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
2017-08-07 11:45:07	ga_s2bm_ard_3-2-1_50HPJ_2017-08-07_final.stac-item
2017-08-26 12:13:17	ga_s2bm_ard_3-2-1_50KKB_2017-08-26_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JLP_2017-12-18_final.stac-item
2018-04-10 12:02:47	ga_s2bm_ard_3-2-1_49JHN_2018-04-10_final.stac-item
2018-06-30 11:33:25	ga_s2bm_ard_3-2-1_50HPJ_2018-06-30_final.stac-item
2018-07-03 11:44:57	ga_s2bm_ard_3-2-1_50JQL_2018-07-03_final.stac-item
2018-07-19 12:02:47	ga_s2bm_ard_3-2-1_50KNC_2018-07-19_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HPH_2018-08-09_final.stac-item
2018-08-22 11:44:50	ga_s2bm_ard_3-2-1_50HPJ_2018-08-22_final.stac-item
2018-08-28 12:04:53	ga_s2bm_ard_3-2-1_49JGJ_2018-08-28_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50HQJ_2018-09-11_final.stac-item
2019-01-25 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2019-01-25_final.stac-item
2019-02-28 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2019-02-28_final.stac-item
2019-04-15 12:05:43	ga_s2bm_ard_3-2-1_50JLP_2019-04-15_final.stac-item
2019-04-16 11:37:08	ga_s2bm_ard_3-2-1_50HQH_2019-04-16_final.stac-item
2019-04-29 11:45:40	ga_s2bm_ard_3-2-1_50JQP_2019-04-29_final.stac-item
2019-05-25 12:05:23	ga_s2bm_ard_3-2-1_49JGL_2019-05-25_final.stac-item
2019-06-08 11:46:45	ga_s2bm_ard_3-2-1_50HNK_2019-06-08_final.stac-item
2019-06-11 11:56:25	ga_s2bm_ard_3-2-1_50JNL_2019-06-11_final.stac-item
2019-07-04 12:05:38	ga_s2bm_ard_3-2-1_49JGK_2019-07-04_final.stac-item
2019-10-06 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2019-10-06_final.stac-item
2019-11-11 12:03:19	ga_s2bm_ard_3-2-1_50KNC_2019-11-11_final.stac-item
2020-01-21 11:37:00	ga_s2bm_ard_3-2-1_50HPH_2020-01-21_final.stac-item
2020-01-24 11:43:08	ga_s2bm_ard_3-2-1_50KQC_2020-01-24_final.stac-item
2020-01-30 12:04:53	ga_s2bm_ard_3-2-1_49JGM_2020-01-30_final.stac-item
2020-02-09 12:05:35	ga_s2bm_ard_3-2-1_50JKP_2020-02-09_final.stac-item
2020-04-23 11:44:05	ga_s2bm_ard_3-2-1_50KPV_2020-04-23_final.stac-item
2020-04-23 11:46:57	ga_s2bm_ard_3-2-1_50HPH_2020-04-23_final.stac-item
2020-05-26 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2020-05-26_final.stac-item
2020-05-29 12:05:42	ga_s2bm_ard_3-2-1_50JKP_2020-05-29_final.stac-item
2020-06-01 12:14:43	ga_s2bm_ard_3-2-1_49JGN_2020-06-01_final.stac-item
2020-07-15 11:55:48	ga_s2bm_ard_3-2-1_50JKP_2020-07-15_final.stac-item
2020-07-18 12:03:35	ga_s2bm_ard_3-2-1_50KNB_2020-07-18_final.stac-item
2020-08-11 11:45:45	ga_s2bm_ard_3-2-1_50JQN_2020-08-11_final.stac-item
2020-10-09 12:13:55	ga_s2bm_ard_3-2-1_50KKA_2020-10-09_final.stac-item
2020-12-19 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2020-12-19_final.stac-item
2021-01-14 12:03:44	ga_s2bm_ard_3-2-1_50KKB_2021-01-14_final.stac-item
2021-02-10 11:53:20	ga_s2bm_ard_3-2-1_50KPC_2021-02-10_final.stac-item
2021-02-17 11:46:28	ga_s2bm_ard_3-2-1_50HQK_2021-02-17_final.stac-item
2021-04-08 11:46:04	ga_s2bm_ard_3-2-1_50JPM_2021-04-08_final.stac-item
2021-07-14 11:36:50	ga_s2bm_ard_3-2-1_50HQJ_2021-07-14_final.stac-item
2021-07-17 11:47:26	ga_s2bm_ard_3-2-1_50HMG_2021-07-17_final
2021-07-30 11:56:24	ga_s2bm_ard_3-2-1_50JML_2021-07-30_final.stac-item
2021-08-16 11:46:34	ga_s2bm_ard_3-2-1_50HPK_2021-08-16_final.stac-item
2021-08-19 11:56:13	ga_s2bm_ard_3-2-1_50JKM_2021-08-19_final.stac-item
2021-08-19 11:56:25	ga_s2bm_ard_3-2-1_50JLL_2021-08-19_final.stac-item
2021-09-04 12:13:55	ga_s2bm_ard_3-2-1_49KGR_2021-09-04_final.stac-item
2021-09-11 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2021-09-11_final.stac-item
2021-10-08 11:56:12	ga_s2bm_ard_3-2-1_50JLM_2021-10-08_final.stac-item
2021-11-04 11:43:19	ga_s2bm_ard_3-2-1_50KRC_2021-11-04_final.stac-item
2021-12-11 11:36:32	ga_s2bm_ard_3-2-1_50HPK_2021-12-11_final.stac-item
2021-12-17 11:52:13	ga_s2bm_ard_3-2-1_50KQG_2021-12-17_final
2022-01-16 11:52:30	ga_s2bm_ard_3-2-1_50KQF_2022-01-16_final
2022-02-08 12:03:18	ga_s2bm_ard_3-2-1_50KMC_2022-02-08_final.stac-item
2022-03-04 11:46:34	ga_s2bm_ard_3-2-1_50HNK_2022-03-04_final.stac-item
2022-03-07 11:56:23	ga_s2bm_ard_3-2-1_50JLL_2022-03-07_final.stac-item
2022-03-27 11:52:31	ga_s2bm_ard_3-2-1_50KQF_2022-03-27_final
2022-03-27 11:54:45	ga_s2bm_ard_3-2-1_50JPS_2022-03-27_final.stac-item
2022-04-03 11:46:52	ga_s2bm_ard_3-2-1_50HMJ_2022-04-03_final.stac-item
2022-04-09 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2022-04-09_final.stac-item
2022-04-16 11:55:52	ga_s2bm_ard_3-2-1_50JLN_2022-04-16_final.stac-item
2022-04-26 11:57:03	ga_s2bm_ard_3-2-1_50HLH_2022-04-26_final.stac-item
2022-05-23 11:43:18	ga_s2bm_ard_3-2-1_50KRC_2022-05-23_final.stac-item
2022-06-15 11:53:14	ga_s2bm_ard_3-2-1_50KRC_2022-06-15_final.stac-item
2022-06-15 11:56:29	ga_s2bm_ard_3-2-1_50JLL_2022-06-15_final.stac-item
2022-08-04 11:53:22	ga_s2bm_ard_3-2-1_50KQC_2022-08-04_final.stac-item
2022-09-16 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2022-09-16_final.stac-item
2022-11-02 11:53:09	ga_s2bm_ard_3-2-1_50KRC_2022-11-02_final.stac-item
2022-11-15 12:05:43	ga_s2bm_ard_3-2-1_49JGJ_2022-11-15_final.stac-item
2022-11-19 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2022-11-19_final.stac-item
2022-12-29 11:43:21	ga_s2bm_ard_3-2-1_50KQC_2022-12-29_final.stac-item
2023-01-28 11:43:19	ga_s2bm_ard_3-2-1_50KQC_2023-01-28_final.stac-item
2023-02-13 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2023-02-13_final
2023-03-05 12:04:45	ga_s2bm_ard_3-2-1_50JKT_2023-03-05_final
2023-04-14 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2023-04-14_final
2023-05-24 12:05:05	ga_s2bm_ard_3-2-1_49JGM_2023-05-24_final
2023-06-03 12:05:59	ga_s2bm_ard_3-2-1_50JKN_2023-06-03_final
2023-07-17 11:43:27	ga_s2bm_ard_3-2-1_50KQC_2023-07-17_final
2023-08-06 11:46:48	ga_s2bm_ard_3-2-1_50HQJ_2023-08-06_final
2023-08-12 12:04:05	ga_s2bm_ard_3-2-1_49KHR_2023-08-12_final
2023-08-16 11:46:46	ga_s2bm_ard_3-2-1_50HMK_2023-08-16_final
2023-09-21 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2023-09-21_final
2023-10-02 11:37:04	ga_s2bm_ard_3-2-1_50HQH_2023-10-02_final
2023-10-21 12:03:46	ga_s2bm_ard_3-2-1_50KKB_2023-10-21_final
2023-11-07 11:53:33	ga_s2bm_ard_3-2-1_50KMC_2023-11-07_final
2023-12-27 11:56:19	ga_s2bm_ard_3-2-1_50JNL_2023-12-27_final
2023-12-30 12:05:56	ga_s2bm_ard_3-2-1_50JKN_2023-12-30_final
2024-01-02 12:13:55	ga_s2bm_ard_3-2-1_50KKA_2024-01-02_final
2024-01-19 12:03:22	ga_s2bm_ard_3-2-1_50KMC_2024-01-19_final
2024-01-23 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2024-01-23_final
2024-01-26 11:55:45	ga_s2bm_ard_3-2-1_50JKP_2024-01-26_final
2024-01-29 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2024-01-29_final
2024-02-05 11:55:44	ga_s2bm_ard_3-2-1_50JLP_2024-02-05_final
2024-02-05 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2024-02-05_final
2024-02-15 11:56:31	ga_s2bm_ard_3-2-1_50HNK_2024-02-15_final
2024-02-28 12:03:43	ga_s2bm_ard_3-2-1_50KKB_2024-02-28_final
2024-02-28 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2024-02-28_final
2024-03-10 11:36:58	ga_s2bm_ard_3-2-1_50HQH_2024-03-10_final
2024-04-12 11:47:25	ga_s2bm_ard_3-2-1_50HMG_2024-04-12_final
2024-05-08 12:04:00	ga_s2bm_ard_3-2-1_49KHR_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