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
2017-07-18 11:45:05	ga_s2bm_ard_3-2-1_50HQJ_2017-07-18_final.stac-item
2017-09-02 12:02:43	ga_s2bm_ard_3-2-1_49KGP_2017-09-02_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_50HPJ_2017-10-13_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50HNH_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50HPK_2017-11-05_final.stac-item
2017-12-01 12:02:38	ga_s2bm_ard_3-2-1_49JGJ_2017-12-01_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49JGL_2017-12-21_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JKP_2017-12-28_final.stac-item
2018-03-08 11:51:37	ga_s2bm_ard_3-2-1_50JLN_2018-03-08_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JKN_2018-04-27_final.stac-item
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50HLH_2018-05-07_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50HQK_2018-05-14_final.stac-item
2018-06-03 11:46:44	ga_s2bm_ard_3-2-1_50HNH_2018-06-03_final.stac-item
2018-07-22 12:13:59	ga_s2bm_ard_3-2-1_49JGL_2018-07-22_final.stac-item
2018-07-23 11:40:57	ga_s2bm_ard_3-2-1_50HNH_2018-07-23_final.stac-item
2018-08-02 11:44:54	ga_s2bm_ard_3-2-1_50HMJ_2018-08-02_final.stac-item
2018-08-21 12:13:14	ga_s2bm_ard_3-2-1_49KHR_2018-08-21_final.stac-item
2018-09-20 12:13:54	ga_s2bm_ard_3-2-1_49KGP_2018-09-20_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50HMK_2018-09-21_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JKP_2018-09-24_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50HLJ_2018-10-04_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49KGP_2018-10-30_final.stac-item
2018-11-10 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2018-11-10_final.stac-item
2018-12-10 11:46:31	ga_s2bm_ard_3-2-1_50HNK_2018-12-10_final.stac-item
2018-12-23 11:55:08	ga_s2bm_ard_3-2-1_50JLR_2018-12-23_final.stac-item
2018-12-30 11:46:40	ga_s2bm_ard_3-2-1_50HQJ_2018-12-30_final.stac-item
2019-01-18 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-01-18_final.stac-item
2019-02-11 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2019-02-11_final.stac-item
2019-02-14 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2019-02-14_final.stac-item
2019-03-29 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2019-03-29_final.stac-item
2019-05-05 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2019-05-05_final.stac-item
2019-05-25 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2019-05-25_final.stac-item
2019-06-21 11:56:38	ga_s2bm_ard_3-2-1_50HNK_2019-06-21_final.stac-item
2019-06-27 12:14:07	ga_s2bm_ard_3-2-1_49KGR_2019-06-27_final.stac-item
2019-08-27 11:46:52	ga_s2bm_ard_3-2-1_50HPJ_2019-08-27_final.stac-item
2019-09-22 12:05:55	ga_s2bm_ard_3-2-1_50JKN_2019-09-22_final.stac-item
2019-09-29 11:56:00	ga_s2bm_ard_3-2-1_50JKN_2019-09-29_final.stac-item
2019-10-22 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2019-10-22_final.stac-item
2019-12-01 12:05:36	ga_s2bm_ard_3-2-1_50JKP_2019-12-01_final.stac-item
2019-12-05 11:46:31	ga_s2bm_ard_3-2-1_50HNK_2019-12-05_final.stac-item
2019-12-15 11:46:32	ga_s2bm_ard_3-2-1_50HNK_2019-12-15_final.stac-item
2020-01-13 12:15:05	ga_s2bm_ard_3-2-1_49JGL_2020-01-13_final.stac-item
2020-02-23 11:46:37	ga_s2bm_ard_3-2-1_50HMK_2020-02-23_final.stac-item
2020-03-30 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2020-03-30_final.stac-item
2020-04-03 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2020-04-03_final.stac-item
2020-05-26 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2020-05-26_final.stac-item
2020-07-22 11:46:55	ga_s2bm_ard_3-2-1_50HNJ_2020-07-22_final.stac-item
2020-07-29 11:36:40	ga_s2bm_ard_3-2-1_50HPK_2020-07-29_final.stac-item
2020-08-04 11:55:49	ga_s2bm_ard_3-2-1_50JKP_2020-08-04_final.stac-item
2020-08-08 11:36:41	ga_s2bm_ard_3-2-1_50HPK_2020-08-08_final.stac-item
2020-09-30 11:46:40	ga_s2bm_ard_3-2-1_50HNK_2020-09-30_final.stac-item
2020-10-17 11:37:10	ga_s2bm_ard_3-2-1_50HPH_2020-10-17_final.stac-item
2020-11-19 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2020-11-19_final.stac-item
2020-12-12 11:55:53	ga_s2bm_ard_3-2-1_50JLN_2020-12-12_final.stac-item
2021-01-24 12:05:12	ga_s2bm_ard_3-2-1_50JKR_2021-01-24_final.stac-item
2021-02-10 11:55:41	ga_s2bm_ard_3-2-1_50JLP_2021-02-10_final.stac-item
2021-02-17 11:46:50	ga_s2bm_ard_3-2-1_50HNJ_2021-02-17_final.stac-item
2021-03-18 12:14:12	ga_s2bm_ard_3-2-1_49KGQ_2021-03-18_final.stac-item
2021-04-18 11:47:16	ga_s2bm_ard_3-2-1_50HNG_2021-04-18_final
2021-04-28 11:46:33	ga_s2bm_ard_3-2-1_50HNK_2021-04-28_final.stac-item
2021-05-11 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2021-05-11_final.stac-item
2021-07-03 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2021-07-03_final.stac-item
2021-10-31 12:05:42	ga_s2bm_ard_3-2-1_50JKP_2021-10-31_final.stac-item
2021-11-23 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2021-11-23_final.stac-item
2022-02-01 12:14:07	ga_s2bm_ard_3-2-1_49KGQ_2022-02-01_final.stac-item
2022-02-12 11:47:00	ga_s2bm_ard_3-2-1_50HPH_2022-02-12_final.stac-item
2022-02-15 11:55:50	ga_s2bm_ard_3-2-1_50JLN_2022-02-15_final.stac-item
2022-02-18 12:05:20	ga_s2bm_ard_3-2-1_50JKQ_2022-02-18_final.stac-item
2022-02-28 12:04:27	ga_s2bm_ard_3-2-1_49KGP_2022-02-28_final.stac-item
2022-03-11 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2022-03-11_final.stac-item
2022-05-02 12:14:36	ga_s2bm_ard_3-2-1_49JGN_2022-05-02_final.stac-item
2022-05-12 12:13:46	ga_s2bm_ard_3-2-1_49KHR_2022-05-12_final.stac-item
2022-10-26 12:05:51	ga_s2bm_ard_3-2-1_50JLN_2022-10-26_final.stac-item
2022-11-05 12:04:26	ga_s2bm_ard_3-2-1_49KHP_2022-11-05_final.stac-item
2022-12-12 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2022-12-12_final.stac-item
2023-01-04 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2023-01-04_final.stac-item
2023-01-05 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2023-01-05_final.stac-item
2023-01-11 11:57:16	ga_s2bm_ard_3-2-1_50HMG_2023-01-11_final
2023-02-10 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2023-02-10_final.stac-item
2023-02-17 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2023-02-17_final
2023-03-05 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-03-05_final
2023-03-29 11:46:41	ga_s2bm_ard_3-2-1_50HNK_2023-03-29_final
2023-04-14 12:04:58	ga_s2bm_ard_3-2-1_50JKS_2023-04-14_final
2023-04-24 12:06:06	ga_s2bm_ard_3-2-1_50JLM_2023-04-24_final
2023-04-27 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2023-04-27_final
2023-05-04 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2023-05-04_final
2023-05-17 12:14:17	ga_s2bm_ard_3-2-1_49KGQ_2023-05-17_final
2023-06-27 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-06-27_final
2023-07-10 11:56:04	ga_s2bm_ard_3-2-1_50JKN_2023-07-10_final
2023-07-13 12:04:51	ga_s2bm_ard_3-2-1_49JGN_2023-07-13_final
2023-09-21 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2023-09-21_final
2023-09-24 12:15:14	ga_s2bm_ard_3-2-1_49JGL_2023-09-24_final
2023-10-11 12:04:44	ga_s2bm_ard_3-2-1_50JKT_2023-10-11_final
2023-10-25 11:46:38	ga_s2bm_ard_3-2-1_50HNK_2023-10-25_final
2023-12-11 11:37:18	ga_s2bm_ard_3-2-1_50HPG_2023-12-11_final
2023-12-17 11:55:56	ga_s2bm_ard_3-2-1_50JLN_2023-12-17_final
2024-03-22 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2024-03-22_final
2024-03-26 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2024-03-26_final
2024-04-15 11:55:47	ga_s2bm_ard_3-2-1_50JKP_2024-04-15_final
2024-05-15 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2024-05-15_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

All years