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
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KVU_2017-09-23_final.stac-item
2017-12-01 12:02:38	ga_s2bm_ard_3-2-1_50KMB_2017-12-01_final.stac-item
2018-01-14 11:40:41	ga_s2bm_ard_3-2-1_50JPS_2018-01-14_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_50JLM_2018-01-20_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_49KHP_2018-03-11_final.stac-item
2018-05-18 11:16:57	ga_s2bm_ard_3-2-1_52KBF_2018-05-18_final.stac-item
2018-05-19 10:54:54	ga_s2bm_ard_3-2-1_52JGL_2018-05-19_final.stac-item
2018-05-30 12:04:45	ga_s2bm_ard_3-2-1_50JLM_2018-05-30_final.stac-item
2018-07-30 11:31:34	ga_s2bm_ard_3-2-1_51KWV_2018-07-30_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_51JWN_2018-08-09_final.stac-item
2018-08-18 10:22:42	ga_s2bm_ard_3-2-1_53JRN_2018-08-18_final.stac-item
2018-12-05 10:53:38	ga_s2bm_ard_3-2-1_53KKQ_2018-12-05_final.stac-item
2018-12-11 11:13:01	ga_s2bm_ard_3-2-1_52KCC_2018-12-11_final.stac-item
2018-12-24 11:23:16	ga_s2bm_ard_3-2-1_52KBB_2018-12-24_final.stac-item
2018-12-27 11:32:11	ga_s2bm_ard_3-2-1_51KWB_2018-12-27_final.stac-item
2018-12-27 11:32:43	ga_s2bm_ard_3-2-1_51KVV_2018-12-27_final.stac-item
2019-02-19 11:13:15	ga_s2bm_ard_3-2-1_52KEB_2019-02-19_final.stac-item
2019-03-17 11:33:07	ga_s2bm_ard_3-2-1_51KXT_2019-03-17_final.stac-item
2019-04-14 10:51:45	ga_s2bm_ard_3-2-1_53LMC_2019-04-14_final.stac-item
2019-04-20 11:13:23	ga_s2bm_ard_3-2-1_52KEB_2019-04-20_final.stac-item
2019-04-29 11:46:04	ga_s2bm_ard_3-2-1_51JTG_2019-04-29_final.stac-item
2019-06-07 10:36:44	ga_s2bm_ard_3-2-1_53HNC_2019-06-07_final.stac-item
2019-07-02 11:24:10	ga_s2bm_ard_3-2-1_51KWQ_2019-07-02_final.stac-item
2019-07-24 12:05:46	ga_s2bm_ard_3-2-1_50JLP_2019-07-24_final.stac-item
2019-07-31 10:16:39	ga_s2bm_ard_3-2-1_54HUH_2019-07-31_final.stac-item
2019-09-02 12:05:41	ga_s2bm_ard_3-2-1_50JLP_2019-09-02_final.stac-item
2019-09-04 11:01:34	ga_s2bm_ard_3-2-1_52LGJ_2019-09-04_final.stac-item
2019-09-27 11:13:15	ga_s2bm_ard_3-2-1_52KEB_2019-09-27_final.stac-item
2019-11-01 10:25:06	ga_s2bm_ard_3-2-1_53JQJ_2019-11-01_final.stac-item
2019-11-23 11:00:42	ga_s2bm_ard_3-2-1_52LHM_2019-11-23_final.stac-item
2019-11-24 10:34:44	ga_s2bm_ard_3-2-1_53JQK_2019-11-24_final.stac-item
2019-12-06 11:13:42	ga_s2bm_ard_3-2-1_52KDV_2019-12-06_final.stac-item
2019-12-26 11:13:10	ga_s2bm_ard_3-2-1_52KEB_2019-12-26_final.stac-item
2020-01-25 11:15:35	ga_s2bm_ard_3-2-1_51JXH_2020-01-25_final.stac-item
2020-01-31 11:36:50	ga_s2bm_ard_3-2-1_51HUC_2020-01-31_final.stac-item
2020-04-21 11:04:51	ga_s2bm_ard_3-2-1_52JCR_2020-04-21_final.stac-item
2020-05-04 11:13:27	ga_s2bm_ard_3-2-1_52KEA_2020-05-04_final.stac-item
2020-05-11 11:03:44	ga_s2bm_ard_3-2-1_52KFV_2020-05-11_final.stac-item
2020-05-13 11:41:54	ga_s2bm_ard_3-2-1_51LWC_2020-05-13_final.stac-item
2020-07-02 11:42:11	ga_s2bm_ard_3-2-1_51KWB_2020-07-02_final.stac-item
2020-09-11 11:11:04	ga_s2bm_ard_3-2-1_52LFL_2020-09-11_final.stac-item
2020-11-03 11:25:06	ga_s2bm_ard_3-2-1_51JVL_2020-11-03_final.stac-item
2020-12-21 10:42:43	ga_s2bm_ard_3-2-1_53KQT_2020-12-21_final.stac-item
2021-01-12 11:23:34	ga_s2bm_ard_3-2-1_52KBA_2021-01-12_final.stac-item
2021-02-06 12:13:57	ga_s2bm_ard_3-2-1_49KGR_2021-02-06_final.stac-item
2021-02-13 10:24:11	ga_s2bm_ard_3-2-1_54JVS_2021-02-13_final.stac-item
2021-02-15 11:00:27	ga_s2bm_ard_3-2-1_53LKH_2021-02-15_final.stac-item
2021-03-19 10:06:37	ga_s2bm_ard_3-2-1_54HYG_2021-03-19_final.stac-item
2021-03-19 11:43:03	ga_s2bm_ard_3-2-1_50KRD_2021-03-19_final.stac-item
2021-03-27 11:00:43	ga_s2bm_ard_3-2-1_52LHM_2021-03-27_final.stac-item
2021-04-02 11:23:04	ga_s2bm_ard_3-2-1_52KBC_2021-04-02_final.stac-item
2021-06-24 09:57:23	ga_s2bm_ard_3-2-1_54HYD_2021-06-24_final.stac-item
2021-06-25 11:04:36	ga_s2bm_ard_3-2-1_52JGR_2021-06-25_final.stac-item
2021-10-10 10:53:50	ga_s2bm_ard_3-2-1_53KMP_2021-10-10_final.stac-item
2021-10-27 10:43:53	ga_s2bm_ard_3-2-1_53KNP_2021-10-27_final.stac-item
2021-11-11 11:36:46	ga_s2bm_ard_3-2-1_51HTD_2021-11-11_final.stac-item
2021-12-23 10:33:30	ga_s2bm_ard_3-2-1_53KQQ_2021-12-23_final.stac-item
2022-02-04 10:42:33	ga_s2bm_ard_3-2-1_53KNU_2022-02-04_final.stac-item
2022-02-12 11:40:51	ga_s2bm_ard_3-2-1_51LWG_2022-02-12_final
2022-04-03 11:44:42	ga_s2bm_ard_3-2-1_50JRS_2022-04-03_final.stac-item
2022-04-29 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2022-04-29_final.stac-item
2022-05-20 11:32:43	ga_s2bm_ard_3-2-1_51KWV_2022-05-20_final.stac-item
2022-06-02 10:06:53	ga_s2bm_ard_3-2-1_54HXF_2022-06-02_final.stac-item
2022-06-07 10:51:23	ga_s2bm_ard_3-2-1_53LND_2022-06-07_final.stac-item
2022-06-12 10:05:35	ga_s2bm_ard_3-2-1_54JYL_2022-06-12_final.stac-item
2022-06-18 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-06-18_final.stac-item
2022-07-20 11:03:18	ga_s2bm_ard_3-2-1_52KGB_2022-07-20_final.stac-item
2022-07-27 10:56:05	ga_s2bm_ard_3-2-1_52JFL_2022-07-27_final.stac-item
2022-08-18 11:33:29	ga_s2bm_ard_3-2-1_51KWS_2022-08-18_final.stac-item
2022-10-19 10:35:14	ga_s2bm_ard_3-2-1_53JMJ_2022-10-19_final.stac-item
2022-11-25 10:26:46	ga_s2bm_ard_3-2-1_53HQB_2022-11-25_final.stac-item
2022-12-19 11:43:02	ga_s2bm_ard_3-2-1_51KTU_2022-12-19_final.stac-item
2023-01-01 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2023-01-01_final.stac-item
2023-01-21 11:56:52	ga_s2bm_ard_3-2-1_50HLJ_2023-01-21_final.stac-item
2023-02-01 11:22:53	ga_s2bm_ard_3-2-1_51KYU_2023-02-01_final.stac-item
2023-02-02 10:51:07	ga_s2bm_ard_3-2-1_53LME_2023-02-02_final
2023-02-21 11:24:01	ga_s2bm_ard_3-2-1_51KWQ_2023-02-21_final
2023-02-26 10:32:52	ga_s2bm_ard_3-2-1_53KQT_2023-02-26_final
2023-02-27 11:42:57	ga_s2bm_ard_3-2-1_51KVU_2023-02-27_final
2023-04-28 11:43:20	ga_s2bm_ard_3-2-1_51KTT_2023-04-28_final
2023-05-27 10:36:55	ga_s2bm_ard_3-2-1_53HNB_2023-05-27_final
2023-07-27 11:42:19	ga_s2bm_ard_3-2-1_51KVB_2023-07-27_final
2023-08-04 11:03:21	ga_s2bm_ard_3-2-1_52KFB_2023-08-04_final
2023-08-10 11:22:57	ga_s2bm_ard_3-2-1_52KBD_2023-08-10_final
2023-09-07 10:44:32	ga_s2bm_ard_3-2-1_53JPL_2023-09-07_final
2023-09-25 10:06:57	ga_s2bm_ard_3-2-1_54HXF_2023-09-25_final
2023-09-28 11:56:21	ga_s2bm_ard_3-2-1_50JNL_2023-09-28_final
2023-10-18 11:56:32	ga_s2bm_ard_3-2-1_50HNK_2023-10-18_final
2023-10-22 11:34:19	ga_s2bm_ard_3-2-1_51KUP_2023-10-22_final
2023-11-15 11:13:42	ga_s2bm_ard_3-2-1_52KEV_2023-11-15_final
2023-11-22 11:00:26	ga_s2bm_ard_3-2-1_52LHN_2023-11-22_final
2024-01-02 10:36:47	ga_s2bm_ard_3-2-1_53HPB_2024-01-02_final
2024-01-03 11:42:10	ga_s2bm_ard_3-2-1_51KWB_2024-01-03_final
2024-01-22 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2024-01-22_final
2024-02-05 10:15:13	ga_s2bm_ard_3-2-1_54JVN_2024-02-05_final
2024-02-08 12:04:39	ga_s2bm_ard_3-2-1_50JLT_2024-02-08_final
2024-03-11 11:04:03	ga_s2bm_ard_3-2-1_52KEU_2024-03-11_final
2024-04-18 10:24:05	ga_s2bm_ard_3-2-1_53JRN_2024-04-18_final
2024-04-30 11:03:34	ga_s2bm_ard_3-2-1_52KEA_2024-04-30_final
2024-05-02 11:40:57	ga_s2bm_ard_3-2-1_51LWG_2024-05-02_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