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
2017-07-11 11:56:34	ga_s2bm_ard_3-2-1_50HMJ_2017-07-11_final.stac-item
2017-08-26 12:13:17	ga_s2bm_ard_3-2-1_49KGR_2017-08-26_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50JLL_2017-10-19_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50HNJ_2017-11-05_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49KHP_2017-12-21_final.stac-item
2018-01-07 11:56:02	ga_s2bm_ard_3-2-1_50JML_2018-01-07_final.stac-item
2018-02-19 12:02:42	ga_s2bm_ard_3-2-1_50JKQ_2018-02-19_final.stac-item
2018-03-28 11:51:53	ga_s2bm_ard_3-2-1_50JKP_2018-03-28_final.stac-item
2018-04-17 11:52:54	ga_s2bm_ard_3-2-1_50JKP_2018-04-17_final.stac-item
2018-04-20 12:04:00	ga_s2bm_ard_3-2-1_50JKS_2018-04-20_final.stac-item
2018-06-03 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2018-06-03_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_50JKQ_2018-10-07_final.stac-item
2018-10-11 11:41:47	ga_s2bm_ard_3-2-1_50HMJ_2018-10-11_final.stac-item
2018-10-11 11:41:47	ga_s2bm_ard_3-2-1_50JMM_2018-10-11_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50HLK_2018-11-03_final.stac-item
2019-01-05 12:06:02	ga_s2bm_ard_3-2-1_50JLM_2019-01-05_final.stac-item
2019-01-29 11:46:30	ga_s2bm_ard_3-2-1_50HQK_2019-01-29_final.stac-item
2019-02-08 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-02-08_final.stac-item
2019-02-28 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2019-02-28_final.stac-item
2019-03-23 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2019-03-23_final.stac-item
2019-03-30 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2019-03-30_final.stac-item
2019-05-25 12:04:54	ga_s2bm_ard_3-2-1_49JGN_2019-05-25_final.stac-item
2019-05-29 11:46:49	ga_s2bm_ard_3-2-1_50HMK_2019-05-29_final.stac-item
2019-06-01 11:56:30	ga_s2bm_ard_3-2-1_50JML_2019-06-01_final.stac-item
2019-06-24 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-06-24_final.stac-item
2019-07-11 11:55:18	ga_s2bm_ard_3-2-1_50JMR_2019-07-11_final.stac-item
2019-08-20 11:56:17	ga_s2bm_ard_3-2-1_50JLM_2019-08-20_final.stac-item
2019-08-30 11:56:55	ga_s2bm_ard_3-2-1_50HMJ_2019-08-30_final.stac-item
2019-09-16 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2019-09-16_final.stac-item
2019-10-23 11:36:39	ga_s2bm_ard_3-2-1_50HPK_2019-10-23_final.stac-item
2019-10-23 11:37:04	ga_s2bm_ard_3-2-1_50HQH_2019-10-23_final.stac-item
2019-12-11 12:04:34	ga_s2bm_ard_3-2-1_50JLT_2019-12-11_final.stac-item
2020-01-07 11:56:17	ga_s2bm_ard_3-2-1_50JML_2020-01-07_final.stac-item
2020-02-06 11:55:47	ga_s2bm_ard_3-2-1_50JMN_2020-02-06_final.stac-item
2020-02-10 11:37:01	ga_s2bm_ard_3-2-1_50HPH_2020-02-10_final.stac-item
2020-02-19 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2020-02-19_final.stac-item
2020-02-26 11:54:52	ga_s2bm_ard_3-2-1_50JMS_2020-02-26_final.stac-item
2020-03-04 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2020-03-04_final.stac-item
2020-04-06 11:56:33	ga_s2bm_ard_3-2-1_50HMK_2020-04-06_final.stac-item
2020-04-09 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2020-04-09_final.stac-item
2020-04-19 12:05:07	ga_s2bm_ard_3-2-1_50JKR_2020-04-19_final.stac-item
2020-06-08 12:05:28	ga_s2bm_ard_3-2-1_50JKQ_2020-06-08_final.stac-item
2020-07-01 12:14:48	ga_s2bm_ard_3-2-1_49JFN_2020-07-01_final.stac-item
2020-07-02 11:46:32	ga_s2bm_ard_3-2-1_50HQK_2020-07-02_final.stac-item
2020-08-17 12:05:26	ga_s2bm_ard_3-2-1_50JLQ_2020-08-17_final.stac-item
2020-08-24 11:55:45	ga_s2bm_ard_3-2-1_50JLP_2020-08-24_final.stac-item
2020-08-31 11:46:16	ga_s2bm_ard_3-2-1_50JMM_2020-08-31_final.stac-item
2020-09-23 11:56:53	ga_s2bm_ard_3-2-1_50HMJ_2020-09-23_final.stac-item
2020-10-06 12:05:00	ga_s2bm_ard_3-2-1_49JHM_2020-10-06_final.stac-item
2020-10-23 11:55:45	ga_s2bm_ard_3-2-1_50JLP_2020-10-23_final.stac-item
2020-10-30 11:46:58	ga_s2bm_ard_3-2-1_50HMJ_2020-10-30_final.stac-item
2020-11-02 11:55:12	ga_s2bm_ard_3-2-1_50JMR_2020-11-02_final.stac-item
2020-12-19 11:46:48	ga_s2bm_ard_3-2-1_50HNJ_2020-12-19_final.stac-item
2020-12-25 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2020-12-25_final.stac-item
2021-01-04 12:03:43	ga_s2bm_ard_3-2-1_49KHS_2021-01-04_final
2021-02-23 12:05:21	ga_s2bm_ard_3-2-1_50JLQ_2021-02-23_final.stac-item
2021-03-02 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2021-03-02_final.stac-item
2021-04-18 11:47:12	ga_s2bm_ard_3-2-1_50HPG_2021-04-18_final
2021-04-24 12:04:40	ga_s2bm_ard_3-2-1_49JGN_2021-04-24_final.stac-item
2021-05-11 11:57:19	ga_s2bm_ard_3-2-1_50HMG_2021-05-11_final
2021-06-10 11:54:56	ga_s2bm_ard_3-2-1_50JMS_2021-06-10_final.stac-item
2021-09-08 11:55:38	ga_s2bm_ard_3-2-1_50JLP_2021-09-08_final.stac-item
2021-10-14 12:14:14	ga_s2bm_ard_3-2-1_49KGQ_2021-10-14_final.stac-item
2021-12-04 11:47:04	ga_s2bm_ard_3-2-1_50HLH_2021-12-04_final.stac-item
2021-12-10 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2021-12-10_final.stac-item
2021-12-13 12:14:07	ga_s2bm_ard_3-2-1_49KGQ_2021-12-13_final.stac-item
2022-01-03 11:46:17	ga_s2bm_ard_3-2-1_50JML_2022-01-03_final.stac-item
2022-01-03 11:46:37	ga_s2bm_ard_3-2-1_50HMK_2022-01-03_final.stac-item
2022-01-23 11:46:56	ga_s2bm_ard_3-2-1_50HNH_2022-01-23_final.stac-item
2022-02-18 12:05:05	ga_s2bm_ard_3-2-1_50JKR_2022-02-18_final.stac-item
2022-03-14 11:46:11	ga_s2bm_ard_3-2-1_50JMM_2022-03-14_final.stac-item
2022-03-17 11:54:42	ga_s2bm_ard_3-2-1_50JLT_2022-03-17_final.stac-item
2022-03-24 11:46:10	ga_s2bm_ard_3-2-1_50JMM_2022-03-24_final.stac-item
2022-04-16 11:56:33	ga_s2bm_ard_3-2-1_50HMK_2022-04-16_final.stac-item
2022-08-14 11:56:39	ga_s2bm_ard_3-2-1_50HMK_2022-08-14_final.stac-item
2022-10-03 11:55:40	ga_s2bm_ard_3-2-1_50JLP_2022-10-03_final.stac-item
2023-01-08 11:46:27	ga_s2bm_ard_3-2-1_50HQK_2023-01-08_final.stac-item
2023-02-03 12:03:41	ga_s2bm_ard_3-2-1_49KHS_2023-02-03_final
2023-02-24 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2023-02-24_final
2023-03-09 11:47:18	ga_s2bm_ard_3-2-1_50HLH_2023-03-09_final
2023-03-25 12:04:59	ga_s2bm_ard_3-2-1_50JKS_2023-03-25_final
2023-04-01 11:55:16	ga_s2bm_ard_3-2-1_50JLR_2023-04-01_final
2023-05-24 12:04:47	ga_s2bm_ard_3-2-1_50JKT_2023-05-24_final
2023-06-23 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2023-06-23_final
2023-07-03 12:05:02	ga_s2bm_ard_3-2-1_50JKS_2023-07-03_final
2023-07-14 11:37:31	ga_s2bm_ard_3-2-1_50HNG_2023-07-14_final
2023-08-06 11:46:18	ga_s2bm_ard_3-2-1_50JMM_2023-08-06_final
2023-09-25 11:46:33	ga_s2bm_ard_3-2-1_50HQK_2023-09-25_final
2023-10-08 11:57:23	ga_s2bm_ard_3-2-1_50HLG_2023-10-08_final
2023-10-28 11:55:54	ga_s2bm_ard_3-2-1_50JMN_2023-10-28_final
2023-10-31 12:03:47	ga_s2bm_ard_3-2-1_49KHS_2023-10-31_final
2023-11-01 11:37:09	ga_s2bm_ard_3-2-1_50HPH_2023-11-01_final
2024-01-09 12:03:43	ga_s2bm_ard_3-2-1_49KHS_2024-01-09_final
2024-01-26 11:56:32	ga_s2bm_ard_3-2-1_50HMK_2024-01-26_final
2024-02-09 11:36:52	ga_s2bm_ard_3-2-1_50HPJ_2024-02-09_final
2024-02-12 11:46:13	ga_s2bm_ard_3-2-1_50JMM_2024-02-12_final
2024-02-22 11:46:52	ga_s2bm_ard_3-2-1_50HNJ_2024-02-22_final
2024-03-16 11:56:49	ga_s2bm_ard_3-2-1_50HMJ_2024-03-16_final
2024-03-16 11:57:04	ga_s2bm_ard_3-2-1_50HMH_2024-03-16_final
2024-03-26 11:55:53	ga_s2bm_ard_3-2-1_50JMN_2024-03-26_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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