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
2017-07-12 11:20:57	ga_s2bm_ard_3-2-1_51KYT_2017-07-12_final.stac-item
2017-08-21 11:18:37	ga_s2bm_ard_3-2-1_51KYT_2017-08-21_final.stac-item
2017-09-19 11:55:56	ga_s2bm_ard_3-2-1_50HLK_2017-09-19_final.stac-item
2017-10-07 11:06:57	ga_s2bm_ard_3-2-1_52KDG_2017-10-07_final.stac-item
2018-01-28 11:19:38	ga_s2bm_ard_3-2-1_51KWQ_2018-01-28_final.stac-item
2018-02-09 12:02:42	ga_s2bm_ard_3-2-1_49JGJ_2018-02-09_final.stac-item
2018-03-19 11:20:54	ga_s2bm_ard_3-2-1_51KXR_2018-03-19_final.stac-item
2018-04-15 11:13:22	ga_s2bm_ard_3-2-1_52KDV_2018-04-15_final.stac-item
2018-09-02 11:14:34	ga_s2bm_ard_3-2-1_52JBP_2018-09-02_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51KZQ_2018-09-05_final.stac-item
2018-12-07 11:33:10	ga_s2bm_ard_3-2-1_51KVT_2018-12-07_final.stac-item
2019-01-03 11:23:08	ga_s2bm_ard_3-2-1_51KYT_2019-01-03_final.stac-item
2019-01-06 11:33:40	ga_s2bm_ard_3-2-1_51KWR_2019-01-06_final.stac-item
2019-01-09 11:43:17	ga_s2bm_ard_3-2-1_51KTT_2019-01-09_final.stac-item
2019-02-06 11:02:55	ga_s2bm_ard_3-2-1_52KHC_2019-02-06_final.stac-item
2019-02-26 11:01:16	ga_s2bm_ard_3-2-1_52LGK_2019-02-26_final.stac-item
2019-03-18 11:05:50	ga_s2bm_ard_3-2-1_52JCM_2019-03-18_final.stac-item
2019-03-31 11:13:56	ga_s2bm_ard_3-2-1_51KZQ_2019-03-31_final.stac-item
2019-04-02 11:56:07	ga_s2bm_ard_3-2-1_50JNM_2019-04-02_final.stac-item
2019-04-06 11:33:34	ga_s2bm_ard_3-2-1_51KVS_2019-04-06_final.stac-item
2019-04-23 11:23:13	ga_s2bm_ard_3-2-1_51KZT_2019-04-23_final.stac-item
2019-06-12 11:23:48	ga_s2bm_ard_3-2-1_51KXR_2019-06-12_final.stac-item
2019-07-06 11:03:25	ga_s2bm_ard_3-2-1_52KFB_2019-07-06_final.stac-item
2019-08-01 11:23:58	ga_s2bm_ard_3-2-1_51KZQ_2019-08-01_final.stac-item
2019-09-07 11:13:42	ga_s2bm_ard_3-2-1_51KZR_2019-09-07_final.stac-item
2019-12-02 11:34:05	ga_s2bm_ard_3-2-1_51KWP_2019-12-02_final.stac-item
2019-12-09 11:23:15	ga_s2bm_ard_3-2-1_52KBB_2019-12-09_final.stac-item
2019-12-15 11:43:24	ga_s2bm_ard_3-2-1_51KUS_2019-12-15_final.stac-item
2020-01-15 11:10:37	ga_s2bm_ard_3-2-1_52LGM_2020-01-15_final.stac-item
2020-02-07 11:23:29	ga_s2bm_ard_3-2-1_52KBA_2020-02-07_final.stac-item
2020-03-08 11:23:08	ga_s2bm_ard_3-2-1_51KYT_2020-03-08_final.stac-item
2020-04-14 11:10:57	ga_s2bm_ard_3-2-1_52LFL_2020-04-14_final.stac-item
2020-06-10 11:03:22	ga_s2bm_ard_3-2-1_52KEB_2020-06-10_final.stac-item
2020-06-29 11:37:05	ga_s2bm_ard_3-2-1_50HQH_2020-06-29_final.stac-item
2020-08-15 11:23:24	ga_s2bm_ard_3-2-1_52KBB_2020-08-15_final.stac-item
2020-08-21 11:43:15	ga_s2bm_ard_3-2-1_51KVT_2020-08-21_final.stac-item
2020-10-11 11:13:34	ga_s2bm_ard_3-2-1_52KEA_2020-10-11_final.stac-item
2021-01-18 11:46:22	ga_s2bm_ard_3-2-1_50JNL_2021-01-18_final.stac-item
2021-01-28 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2021-01-28_final.stac-item
2021-02-04 11:33:15	ga_s2bm_ard_3-2-1_51KVT_2021-02-04_final.stac-item
2021-02-06 12:14:20	ga_s2bm_ard_3-2-1_49KHP_2021-02-06_final.stac-item
2021-03-06 11:33:33	ga_s2bm_ard_3-2-1_51KUS_2021-03-06_final.stac-item
2021-05-19 11:13:40	ga_s2bm_ard_3-2-1_51KZR_2021-05-19_final.stac-item
2021-05-28 11:43:44	ga_s2bm_ard_3-2-1_51KUR_2021-05-28_final.stac-item
2021-06-03 12:04:29	ga_s2bm_ard_3-2-1_50KKU_2021-06-03_final.stac-item
2021-06-03 12:05:01	ga_s2bm_ard_3-2-1_49JGM_2021-06-03_final.stac-item
2021-06-08 11:13:26	ga_s2bm_ard_3-2-1_52KBB_2021-06-08_final.stac-item
2021-06-08 11:14:10	ga_s2bm_ard_3-2-1_52KBU_2021-06-08_final.stac-item
2021-07-04 11:36:28	ga_s2bm_ard_3-2-1_50JPL_2021-07-04_final.stac-item
2021-08-07 11:13:05	ga_s2bm_ard_3-2-1_52KDC_2021-08-07_final.stac-item
2021-09-05 11:42:32	ga_s2bm_ard_3-2-1_51KVV_2021-09-05_final.stac-item
2021-09-06 11:13:51	ga_s2bm_ard_3-2-1_51KZQ_2021-09-06_final.stac-item
2021-09-29 11:23:27	ga_s2bm_ard_3-2-1_51KXS_2021-09-29_final.stac-item
2021-10-12 11:36:47	ga_s2bm_ard_3-2-1_51HTD_2021-10-12_final.stac-item
2021-11-01 11:32:56	ga_s2bm_ard_3-2-1_51KXU_2021-11-01_final.stac-item
2021-11-24 11:43:07	ga_s2bm_ard_3-2-1_51KVT_2021-11-24_final.stac-item
2022-01-09 12:06:06	ga_s2bm_ard_3-2-1_50JKM_2022-01-09_final.stac-item
2022-02-02 11:43:38	ga_s2bm_ard_3-2-1_51KUR_2022-02-02_final.stac-item
2022-03-18 11:23:52	ga_s2bm_ard_3-2-1_51KYQ_2022-03-18_final.stac-item
2022-04-20 11:34:06	ga_s2bm_ard_3-2-1_51KWP_2022-04-20_final.stac-item
2022-04-22 12:14:36	ga_s2bm_ard_3-2-1_49JGN_2022-04-22_final.stac-item
2022-05-23 11:42:28	ga_s2bm_ard_3-2-1_51KVA_2022-05-23_final.stac-item
2022-05-28 10:55:35	ga_s2bm_ard_3-2-1_52JEN_2022-05-28_final.stac-item
2022-08-10 12:14:02	ga_s2bm_ard_3-2-1_49KGR_2022-08-10_final.stac-item
2022-08-15 11:21:35	ga_s2bm_ard_3-2-1_52LDJ_2022-08-15_final.stac-item
2022-08-28 11:36:24	ga_s2bm_ard_3-2-1_51HVE_2022-08-28_final.stac-item
2022-09-04 11:23:30	ga_s2bm_ard_3-2-1_51KXS_2022-09-04_final.stac-item
2022-11-19 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2022-11-19_final.stac-item
2022-12-03 11:24:06	ga_s2bm_ard_3-2-1_51KYP_2022-12-03_final.stac-item
2023-01-26 11:03:00	ga_s2bm_ard_3-2-1_52KFC_2023-01-26_final.stac-item
2023-03-10 11:10:47	ga_s2bm_ard_3-2-1_52LGM_2023-03-10_final
2023-04-02 11:25:27	ga_s2bm_ard_3-2-1_51JXJ_2023-04-02_final
2023-04-15 11:34:16	ga_s2bm_ard_3-2-1_51JXN_2023-04-15_final
2023-04-18 11:42:15	ga_s2bm_ard_3-2-1_51KVB_2023-04-18_final
2023-05-08 11:41:35	ga_s2bm_ard_3-2-1_51LUE_2023-05-08_final
2023-05-19 11:13:30	ga_s2bm_ard_3-2-1_52KBB_2023-05-19_final
2023-05-19 11:13:59	ga_s2bm_ard_3-2-1_51KZQ_2023-05-19_final
2023-06-01 11:26:44	ga_s2bm_ard_3-2-1_51HWD_2023-06-01_final
2023-06-04 11:33:46	ga_s2bm_ard_3-2-1_51KWR_2023-06-04_final
2023-07-04 11:33:07	ga_s2bm_ard_3-2-1_51KVU_2023-07-04_final
2023-07-08 11:13:42	ga_s2bm_ard_3-2-1_52KCA_2023-07-08_final
2023-07-28 11:14:15	ga_s2bm_ard_3-2-1_52KBU_2023-07-28_final
2023-08-01 10:55:36	ga_s2bm_ard_3-2-1_52JFN_2023-08-01_final
2023-08-03 11:34:04	ga_s2bm_ard_3-2-1_51KVQ_2023-08-03_final
2023-10-05 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2023-10-05_final
2023-10-09 11:23:29	ga_s2bm_ard_3-2-1_51KXS_2023-10-09_final
2023-11-04 11:43:06	ga_s2bm_ard_3-2-1_51KTU_2023-11-04_final
2023-11-30 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2023-11-30_final
2024-01-03 11:42:57	ga_s2bm_ard_3-2-1_51KVU_2024-01-03_final
2024-01-04 11:14:08	ga_s2bm_ard_3-2-1_52JET_2024-01-04_final
2024-01-20 11:33:12	ga_s2bm_ard_3-2-1_51KWT_2024-01-20_final
2024-01-30 11:32:59	ga_s2bm_ard_3-2-1_51KVU_2024-01-30_final
2024-02-19 11:32:59	ga_s2bm_ard_3-2-1_51KWU_2024-02-19_final
2024-02-20 11:01:03	ga_s2bm_ard_3-2-1_52LGL_2024-02-20_final
2024-04-08 12:03:43	ga_s2bm_ard_3-2-1_50KKB_2024-04-08_final
2024-04-29 11:32:25	ga_s2bm_ard_3-2-1_51KXA_2024-04-29_final
2024-05-13 11:14:29	ga_s2bm_ard_3-2-1_51JYN_2024-05-13_final
2024-05-26 11:24:04	ga_s2bm_ard_3-2-1_52KBU_2024-05-26_nrt
2024-05-28 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2024-05-28_nrt
2024-06-01 11:42:14	ga_s2bm_ard_3-2-1_51KVB_2024-06-01_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

All years