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
2017-08-03 10:23:06	ga_s2bm_ard_3-2-1_53HNB_2017-08-03_final.stac-item
2017-10-28 10:37:14	ga_s2bm_ard_3-2-1_53KPS_2017-10-28_final.stac-item
2017-10-30 11:20:19	ga_s2bm_ard_3-2-1_51JWG_2017-10-30_final.stac-item
2017-11-11 10:23:14	ga_s2bm_ard_3-2-1_53HNB_2017-11-11_final.stac-item
2017-12-02 11:27:18	ga_s2bm_ard_3-2-1_51KWT_2017-12-02_final.stac-item
2017-12-29 11:16:48	ga_s2bm_ard_3-2-1_51KYS_2017-12-29_final.stac-item
2018-01-03 10:32:23	ga_s2bm_ard_3-2-1_53JPN_2018-01-03_final.stac-item
2018-01-30 10:23:21	ga_s2bm_ard_3-2-1_53JPG_2018-01-30_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_51JUN_2018-01-31_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_51LXC_2018-01-31_final.stac-item
2018-05-02 11:00:12	ga_s2bm_ard_3-2-1_52JEL_2018-05-02_final.stac-item
2018-07-04 11:12:50	ga_s2bm_ard_3-2-1_51JXJ_2018-07-04_final.stac-item
2018-10-02 11:12:46	ga_s2bm_ard_3-2-1_51HXD_2018-10-02_final.stac-item
2018-11-19 10:36:33	ga_s2bm_ard_3-2-1_53HNC_2018-11-19_final.stac-item
2018-11-27 11:33:05	ga_s2bm_ard_3-2-1_51KXT_2018-11-27_final.stac-item
2019-01-16 11:34:14	ga_s2bm_ard_3-2-1_51KVP_2019-01-16_final.stac-item
2019-03-22 10:46:00	ga_s2bm_ard_3-2-1_52JGL_2019-03-22_final.stac-item
2019-04-13 11:23:32	ga_s2bm_ard_3-2-1_52KCA_2019-04-13_final.stac-item
2019-05-08 10:34:01	ga_s2bm_ard_3-2-1_53KPP_2019-05-08_final.stac-item
2019-10-20 11:25:17	ga_s2bm_ard_3-2-1_51JVK_2019-10-20_final.stac-item
2019-10-27 11:13:16	ga_s2bm_ard_3-2-1_52KEB_2019-10-27_final.stac-item
2019-12-01 10:26:02	ga_s2bm_ard_3-2-1_53HPE_2019-12-01_final.stac-item
2019-12-22 11:34:32	ga_s2bm_ard_3-2-1_50JRT_2019-12-22_final.stac-item
2020-01-11 11:34:31	ga_s2bm_ard_3-2-1_51JTN_2020-01-11_final.stac-item
2020-02-11 11:00:54	ga_s2bm_ard_3-2-1_52LHL_2020-02-11_final.stac-item
2020-03-01 11:32:38	ga_s2bm_ard_3-2-1_51KWV_2020-03-01_final.stac-item
2020-03-21 11:33:14	ga_s2bm_ard_3-2-1_51KVT_2020-03-21_final.stac-item
2020-05-06 11:55:32	ga_s2bm_ard_3-2-1_50JNP_2020-05-06_final.stac-item
2020-07-14 10:43:49	ga_s2bm_ard_3-2-1_53KPP_2020-07-14_final.stac-item
2020-08-11 11:45:03	ga_s2bm_ard_3-2-1_51JTL_2020-08-11_final.stac-item
2020-08-11 11:46:46	ga_s2bm_ard_3-2-1_50HQJ_2020-08-11_final.stac-item
2020-09-01 11:15:51	ga_s2bm_ard_3-2-1_52JCM_2020-09-01_final.stac-item
2020-10-09 10:36:00	ga_s2bm_ard_3-2-1_53HQE_2020-10-09_final.stac-item
2020-10-19 10:34:11	ga_s2bm_ard_3-2-1_53JPN_2020-10-19_final.stac-item
2020-10-31 11:10:28	ga_s2bm_ard_3-2-1_52LHN_2020-10-31_final.stac-item
2020-12-09 11:42:58	ga_s2bm_ard_3-2-1_51KUU_2020-12-09_final.stac-item
2020-12-10 11:15:45	ga_s2bm_ard_3-2-1_52JCM_2020-12-10_final.stac-item
2021-01-27 10:34:17	ga_s2bm_ard_3-2-1_53JPM_2021-01-27_final.stac-item
2021-02-01 11:22:23	ga_s2bm_ard_3-2-1_51KZA_2021-02-01_final.stac-item
2021-02-05 11:04:17	ga_s2bm_ard_3-2-1_52JET_2021-02-05_final.stac-item
2021-02-11 11:24:03	ga_s2bm_ard_3-2-1_52KBU_2021-02-11_final.stac-item
2021-03-05 10:27:04	ga_s2bm_ard_3-2-1_53HPA_2021-03-05_final.stac-item
2021-03-13 11:24:40	ga_s2bm_ard_3-2-1_51JXM_2021-03-13_final.stac-item
2021-03-20 11:14:30	ga_s2bm_ard_3-2-1_52JDS_2021-03-20_final.stac-item
2021-06-03 12:04:22	ga_s2bm_ard_3-2-1_49KHP_2021-06-03_final.stac-item
2021-06-11 11:24:52	ga_s2bm_ard_3-2-1_51JYL_2021-06-11_final.stac-item
2021-06-14 11:34:06	ga_s2bm_ard_3-2-1_51KXP_2021-06-14_final.stac-item
2021-06-20 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2021-06-20_final.stac-item
2021-07-11 11:23:08	ga_s2bm_ard_3-2-1_52KBC_2021-07-11_final.stac-item
2021-07-20 11:55:29	ga_s2bm_ard_3-2-1_50JLQ_2021-07-20_final.stac-item
2021-07-24 11:33:32	ga_s2bm_ard_3-2-1_51KVS_2021-07-24_final.stac-item
2021-08-26 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2021-08-26_final.stac-item
2021-09-17 10:46:20	ga_s2bm_ard_3-2-1_53HLD_2021-09-17_final.stac-item
2021-11-03 10:36:29	ga_s2bm_ard_3-2-1_53HLD_2021-11-03_final.stac-item
2021-11-08 11:23:16	ga_s2bm_ard_3-2-1_52KCB_2021-11-08_final.stac-item
2021-11-23 10:36:32	ga_s2bm_ard_3-2-1_53HNC_2021-11-23_final.stac-item
2022-02-02 11:42:25	ga_s2bm_ard_3-2-1_51KUA_2022-02-02_final.stac-item
2022-03-16 10:46:04	ga_s2bm_ard_3-2-1_53HME_2022-03-16_final.stac-item
2022-04-03 11:46:05	ga_s2bm_ard_3-2-1_50JNM_2022-04-03_final.stac-item
2022-04-13 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2022-04-13_final.stac-item
2022-05-01 11:04:26	ga_s2bm_ard_3-2-1_52JES_2022-05-01_final.stac-item
2022-05-23 11:44:31	ga_s2bm_ard_3-2-1_51JTN_2022-05-23_final.stac-item
2022-06-18 12:03:37	ga_s2bm_ard_3-2-1_50KNB_2022-06-18_final.stac-item
2022-07-24 10:44:21	ga_s2bm_ard_3-2-1_53JPM_2022-07-24_final.stac-item
2022-08-28 11:36:32	ga_s2bm_ard_3-2-1_51HTE_2022-08-28_final.stac-item
2022-09-25 10:56:01	ga_s2bm_ard_3-2-1_52JFL_2022-09-25_final.stac-item
2022-10-01 11:15:36	ga_s2bm_ard_3-2-1_52JBN_2022-10-01_final.stac-item
2022-11-03 11:26:59	ga_s2bm_ard_3-2-1_51HUC_2022-11-03_final.stac-item
2022-12-16 11:33:51	ga_s2bm_ard_3-2-1_51KXQ_2022-12-16_final.stac-item
2022-12-30 11:13:38	ga_s2bm_ard_3-2-1_52KBA_2022-12-30_final.stac-item
2022-12-31 10:41:48	ga_s2bm_ard_3-2-1_53KQB_2022-12-31_final.stac-item
2023-01-03 10:54:28	ga_s2bm_ard_3-2-1_52JGS_2023-01-03_final.stac-item
2023-01-13 10:52:22	ga_s2bm_ard_3-2-1_53KLV_2023-01-13_final.stac-item
2023-02-01 11:21:29	ga_s2bm_ard_3-2-1_52LDJ_2023-02-01_final
2023-02-02 10:52:06	ga_s2bm_ard_3-2-1_53KMA_2023-02-02_final
2023-02-13 10:27:03	ga_s2bm_ard_3-2-1_53HPA_2023-02-13_final
2023-02-25 11:03:46	ga_s2bm_ard_3-2-1_52KFV_2023-02-25_final
2023-03-28 10:35:26	ga_s2bm_ard_3-2-1_53JNH_2023-03-28_final
2023-03-30 11:15:03	ga_s2bm_ard_3-2-1_52JDQ_2023-03-30_final
2023-04-10 10:46:11	ga_s2bm_ard_3-2-1_53HLE_2023-04-10_final
2023-04-27 10:33:54	ga_s2bm_ard_3-2-1_53KPP_2023-04-27_final
2023-07-01 11:21:41	ga_s2bm_ard_3-2-1_52LCJ_2023-07-01_final
2023-07-03 10:25:25	ga_s2bm_ard_3-2-1_53JQH_2023-07-03_final
2023-07-21 11:23:34	ga_s2bm_ard_3-2-1_51KXS_2023-07-21_final
2023-07-27 11:46:58	ga_s2bm_ard_3-2-1_50HNJ_2023-07-27_final
2023-09-21 12:05:33	ga_s2bm_ard_3-2-1_49JGK_2023-09-21_final
2023-10-02 11:33:43	ga_s2bm_ard_3-2-1_51KWR_2023-10-02_final
2023-11-12 11:04:37	ga_s2bm_ard_3-2-1_52JDS_2023-11-12_final
2023-11-19 10:52:29	ga_s2bm_ard_3-2-1_52KHE_2023-11-19_final
2023-11-20 10:26:51	ga_s2bm_ard_3-2-1_53HNB_2023-11-20_final
2024-01-10 11:33:22	ga_s2bm_ard_3-2-1_51KXS_2024-01-10_final
2024-01-12 10:34:19	ga_s2bm_ard_3-2-1_53JPM_2024-01-12_final
2024-01-17 11:22:04	ga_s2bm_ard_3-2-1_52KCG_2024-01-17_final
2024-01-28 10:52:00	ga_s2bm_ard_3-2-1_53KKB_2024-01-28_final
2024-02-20 11:02:12	ga_s2bm_ard_3-2-1_52KHF_2024-02-20_final
2024-03-04 11:10:21	ga_s2bm_ard_3-2-1_52LHN_2024-03-04_final
2024-03-10 11:35:29	ga_s2bm_ard_3-2-1_51JTJ_2024-03-10_final
2024-03-11 11:01:39	ga_s2bm_ard_3-2-1_52LHH_2024-03-11_final
2024-03-11 11:03:52	ga_s2bm_ard_3-2-1_52KGU_2024-03-11_final
2024-04-05 11:57:15	ga_s2bm_ard_3-2-1_49HGC_2024-04-05_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

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