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
2017-08-27 11:40:44	ga_s2bm_ard_3-2-1_50JNQ_2017-08-27_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JKN_2017-11-08_final.stac-item
2017-11-15 11:46:01	ga_s2bm_ard_3-2-1_50HNJ_2017-11-15_final.stac-item
2018-01-14 11:40:41	ga_s2bm_ard_3-2-1_50JQT_2018-01-14_final.stac-item
2018-02-03 11:46:07	ga_s2bm_ard_3-2-1_50HPK_2018-02-03_final.stac-item
2018-02-19 12:02:42	ga_s2bm_ard_3-2-1_50KLC_2018-02-19_final.stac-item
2018-02-23 11:44:25	ga_s2bm_ard_3-2-1_50JMM_2018-02-23_final.stac-item
2018-03-08 11:51:37	ga_s2bm_ard_3-2-1_50HLH_2018-03-08_final.stac-item
2018-03-25 11:44:34	ga_s2bm_ard_3-2-1_50JQR_2018-03-25_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_50KLU_2018-07-09_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HQK_2018-07-13_final.stac-item
2018-11-16 12:04:10	ga_s2bm_ard_3-2-1_50KKV_2018-11-16_final.stac-item
2018-11-16 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2018-11-16_final.stac-item
2018-12-26 12:04:14	ga_s2bm_ard_3-2-1_49KGQ_2018-12-26_final.stac-item
2019-06-04 12:04:47	ga_s2bm_ard_3-2-1_50JLT_2019-06-04_final.stac-item
2019-06-14 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2019-06-14_final.stac-item
2019-06-24 12:04:21	ga_s2bm_ard_3-2-1_50KKV_2019-06-24_final.stac-item
2019-08-23 12:04:19	ga_s2bm_ard_3-2-1_49KHQ_2019-08-23_final.stac-item
2019-09-15 12:15:00	ga_s2bm_ard_3-2-1_49JFM_2019-09-15_final.stac-item
2019-09-16 11:46:51	ga_s2bm_ard_3-2-1_50HNJ_2019-09-16_final.stac-item
2019-09-16 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-09-16_final.stac-item
2019-10-19 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2019-10-19_final.stac-item
2019-12-21 12:05:39	ga_s2bm_ard_3-2-1_49JGJ_2019-12-21_final.stac-item
2020-02-02 12:14:49	ga_s2bm_ard_3-2-1_49JGM_2020-02-02_final.stac-item
2020-02-20 11:36:34	ga_s2bm_ard_3-2-1_50HPK_2020-02-20_final.stac-item
2020-04-02 12:13:51	ga_s2bm_ard_3-2-1_50KKA_2020-04-02_final.stac-item
2020-04-06 11:56:52	ga_s2bm_ard_3-2-1_50HLJ_2020-04-06_final.stac-item
2020-04-19 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2020-04-19_final.stac-item
2020-04-19 12:04:52	ga_s2bm_ard_3-2-1_49JHM_2020-04-19_final.stac-item
2020-04-29 12:04:09	ga_s2bm_ard_3-2-1_50KKV_2020-04-29_final.stac-item
2020-06-28 12:04:16	ga_s2bm_ard_3-2-1_50KKV_2020-06-28_final.stac-item
2020-08-01 11:47:09	ga_s2bm_ard_3-2-1_50HNH_2020-08-01_final.stac-item
2020-08-17 12:04:51	ga_s2bm_ard_3-2-1_50JKS_2020-08-17_final.stac-item
2020-08-27 12:03:44	ga_s2bm_ard_3-2-1_50KLB_2020-08-27_final.stac-item
2020-08-31 11:46:33	ga_s2bm_ard_3-2-1_50HQK_2020-08-31_final.stac-item
2020-09-16 12:04:49	ga_s2bm_ard_3-2-1_50JKS_2020-09-16_final.stac-item
2020-09-26 12:05:46	ga_s2bm_ard_3-2-1_49JGJ_2020-09-26_final.stac-item
2020-11-02 11:55:44	ga_s2bm_ard_3-2-1_50JLP_2020-11-02_final.stac-item
2020-11-05 12:04:45	ga_s2bm_ard_3-2-1_50JKT_2020-11-05_final.stac-item
2020-12-12 11:56:19	ga_s2bm_ard_3-2-1_50JML_2020-12-12_final.stac-item
2020-12-19 11:46:22	ga_s2bm_ard_3-2-1_50JPL_2020-12-19_final.stac-item
2021-02-07 11:45:04	ga_s2bm_ard_3-2-1_50JQR_2021-02-07_final.stac-item
2021-02-17 11:45:48	ga_s2bm_ard_3-2-1_50JPN_2021-02-17_final.stac-item
2021-02-17 11:46:13	ga_s2bm_ard_3-2-1_50JQL_2021-02-17_final.stac-item
2021-02-17 11:46:42	ga_s2bm_ard_3-2-1_50HQJ_2021-02-17_final.stac-item
2021-02-26 12:13:53	ga_s2bm_ard_3-2-1_49KHR_2021-02-26_final.stac-item
2021-03-06 11:36:04	ga_s2bm_ard_3-2-1_50JQM_2021-03-06_final.stac-item
2021-04-25 11:36:57	ga_s2bm_ard_3-2-1_50HQH_2021-04-25_final.stac-item
2021-05-01 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2021-05-01_final.stac-item
2021-07-07 11:46:02	ga_s2bm_ard_3-2-1_50JQM_2021-07-07_final.stac-item
2021-07-14 11:37:05	ga_s2bm_ard_3-2-1_50HQH_2021-07-14_final.stac-item
2021-07-24 11:36:36	ga_s2bm_ard_3-2-1_50HQK_2021-07-24_final.stac-item
2021-08-12 12:03:59	ga_s2bm_ard_3-2-1_50KKA_2021-08-12_final.stac-item
2021-08-19 11:56:10	ga_s2bm_ard_3-2-1_50JLM_2021-08-19_final.stac-item
2021-09-11 12:05:22	ga_s2bm_ard_3-2-1_50JKQ_2021-09-11_final.stac-item
2021-10-14 12:13:59	ga_s2bm_ard_3-2-1_49KGR_2021-10-14_final.stac-item
2021-10-31 12:03:57	ga_s2bm_ard_3-2-1_50KLA_2021-10-31_final.stac-item
2021-11-03 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2021-11-03_final.stac-item
2021-12-04 11:47:19	ga_s2bm_ard_3-2-1_50HMG_2021-12-04_final
2021-12-10 12:05:24	ga_s2bm_ard_3-2-1_49JGK_2021-12-10_final.stac-item
2021-12-17 11:57:03	ga_s2bm_ard_3-2-1_50HLH_2021-12-17_final.stac-item
2021-12-20 12:05:24	ga_s2bm_ard_3-2-1_49JGK_2021-12-20_final.stac-item
2021-12-23 12:13:49	ga_s2bm_ard_3-2-1_50KKA_2021-12-23_final.stac-item
2022-01-16 11:56:14	ga_s2bm_ard_3-2-1_50JNL_2022-01-16_final.stac-item
2022-01-19 12:04:09	ga_s2bm_ard_3-2-1_49KHQ_2022-01-19_final.stac-item
2022-01-29 12:05:31	ga_s2bm_ard_3-2-1_50JLP_2022-01-29_final.stac-item
2022-02-02 11:46:37	ga_s2bm_ard_3-2-1_50HQJ_2022-02-02_final.stac-item
2022-02-12 11:45:19	ga_s2bm_ard_3-2-1_50JNQ_2022-02-12_final.stac-item
2022-02-18 12:04:07	ga_s2bm_ard_3-2-1_50KKV_2022-02-18_final.stac-item
2022-06-12 11:46:46	ga_s2bm_ard_3-2-1_50HQJ_2022-06-12_final.stac-item
2022-07-08 12:04:44	ga_s2bm_ard_3-2-1_50JKT_2022-07-08_final.stac-item
2022-08-11 11:46:19	ga_s2bm_ard_3-2-1_50JQL_2022-08-11_final.stac-item
2022-08-27 12:05:52	ga_s2bm_ard_3-2-1_50JLN_2022-08-27_final.stac-item
2022-09-07 11:35:52	ga_s2bm_ard_3-2-1_50JQN_2022-09-07_final.stac-item
2022-09-10 11:46:39	ga_s2bm_ard_3-2-1_50HNK_2022-09-10_final.stac-item
2022-09-26 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2022-09-26_final.stac-item
2022-10-27 11:36:47	ga_s2bm_ard_3-2-1_50HQJ_2022-10-27_final.stac-item
2022-11-09 11:46:00	ga_s2bm_ard_3-2-1_50JQM_2022-11-09_final.stac-item
2022-11-22 11:56:11	ga_s2bm_ard_3-2-1_50JLM_2022-11-22_final.stac-item
2023-02-07 11:46:17	ga_s2bm_ard_3-2-1_50JPL_2023-02-07_final
2023-02-07 11:46:50	ga_s2bm_ard_3-2-1_50HNJ_2023-02-07_final
2023-02-17 11:46:21	ga_s2bm_ard_3-2-1_50JNL_2023-02-17_final
2023-04-11 11:56:06	ga_s2bm_ard_3-2-1_50JNM_2023-04-11_final
2023-04-11 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2023-04-11_final
2023-05-27 12:14:31	ga_s2bm_ard_3-2-1_49KGP_2023-05-27_final
2023-07-06 12:14:32	ga_s2bm_ard_3-2-1_49KGP_2023-07-06_final
2023-07-20 11:56:28	ga_s2bm_ard_3-2-1_50JML_2023-07-20_final
2023-08-02 12:04:18	ga_s2bm_ard_3-2-1_50KKV_2023-08-02_final
2023-08-06 11:47:07	ga_s2bm_ard_3-2-1_50HPH_2023-08-06_final
2023-09-02 11:37:22	ga_s2bm_ard_3-2-1_50HQG_2023-09-02_final
2023-09-08 11:56:04	ga_s2bm_ard_3-2-1_50JKN_2023-09-08_final
2023-09-28 11:56:39	ga_s2bm_ard_3-2-1_50HMK_2023-09-28_final
2023-11-10 12:05:53	ga_s2bm_ard_3-2-1_50JLN_2023-11-10_final
2023-11-14 11:46:38	ga_s2bm_ard_3-2-1_50HNK_2023-11-14_final
2023-11-24 11:45:13	ga_s2bm_ard_3-2-1_50JQQ_2023-11-24_final
2023-11-30 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2023-11-30_final
2023-12-04 11:46:52	ga_s2bm_ard_3-2-1_50HMJ_2023-12-04_final
2023-12-07 11:56:15	ga_s2bm_ard_3-2-1_50JNL_2023-12-07_final
2024-03-29 12:04:34	ga_s2bm_ard_3-2-1_49KGP_2024-03-29_final
2024-03-30 11:37:02	ga_s2bm_ard_3-2-1_50HQH_2024-03-30_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

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