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
2017-07-04 11:59:31	ga_s2bm_ard_3-2-1_50KKB_2017-07-04_final.stac-item
2017-08-27 11:40:44	ga_s2bm_ard_3-2-1_50JQP_2017-08-27_final.stac-item
2017-10-07 11:11:46	ga_s2bm_ard_3-2-1_51HWD_2017-10-07_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_49JGM_2017-11-21_final.stac-item
2017-12-05 11:46:02	ga_s2bm_ard_3-2-1_50JML_2017-12-05_final.stac-item
2018-02-06 11:49:12	ga_s2bm_ard_3-2-1_50HLJ_2018-02-06_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50HLH_2018-02-13_final.stac-item
2018-02-19 12:02:42	ga_s2bm_ard_3-2-1_50KKB_2018-02-19_final.stac-item
2018-02-23 11:40:38	ga_s2bm_ard_3-2-1_50KRC_2018-02-23_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JKP_2018-03-21_final.stac-item
2018-04-04 11:40:13	ga_s2bm_ard_3-2-1_50KRD_2018-04-04_final.stac-item
2018-04-17 11:52:54	ga_s2bm_ard_3-2-1_50KRC_2018-04-17_final.stac-item
2018-05-24 11:43:21	ga_s2bm_ard_3-2-1_51JTH_2018-05-24_final.stac-item
2018-06-19 12:02:48	ga_s2bm_ard_3-2-1_49JGN_2018-06-19_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_50KRB_2018-06-23_final.stac-item
2018-07-04 11:12:50	ga_s2bm_ard_3-2-1_51HXD_2018-07-04_final.stac-item
2018-07-23 11:40:57	ga_s2bm_ard_3-2-1_50JQL_2018-07-23_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50JMM_2018-08-05_final.stac-item
2018-09-14 11:52:51	ga_s2bm_ard_3-2-1_50KRC_2018-09-14_final.stac-item
2018-12-20 11:44:26	ga_s2bm_ard_3-2-1_50JRT_2018-12-20_final.stac-item
2019-01-08 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2019-01-08_final.stac-item
2019-01-09 11:43:17	ga_s2bm_ard_3-2-1_50KRC_2019-01-09_final.stac-item
2019-01-22 11:56:14	ga_s2bm_ard_3-2-1_50JKM_2019-01-22_final.stac-item
2019-04-25 12:03:51	ga_s2bm_ard_3-2-1_50KKB_2019-04-25_final.stac-item
2019-06-11 11:54:15	ga_s2bm_ard_3-2-1_50KNV_2019-06-11_final.stac-item
2019-08-04 11:36:56	ga_s2bm_ard_3-2-1_50HQJ_2019-08-04_final.stac-item
2019-08-17 11:46:25	ga_s2bm_ard_3-2-1_50JPL_2019-08-17_final.stac-item
2019-10-19 11:55:04	ga_s2bm_ard_3-2-1_50JPR_2019-10-19_final.stac-item
2019-11-22 11:37:00	ga_s2bm_ard_3-2-1_50HQH_2019-11-22_final.stac-item
2020-01-07 11:56:13	ga_s2bm_ard_3-2-1_50JNL_2020-01-07_final.stac-item
2020-02-19 12:03:40	ga_s2bm_ard_3-2-1_50KKB_2020-02-19_final.stac-item
2020-04-23 11:46:17	ga_s2bm_ard_3-2-1_50JNL_2020-04-23_final.stac-item
2020-05-17 11:26:22	ga_s2bm_ard_3-2-1_51HXE_2020-05-17_final.stac-item
2020-07-19 11:36:12	ga_s2bm_ard_3-2-1_51JVF_2020-07-19_final.stac-item
2020-08-21 11:46:16	ga_s2bm_ard_3-2-1_50JMM_2020-08-21_final.stac-item
2020-09-26 12:04:45	ga_s2bm_ard_3-2-1_50JKT_2020-09-26_final.stac-item
2020-10-23 11:56:03	ga_s2bm_ard_3-2-1_50JKN_2020-10-23_final.stac-item
2020-10-26 12:03:44	ga_s2bm_ard_3-2-1_50KLB_2020-10-26_final.stac-item
2020-12-29 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2020-12-29_final.stac-item
2021-01-21 11:57:12	ga_s2bm_ard_3-2-1_50HMH_2021-01-21_final.stac-item
2021-02-10 11:56:28	ga_s2bm_ard_3-2-1_50HNK_2021-02-10_final.stac-item
2021-03-02 11:53:49	ga_s2bm_ard_3-2-1_50KPA_2021-03-02_final.stac-item
2021-03-02 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2021-03-02_final.stac-item
2021-03-03 11:24:58	ga_s2bm_ard_3-2-1_51JWL_2021-03-03_final.stac-item
2021-04-11 11:55:53	ga_s2bm_ard_3-2-1_50JLN_2021-04-11_final.stac-item
2021-05-18 11:45:55	ga_s2bm_ard_3-2-1_51JTG_2021-05-18_final.stac-item
2021-06-27 11:46:34	ga_s2bm_ard_3-2-1_50HPK_2021-06-27_final.stac-item
2021-07-07 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2021-07-07_final.stac-item
2021-08-09 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2021-08-09_final.stac-item
2021-08-13 11:36:52	ga_s2bm_ard_3-2-1_50HPJ_2021-08-13_final.stac-item
2021-08-22 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2021-08-22_final.stac-item
2021-09-05 11:46:48	ga_s2bm_ard_3-2-1_50HNJ_2021-09-05_final.stac-item
2021-09-28 11:52:19	ga_s2bm_ard_3-2-1_50KQG_2021-09-28_final
2021-10-04 12:13:44	ga_s2bm_ard_3-2-1_49KHS_2021-10-04_final
2021-10-12 11:36:35	ga_s2bm_ard_3-2-1_50HQK_2021-10-12_final.stac-item
2022-01-07 11:26:54	ga_s2bm_ard_3-2-1_51HVC_2022-01-07_final.stac-item
2022-01-17 11:24:54	ga_s2bm_ard_3-2-1_51JWL_2022-01-17_final.stac-item
2022-01-20 11:36:22	ga_s2bm_ard_3-2-1_50JPL_2022-01-20_final.stac-item
2022-01-29 12:05:38	ga_s2bm_ard_3-2-1_49JGJ_2022-01-29_final.stac-item
2022-03-04 11:44:28	ga_s2bm_ard_3-2-1_50JRT_2022-03-04_final.stac-item
2022-04-26 11:53:18	ga_s2bm_ard_3-2-1_50KNC_2022-04-26_final.stac-item
2022-04-26 11:56:16	ga_s2bm_ard_3-2-1_50JML_2022-04-26_final.stac-item
2022-05-20 11:36:57	ga_s2bm_ard_3-2-1_51HUC_2022-05-20_final.stac-item
2022-07-08 12:05:49	ga_s2bm_ard_3-2-1_49JGJ_2022-07-08_final.stac-item
2022-07-22 11:46:39	ga_s2bm_ard_3-2-1_50HPK_2022-07-22_final.stac-item
2022-08-18 11:37:19	ga_s2bm_ard_3-2-1_50HQG_2022-08-18_final
2022-09-07 11:35:28	ga_s2bm_ard_3-2-1_51JVJ_2022-09-07_final.stac-item
2022-10-26 12:03:22	ga_s2bm_ard_3-2-1_50KMC_2022-10-26_final.stac-item
2022-11-15 12:04:24	ga_s2bm_ard_3-2-1_50KLU_2022-11-15_final.stac-item
2022-12-15 12:03:42	ga_s2bm_ard_3-2-1_50KKB_2022-12-15_final.stac-item
2023-01-02 11:27:00	ga_s2bm_ard_3-2-1_51HUC_2023-01-02_final.stac-item
2023-01-04 12:03:57	ga_s2bm_ard_3-2-1_49KHR_2023-01-04_final.stac-item
2023-01-21 11:53:33	ga_s2bm_ard_3-2-1_50KPB_2023-01-21_final.stac-item
2023-03-09 11:43:22	ga_s2bm_ard_3-2-1_50KRC_2023-03-09_final
2023-03-28 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2023-03-28_final
2023-04-18 11:46:17	ga_s2bm_ard_3-2-1_50JQL_2023-04-18_final
2023-04-21 11:53:23	ga_s2bm_ard_3-2-1_50KPC_2023-04-21_final
2023-04-24 12:03:25	ga_s2bm_ard_3-2-1_50KMC_2023-04-24_final
2023-05-05 11:37:03	ga_s2bm_ard_3-2-1_51HTC_2023-05-05_final
2023-06-10 11:57:27	ga_s2bm_ard_3-2-1_50HLG_2023-06-10_final
2023-06-27 11:45:04	ga_s2bm_ard_3-2-1_51JTL_2023-06-27_final
2023-07-17 11:43:09	ga_s2bm_ard_3-2-1_50KRD_2023-07-17_final
2023-07-23 12:06:01	ga_s2bm_ard_3-2-1_50JKN_2023-07-23_final
2023-08-02 12:05:42	ga_s2bm_ard_3-2-1_50JLP_2023-08-02_final
2023-08-06 11:43:09	ga_s2bm_ard_3-2-1_50KRD_2023-08-06_final
2023-08-16 11:47:30	ga_s2bm_ard_3-2-1_50HMG_2023-08-16_final
2023-09-04 12:13:59	ga_s2bm_ard_3-2-1_49KHR_2023-09-04_final
2023-10-18 11:53:23	ga_s2bm_ard_3-2-1_50KPC_2023-10-18_final
2023-11-28 11:26:11	ga_s2bm_ard_3-2-1_51JVF_2023-11-28_final
2023-12-17 11:53:30	ga_s2bm_ard_3-2-1_50KMC_2023-12-17_final
2023-12-21 11:36:53	ga_s2bm_ard_3-2-1_50HPJ_2023-12-21_final
2023-12-31 11:35:13	ga_s2bm_ard_3-2-1_51JVK_2023-12-31_final
2024-01-26 11:53:20	ga_s2bm_ard_3-2-1_50KPC_2024-01-26_final
2024-01-30 11:37:15	ga_s2bm_ard_3-2-1_50HQG_2024-01-30_final
2024-02-21 12:13:55	ga_s2bm_ard_3-2-1_50KKA_2024-02-21_final
2024-02-28 12:03:22	ga_s2bm_ard_3-2-1_50KMC_2024-02-28_final
2024-03-16 11:53:16	ga_s2bm_ard_3-2-1_50KQC_2024-03-16_final
2024-03-29 12:03:44	ga_s2bm_ard_3-2-1_49KHS_2024-03-29_final
2024-04-05 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2024-04-05_final
2024-05-05 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2024-05-05_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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