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
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_49JGK_2017-07-14_final.stac-item
2017-09-05 12:14:35	ga_s2bm_ard_3-2-1_49JGL_2017-09-05_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLM_2017-11-01_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50HMH_2017-11-08_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JLR_2017-12-18_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_49KHP_2017-12-21_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50HMH_2017-12-25_final.stac-item
2018-01-10 12:02:41	ga_s2bm_ard_3-2-1_49KHP_2018-01-10_final.stac-item
2018-01-27 11:50:39	ga_s2bm_ard_3-2-1_50JNL_2018-01-27_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50JML_2018-01-27_final.stac-item
2018-01-30 12:02:42	ga_s2bm_ard_3-2-1_50JLT_2018-01-30_final.stac-item
2018-02-03 11:40:42	ga_s2bm_ard_3-2-1_50JNL_2018-02-03_final.stac-item
2018-02-06 11:49:12	ga_s2bm_ard_3-2-1_50HLK_2018-02-06_final.stac-item
2018-02-16 11:54:55	ga_s2bm_ard_3-2-1_50JMN_2018-02-16_final.stac-item
2018-03-12 11:35:28	ga_s2bm_ard_3-2-1_50HQK_2018-03-12_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50JLP_2018-03-18_final.stac-item
2018-03-21 12:02:43	ga_s2bm_ard_3-2-1_49JGN_2018-03-21_final.stac-item
2018-05-04 11:43:41	ga_s2bm_ard_3-2-1_50HNJ_2018-05-04_final.stac-item
2018-05-04 11:43:41	ga_s2bm_ard_3-2-1_50HPH_2018-05-04_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50HQK_2018-05-11_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JKT_2018-05-20_final.stac-item
2018-05-21 11:31:10	ga_s2bm_ard_3-2-1_50HPH_2018-05-21_final.stac-item
2018-06-29 12:02:48	ga_s2bm_ard_3-2-1_49JGK_2018-06-29_final.stac-item
2018-08-25 11:52:52	ga_s2bm_ard_3-2-1_50JMN_2018-08-25_final.stac-item
2018-12-10 11:47:08	ga_s2bm_ard_3-2-1_50HLH_2018-12-10_final.stac-item
2018-12-13 11:56:59	ga_s2bm_ard_3-2-1_50HMH_2018-12-13_final.stac-item
2018-12-23 11:57:01	ga_s2bm_ard_3-2-1_50HMH_2018-12-23_final.stac-item
2019-01-05 12:04:26	ga_s2bm_ard_3-2-1_49KHP_2019-01-05_final.stac-item
2019-03-23 11:55:42	ga_s2bm_ard_3-2-1_50JLP_2019-03-23_final.stac-item
2019-04-09 11:46:56	ga_s2bm_ard_3-2-1_50HNJ_2019-04-09_final.stac-item
2019-06-11 11:56:37	ga_s2bm_ard_3-2-1_50HNK_2019-06-11_final.stac-item
2019-10-19 11:54:46	ga_s2bm_ard_3-2-1_50JLT_2019-10-19_final.stac-item
2019-10-19 11:56:19	ga_s2bm_ard_3-2-1_50JNL_2019-10-19_final.stac-item
2019-10-29 11:54:45	ga_s2bm_ard_3-2-1_50JLT_2019-10-29_final.stac-item
2019-11-11 12:04:56	ga_s2bm_ard_3-2-1_49JHM_2019-11-11_final.stac-item
2019-11-25 11:47:06	ga_s2bm_ard_3-2-1_50HMH_2019-11-25_final.stac-item
2019-12-21 12:04:41	ga_s2bm_ard_3-2-1_49JGN_2019-12-21_final.stac-item
2019-12-21 12:05:59	ga_s2bm_ard_3-2-1_50JLM_2019-12-21_final.stac-item
2019-12-31 12:04:41	ga_s2bm_ard_3-2-1_49JGN_2019-12-31_final.stac-item
2020-01-07 11:55:48	ga_s2bm_ard_3-2-1_50JMN_2020-01-07_final.stac-item
2020-01-17 11:55:47	ga_s2bm_ard_3-2-1_50JMN_2020-01-17_final.stac-item
2020-02-03 11:46:19	ga_s2bm_ard_3-2-1_50JML_2020-02-03_final.stac-item
2020-06-05 11:55:44	ga_s2bm_ard_3-2-1_50JLP_2020-06-05_final.stac-item
2020-06-25 11:55:44	ga_s2bm_ard_3-2-1_50JLP_2020-06-25_final.stac-item
2020-07-05 11:56:53	ga_s2bm_ard_3-2-1_50HMJ_2020-07-05_final.stac-item
2020-07-08 12:05:39	ga_s2bm_ard_3-2-1_50JLP_2020-07-08_final.stac-item
2020-11-22 11:55:42	ga_s2bm_ard_3-2-1_50JLP_2020-11-22_final.stac-item
2020-11-25 12:04:14	ga_s2bm_ard_3-2-1_49KHQ_2020-11-25_final.stac-item
2020-12-12 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2020-12-12_final.stac-item
2020-12-22 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2020-12-22_final.stac-item
2020-12-29 11:46:53	ga_s2bm_ard_3-2-1_50HMJ_2020-12-29_final.stac-item
2021-01-01 11:54:53	ga_s2bm_ard_3-2-1_50JMS_2021-01-01_final.stac-item
2021-01-21 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2021-01-21_final.stac-item
2021-05-01 11:54:54	ga_s2bm_ard_3-2-1_50JLS_2021-05-01_final.stac-item
2021-05-01 11:55:38	ga_s2bm_ard_3-2-1_50JLP_2021-05-01_final.stac-item
2021-05-15 11:37:25	ga_s2bm_ard_3-2-1_50HNG_2021-05-15_final
2021-08-15 12:14:09	ga_s2bm_ard_3-2-1_49KHQ_2021-08-15_final.stac-item
2021-10-01 12:04:17	ga_s2bm_ard_3-2-1_49KGQ_2021-10-01_final.stac-item
2021-10-11 12:06:05	ga_s2bm_ard_3-2-1_50JLM_2021-10-11_final.stac-item
2021-11-27 11:56:06	ga_s2bm_ard_3-2-1_50JLM_2021-11-27_final.stac-item
2022-01-26 11:55:36	ga_s2bm_ard_3-2-1_50JLP_2022-01-26_final.stac-item
2022-01-26 11:56:16	ga_s2bm_ard_3-2-1_50JML_2022-01-26_final.stac-item
2022-02-09 11:37:01	ga_s2bm_ard_3-2-1_50HPH_2022-02-09_final.stac-item
2022-02-22 11:46:25	ga_s2bm_ard_3-2-1_50HQK_2022-02-22_final.stac-item
2022-03-17 11:56:49	ga_s2bm_ard_3-2-1_50HMJ_2022-03-17_final.stac-item
2022-03-30 12:04:10	ga_s2bm_ard_3-2-1_49KHQ_2022-03-30_final.stac-item
2022-04-23 11:46:46	ga_s2bm_ard_3-2-1_50HNJ_2022-04-23_final.stac-item
2022-05-16 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2022-05-16_final.stac-item
2022-05-26 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2022-05-26_final.stac-item
2022-07-12 11:47:00	ga_s2bm_ard_3-2-1_50HMJ_2022-07-12_final.stac-item
2022-09-23 11:55:43	ga_s2bm_ard_3-2-1_50JLP_2022-09-23_final.stac-item
2022-11-15 12:04:57	ga_s2bm_ard_3-2-1_50JKS_2022-11-15_final.stac-item
2022-12-19 11:46:29	ga_s2bm_ard_3-2-1_50HQK_2022-12-19_final.stac-item
2023-01-31 11:55:39	ga_s2bm_ard_3-2-1_50JLP_2023-01-31_final.stac-item
2023-02-13 12:03:43	ga_s2bm_ard_3-2-1_49KHS_2023-02-13_final
2023-02-24 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2023-02-24_final
2023-03-06 11:36:37	ga_s2bm_ard_3-2-1_50HQK_2023-03-06_final
2023-03-12 11:55:46	ga_s2bm_ard_3-2-1_50JLP_2023-03-12_final
2023-04-28 11:46:14	ga_s2bm_ard_3-2-1_50JMM_2023-04-28_final
2023-05-04 12:04:21	ga_s2bm_ard_3-2-1_49KGQ_2023-05-04_final
2023-05-04 12:05:14	ga_s2bm_ard_3-2-1_50JKR_2023-05-04_final
2023-05-08 11:46:32	ga_s2bm_ard_3-2-1_50HQK_2023-05-08_final
2023-08-06 11:47:19	ga_s2bm_ard_3-2-1_50HLH_2023-08-06_final
2023-10-31 12:04:20	ga_s2bm_ard_3-2-1_49KGQ_2023-10-31_final
2023-11-10 12:05:28	ga_s2bm_ard_3-2-1_50JKQ_2023-11-10_final
2023-11-17 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2023-11-17_final
2023-12-07 11:55:39	ga_s2bm_ard_3-2-1_50JLP_2023-12-07_final
2023-12-14 11:46:11	ga_s2bm_ard_3-2-1_50JMM_2023-12-14_final
2023-12-30 12:05:13	ga_s2bm_ard_3-2-1_50JKR_2023-12-30_final
2024-01-06 11:55:41	ga_s2bm_ard_3-2-1_50JLP_2024-01-06_final
2024-01-13 11:46:28	ga_s2bm_ard_3-2-1_50HQK_2024-01-13_final
2024-01-20 11:36:51	ga_s2bm_ard_3-2-1_50HPJ_2024-01-20_final
2024-02-15 11:55:54	ga_s2bm_ard_3-2-1_50JMN_2024-02-15_final
2024-02-22 11:46:13	ga_s2bm_ard_3-2-1_50JMM_2024-02-22_final
2024-02-22 11:47:10	ga_s2bm_ard_3-2-1_50HMH_2024-02-22_final
2024-03-10 11:36:29	ga_s2bm_ard_3-2-1_50HQK_2024-03-10_final
2024-04-02 11:46:11	ga_s2bm_ard_3-2-1_50JMM_2024-04-02_final
2024-04-05 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2024-04-05_final
2024-04-18 12:04:19	ga_s2bm_ard_3-2-1_49KGQ_2024-04-18_final
2024-04-18 12:06:11	ga_s2bm_ard_3-2-1_50JKM_2024-04-18_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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