
2023-09-01 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2023-09-01_final
2023-09-01 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-09-01_final
2023-09-08 11:55:32	ga_s2bm_ard_3-2-1_50JLQ_2023-09-08_final
2023-10-01 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2023-10-01_final
2024-01-10 11:37:25	ga_s2bm_ard_3-2-1_50HNG_2024-01-10_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