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
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50JPL_2017-10-06_final.stac-item
2017-12-05 11:40:37	ga_s2bm_ard_3-2-1_50KPU_2017-12-05_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_51KWA_2017-12-22_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50HPK_2017-12-25_final.stac-item
2018-01-01 11:30:30	ga_s2bm_ard_3-2-1_51JTJ_2018-01-01_final.stac-item
2018-01-02 10:57:06	ga_s2bm_ard_3-2-1_53KKU_2018-01-02_final.stac-item
2018-01-03 12:13:12	ga_s2bm_ard_3-2-1_49KGP_2018-01-03_final.stac-item
2018-02-14 11:07:05	ga_s2bm_ard_3-2-1_51JZM_2018-02-14_final.stac-item
2018-03-06 11:07:03	ga_s2bm_ard_3-2-1_52LFL_2018-03-06_final.stac-item
2018-07-27 11:23:26	ga_s2bm_ard_3-2-1_51HXD_2018-07-27_final.stac-item
2018-08-13 11:11:16	ga_s2bm_ard_3-2-1_52KBA_2018-08-13_final.stac-item
2018-08-28 12:04:53	ga_s2bm_ard_3-2-1_50JLM_2018-08-28_final.stac-item
2018-09-12 11:07:03	ga_s2bm_ard_3-2-1_52KDB_2018-09-12_final.stac-item
2018-10-09 11:00:38	ga_s2bm_ard_3-2-1_52KDV_2018-10-09_final.stac-item
2018-10-18 11:32:25	ga_s2bm_ard_3-2-1_51KWP_2018-10-18_final.stac-item
2018-10-27 10:23:51	ga_s2bm_ard_3-2-1_53JPG_2018-10-27_final.stac-item
2018-11-10 11:42:43	ga_s2bm_ard_3-2-1_51KUV_2018-11-10_final.stac-item
2018-12-26 12:05:37	ga_s2bm_ard_3-2-1_50JKP_2018-12-26_final.stac-item
2019-01-06 11:33:46	ga_s2bm_ard_3-2-1_51KUR_2019-01-06_final.stac-item
2019-03-09 10:36:48	ga_s2bm_ard_3-2-1_53HNB_2019-03-09_final.stac-item
2019-03-24 11:25:04	ga_s2bm_ard_3-2-1_51JVL_2019-03-24_final.stac-item
2019-04-05 10:26:35	ga_s2bm_ard_3-2-1_53HQC_2019-04-05_final.stac-item
2019-04-19 11:46:29	ga_s2bm_ard_3-2-1_50JNL_2019-04-19_final.stac-item
2019-04-20 11:13:28	ga_s2bm_ard_3-2-1_52KCB_2019-04-20_final.stac-item
2019-04-27 11:04:25	ga_s2bm_ard_3-2-1_52JET_2019-04-27_final.stac-item
2019-05-07 11:03:25	ga_s2bm_ard_3-2-1_52KFB_2019-05-07_final.stac-item
2019-06-26 11:02:48	ga_s2bm_ard_3-2-1_52KHD_2019-06-26_final.stac-item
2019-07-06 11:03:14	ga_s2bm_ard_3-2-1_52KEC_2019-07-06_final.stac-item
2019-07-22 11:22:32	ga_s2bm_ard_3-2-1_51KZA_2019-07-22_final.stac-item
2019-09-21 10:52:59	ga_s2bm_ard_3-2-1_52KHC_2019-09-21_final.stac-item
2019-09-30 11:22:23	ga_s2bm_ard_3-2-1_52KBF_2019-09-30_final.stac-item
2019-10-26 11:42:43	ga_s2bm_ard_3-2-1_51KVV_2019-10-26_final.stac-item
2019-11-02 11:32:20	ga_s2bm_ard_3-2-1_51KVB_2019-11-02_final.stac-item
2019-11-23 11:02:41	ga_s2bm_ard_3-2-1_52KGD_2019-11-23_final.stac-item
2019-12-31 12:04:05	ga_s2bm_ard_3-2-1_50KLV_2019-12-31_final.stac-item
2020-01-25 11:11:52	ga_s2bm_ard_3-2-1_52KFG_2020-01-25_final.stac-item
2020-02-14 11:16:36	ga_s2bm_ard_3-2-1_51HXD_2020-02-14_final.stac-item
2020-02-26 10:17:02	ga_s2bm_ard_3-2-1_53HQA_2020-02-26_final.stac-item
2020-03-09 10:55:43	ga_s2bm_ard_3-2-1_52JFM_2020-03-09_final.stac-item
2020-03-12 11:04:16	ga_s2bm_ard_3-2-1_52JET_2020-03-12_final.stac-item
2020-04-14 11:13:47	ga_s2bm_ard_3-2-1_52KCV_2020-04-14_final.stac-item
2020-04-20 11:34:44	ga_s2bm_ard_3-2-1_51JTM_2020-04-20_final.stac-item
2020-05-07 11:24:02	ga_s2bm_ard_3-2-1_52KBU_2020-05-07_final.stac-item
2020-05-23 11:44:02	ga_s2bm_ard_3-2-1_50KRV_2020-05-23_final.stac-item
2020-07-23 11:10:27	ga_s2bm_ard_3-2-1_52LHN_2020-07-23_final.stac-item
2020-08-16 10:53:50	ga_s2bm_ard_3-2-1_52KGV_2020-08-16_final.stac-item
2020-09-07 11:33:37	ga_s2bm_ard_3-2-1_51KUS_2020-09-07_final.stac-item
2020-09-14 11:27:00	ga_s2bm_ard_3-2-1_51HVC_2020-09-14_final.stac-item
2020-11-02 11:56:43	ga_s2bm_ard_3-2-1_50HLK_2020-11-02_final.stac-item
2020-12-11 10:44:14	ga_s2bm_ard_3-2-1_53JPM_2020-12-11_final.stac-item
2020-12-20 11:14:37	ga_s2bm_ard_3-2-1_51JYM_2020-12-20_final.stac-item
2021-02-15 11:00:47	ga_s2bm_ard_3-2-1_52LGM_2021-02-15_final.stac-item
2021-04-08 11:43:08	ga_s2bm_ard_3-2-1_51KVT_2021-04-08_final.stac-item
2021-08-30 11:22:58	ga_s2bm_ard_3-2-1_51KXU_2021-08-30_final.stac-item
2021-09-23 11:03:43	ga_s2bm_ard_3-2-1_52KFV_2021-09-23_final.stac-item
2021-09-29 11:23:49	ga_s2bm_ard_3-2-1_51KZQ_2021-09-29_final.stac-item
2021-10-24 10:36:48	ga_s2bm_ard_3-2-1_53HPB_2021-10-24_final.stac-item
2021-11-07 11:57:06	ga_s2bm_ard_3-2-1_50HMH_2021-11-07_final.stac-item
2021-12-21 11:32:57	ga_s2bm_ard_3-2-1_51KYT_2021-12-21_final.stac-item
2022-01-09 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2022-01-09_final.stac-item
2022-02-03 11:12:08	ga_s2bm_ard_3-2-1_52KFF_2022-02-03_final.stac-item
2022-03-11 11:33:46	ga_s2bm_ard_3-2-1_51KUR_2022-03-11_final.stac-item
2022-05-09 10:26:29	ga_s2bm_ard_3-2-1_53HQC_2022-05-09_final.stac-item
2022-05-10 11:34:29	ga_s2bm_ard_3-2-1_51JUN_2022-05-10_final.stac-item
2022-05-23 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2022-05-23_final.stac-item
2022-05-29 12:05:55	ga_s2bm_ard_3-2-1_50JKN_2022-05-29_final.stac-item
2022-08-19 11:03:43	ga_s2bm_ard_3-2-1_52KGV_2022-08-19_final.stac-item
2022-09-02 10:46:07	ga_s2bm_ard_3-2-1_53HME_2022-09-02_final.stac-item
2022-09-25 10:55:03	ga_s2bm_ard_3-2-1_52JFQ_2022-09-25_final.stac-item
2022-10-25 10:55:48	ga_s2bm_ard_3-2-1_52JEM_2022-10-25_final.stac-item
2022-10-29 12:14:59	ga_s2bm_ard_3-2-1_49JFM_2022-10-29_final.stac-item
2022-12-16 11:32:38	ga_s2bm_ard_3-2-1_51KXV_2022-12-16_final.stac-item
2022-12-16 11:32:52	ga_s2bm_ard_3-2-1_51KYU_2022-12-16_final.stac-item
2023-01-06 11:00:46	ga_s2bm_ard_3-2-1_52LGM_2023-01-06_final.stac-item
2023-02-08 11:14:07	ga_s2bm_ard_3-2-1_51KZP_2023-02-08_final
2023-02-18 11:10:56	ga_s2bm_ard_3-2-1_52LGL_2023-02-18_final
2023-03-03 11:23:01	ga_s2bm_ard_3-2-1_51KXU_2023-03-03_final
2023-04-09 11:14:11	ga_s2bm_ard_3-2-1_52KBU_2023-04-09_final
2023-05-04 12:04:29	ga_s2bm_ard_3-2-1_50KKU_2023-05-04_final
2023-05-08 11:43:06	ga_s2bm_ard_3-2-1_51KTU_2023-05-08_final
2023-05-20 10:45:48	ga_s2bm_ard_3-2-1_53JKG_2023-05-20_final
2023-05-28 11:41:02	ga_s2bm_ard_3-2-1_51LWG_2023-05-28_final
2023-06-25 11:04:47	ga_s2bm_ard_3-2-1_52JFR_2023-06-25_final
2023-07-16 10:36:33	ga_s2bm_ard_3-2-1_53HLD_2023-07-16_final
2023-09-06 11:12:25	ga_s2bm_ard_3-2-1_52KDF_2023-09-06_final
2023-09-06 11:14:10	ga_s2bm_ard_3-2-1_52KCU_2023-09-06_final
2023-09-18 11:52:23	ga_s2bm_ard_3-2-1_50KQG_2023-09-18_final
2023-10-01 12:03:46	ga_s2bm_ard_3-2-1_50KKB_2023-10-01_final
2023-10-17 10:46:12	ga_s2bm_ard_3-2-1_53HLE_2023-10-17_final
2023-11-08 11:23:52	ga_s2bm_ard_3-2-1_51KZQ_2023-11-08_final
2023-11-15 11:13:25	ga_s2bm_ard_3-2-1_52KBB_2023-11-15_final
2023-11-18 11:23:19	ga_s2bm_ard_3-2-1_52KBB_2023-11-18_final
2023-12-03 10:33:57	ga_s2bm_ard_3-2-1_53JRN_2023-12-03_final
2023-12-07 11:56:51	ga_s2bm_ard_3-2-1_50HLJ_2023-12-07_final
2023-12-12 11:05:55	ga_s2bm_ard_3-2-1_52JBM_2023-12-12_final
2023-12-25 11:13:41	ga_s2bm_ard_3-2-1_51KZR_2023-12-25_final
2024-02-23 11:11:05	ga_s2bm_ard_3-2-1_52LEL_2024-02-23_final
2024-02-27 10:52:19	ga_s2bm_ard_3-2-1_52KHF_2024-02-27_final
2024-03-04 11:13:11	ga_s2bm_ard_3-2-1_52KEB_2024-03-04_final
2024-03-28 10:55:10	ga_s2bm_ard_3-2-1_53JKJ_2024-03-28_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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