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
2017-07-05 11:32:58	ga_s2bm_ard_3-2-1_50HQJ_2017-07-05_final.stac-item
2017-09-03 11:30:07	ga_s2bm_ard_3-2-1_51HUE_2017-09-03_final.stac-item
2017-12-01 12:02:38	ga_s2bm_ard_3-2-1_50KKB_2017-12-01_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_49KGQ_2017-12-11_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_50KLU_2017-12-11_final.stac-item
2018-01-27 11:50:39	ga_s2bm_ard_3-2-1_50KRC_2018-01-27_final.stac-item
2018-03-09 11:26:31	ga_s2bm_ard_3-2-1_51HUD_2018-03-09_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_50JKP_2018-03-21_final.stac-item
2018-05-13 12:14:07	ga_s2bm_ard_3-2-1_49KGQ_2018-05-13_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50KRU_2018-08-12_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49KGP_2018-10-30_final.stac-item
2018-11-26 12:05:37	ga_s2bm_ard_3-2-1_50JKP_2018-11-26_final.stac-item
2019-01-08 12:13:53	ga_s2bm_ard_3-2-1_50KKA_2019-01-08_final.stac-item
2019-01-29 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-01-29_final.stac-item
2019-02-02 11:26:59	ga_s2bm_ard_3-2-1_51HVC_2019-02-02_final.stac-item
2019-03-09 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2019-03-09_final.stac-item
2019-03-20 11:43:03	ga_s2bm_ard_3-2-1_50KRD_2019-03-20_final.stac-item
2019-04-06 11:36:46	ga_s2bm_ard_3-2-1_51HUD_2019-04-06_final.stac-item
2019-04-28 12:14:20	ga_s2bm_ard_3-2-1_49KGQ_2019-04-28_final.stac-item
2019-06-08 11:47:03	ga_s2bm_ard_3-2-1_50HMJ_2019-06-08_final.stac-item
2019-07-17 12:15:19	ga_s2bm_ard_3-2-1_49JGL_2019-07-17_final.stac-item
2019-08-16 12:14:04	ga_s2bm_ard_3-2-1_49KGR_2019-08-16_final.stac-item
2019-09-09 11:53:12	ga_s2bm_ard_3-2-1_50KRC_2019-09-09_final.stac-item
2019-09-19 11:54:54	ga_s2bm_ard_3-2-1_50JMS_2019-09-19_final.stac-item
2019-11-01 12:04:58	ga_s2bm_ard_3-2-1_50JKS_2019-11-01_final.stac-item
2019-11-28 11:53:07	ga_s2bm_ard_3-2-1_50KRC_2019-11-28_final.stac-item
2020-02-10 11:36:47	ga_s2bm_ard_3-2-1_50HPJ_2020-02-10_final.stac-item
2020-02-16 11:52:30	ga_s2bm_ard_3-2-1_50KQF_2020-02-16_final
2020-03-13 12:14:02	ga_s2bm_ard_3-2-1_50KKV_2020-03-13_final.stac-item
2020-03-13 12:15:08	ga_s2bm_ard_3-2-1_49JGL_2020-03-13_final.stac-item
2020-05-02 12:13:51	ga_s2bm_ard_3-2-1_50KKA_2020-05-02_final.stac-item
2020-05-02 12:14:10	ga_s2bm_ard_3-2-1_49KGQ_2020-05-02_final.stac-item
2020-05-17 11:26:53	ga_s2bm_ard_3-2-1_51HUD_2020-05-17_final.stac-item
2020-05-20 11:37:01	ga_s2bm_ard_3-2-1_51HTC_2020-05-20_final.stac-item
2020-07-18 12:05:45	ga_s2bm_ard_3-2-1_49JGJ_2020-07-18_final.stac-item
2020-07-21 12:13:56	ga_s2bm_ard_3-2-1_50KKA_2020-07-21_final.stac-item
2020-07-29 11:36:36	ga_s2bm_ard_3-2-1_50HQK_2020-07-29_final.stac-item
2020-08-11 11:45:57	ga_s2bm_ard_3-2-1_50JNN_2020-08-11_final.stac-item
2020-09-03 11:56:43	ga_s2bm_ard_3-2-1_50HLK_2020-09-03_final.stac-item
2020-10-26 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2020-10-26_final.stac-item
2020-12-19 11:46:22	ga_s2bm_ard_3-2-1_50JPL_2020-12-19_final.stac-item
2021-01-08 11:46:24	ga_s2bm_ard_3-2-1_50JPL_2021-01-08_final.stac-item
2021-02-10 11:55:52	ga_s2bm_ard_3-2-1_50JMN_2021-02-10_final.stac-item
2021-02-16 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2021-02-16_final.stac-item
2021-04-07 12:14:57	ga_s2bm_ard_3-2-1_49JFM_2021-04-07_final.stac-item
2021-04-25 11:36:21	ga_s2bm_ard_3-2-1_50JPL_2021-04-25_final.stac-item
2021-05-18 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2021-05-18_final.stac-item
2021-05-31 11:55:50	ga_s2bm_ard_3-2-1_50JNN_2021-05-31_final.stac-item
2021-07-03 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2021-07-03_final.stac-item
2021-07-31 11:27:03	ga_s2bm_ard_3-2-1_51HUC_2021-07-31_final.stac-item
2021-08-20 11:26:46	ga_s2bm_ard_3-2-1_51HUD_2021-08-20_final.stac-item
2021-08-29 11:53:44	ga_s2bm_ard_3-2-1_50KQA_2021-08-29_final.stac-item
2021-11-20 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2021-11-20_final.stac-item
2021-11-30 12:04:56	ga_s2bm_ard_3-2-1_49JGM_2021-11-30_final.stac-item
2022-01-02 12:13:54	ga_s2bm_ard_3-2-1_49KGR_2022-01-02_final.stac-item
2022-01-09 12:03:55	ga_s2bm_ard_3-2-1_49KHR_2022-01-09_final.stac-item
2022-01-17 11:26:39	ga_s2bm_ard_3-2-1_51HVD_2022-01-17_final.stac-item
2022-01-20 11:36:42	ga_s2bm_ard_3-2-1_51HTD_2022-01-20_final.stac-item
2022-01-29 12:03:53	ga_s2bm_ard_3-2-1_49KHR_2022-01-29_final.stac-item
2022-01-30 11:36:51	ga_s2bm_ard_3-2-1_51HUC_2022-01-30_final.stac-item
2022-03-03 12:13:48	ga_s2bm_ard_3-2-1_49KHR_2022-03-03_final.stac-item
2022-04-29 12:04:53	ga_s2bm_ard_3-2-1_49JGM_2022-04-29_final.stac-item
2022-05-20 11:34:36	ga_s2bm_ard_3-2-1_50JRT_2022-05-20_final.stac-item
2022-05-26 11:56:26	ga_s2bm_ard_3-2-1_50JLL_2022-05-26_final.stac-item
2022-07-05 11:56:34	ga_s2bm_ard_3-2-1_50HNK_2022-07-05_final.stac-item
2022-07-25 11:53:26	ga_s2bm_ard_3-2-1_50KPC_2022-07-25_final.stac-item
2022-08-14 11:55:56	ga_s2bm_ard_3-2-1_50JMN_2022-08-14_final.stac-item
2022-09-09 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2022-09-09_final.stac-item
2022-10-16 12:03:58	ga_s2bm_ard_3-2-1_50KKA_2022-10-16_final.stac-item
2022-11-05 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2022-11-05_final.stac-item
2022-11-25 12:03:43	ga_s2bm_ard_3-2-1_50KKB_2022-11-25_final.stac-item
2022-12-02 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-12-02_final.stac-item
2022-12-12 11:55:57	ga_s2bm_ard_3-2-1_50JKN_2022-12-12_final.stac-item
2023-01-11 11:56:26	ga_s2bm_ard_3-2-1_50HNK_2023-01-11_final.stac-item
2023-01-25 11:36:36	ga_s2bm_ard_3-2-1_50HPK_2023-01-25_final.stac-item
2023-02-16 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2023-02-16_final
2023-04-01 11:54:37	ga_s2bm_ard_3-2-1_50JPT_2023-04-01_final
2023-04-04 12:04:49	ga_s2bm_ard_3-2-1_49JGN_2023-04-04_final
2023-04-14 12:06:05	ga_s2bm_ard_3-2-1_50JLM_2023-04-14_final
2023-04-28 11:43:53	ga_s2bm_ard_3-2-1_50KQA_2023-04-28_final
2023-05-11 11:55:59	ga_s2bm_ard_3-2-1_50JLN_2023-05-11_final
2023-05-18 11:43:26	ga_s2bm_ard_3-2-1_50KQC_2023-05-18_final
2023-05-27 12:14:31	ga_s2bm_ard_3-2-1_49KGP_2023-05-27_final
2023-06-30 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-06-30_final
2023-08-22 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2023-08-22_final
2023-09-14 12:13:57	ga_s2bm_ard_3-2-1_49KHR_2023-09-14_final
2023-10-01 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-10-01_final
2023-11-27 11:55:52	ga_s2bm_ard_3-2-1_50JLN_2023-11-27_final
2023-12-07 11:53:21	ga_s2bm_ard_3-2-1_50KNC_2023-12-07_final
2023-12-24 11:43:30	ga_s2bm_ard_3-2-1_50KQC_2023-12-24_final
2023-12-27 11:56:12	ga_s2bm_ard_3-2-1_50JLM_2023-12-27_final
2024-02-28 12:05:28	ga_s2bm_ard_3-2-1_49JGK_2024-02-28_final
2024-03-06 11:54:28	ga_s2bm_ard_3-2-1_50JPT_2024-03-06_final
2024-04-18 12:04:32	ga_s2bm_ard_3-2-1_50KLU_2024-04-18_final
2024-04-28 12:03:58	ga_s2bm_ard_3-2-1_50KKA_2024-04-28_final
2024-05-08 12:05:52	ga_s2bm_ard_3-2-1_50JLN_2024-05-08_final
2024-05-12 11:46:19	ga_s2bm_ard_3-2-1_50JPL_2024-05-12_final
2024-05-12 11:46:34	ga_s2bm_ard_3-2-1_50HPK_2024-05-12_final
2024-05-26 11:27:02	ga_s2bm_ard_3-2-1_51HUC_2024-05-26_nrt
2024-05-28 12:05:37	ga_s2bm_ard_3-2-1_50JLP_2024-05-28_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