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
2017-09-19 11:55:56	ga_s2bm_ard_3-2-1_50JLM_2017-09-19_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50HMH_2017-12-28_final.stac-item
2018-01-20 12:02:42	ga_s2bm_ard_3-2-1_50JKQ_2018-01-20_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50HMJ_2018-01-27_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50JKT_2018-03-11_final.stac-item
2018-05-04 11:43:41	ga_s2bm_ard_3-2-1_50HQJ_2018-05-04_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50JML_2018-05-14_final.stac-item
2018-06-16 11:51:10	ga_s2bm_ard_3-2-1_50JLM_2018-06-16_final
2018-07-20 11:35:23	ga_s2bm_ard_3-2-1_50HPK_2018-07-20_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50HQH_2018-09-11_final.stac-item
2019-01-09 11:47:05	ga_s2bm_ard_3-2-1_50HNH_2019-01-09_final.stac-item
2019-01-12 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2019-01-12_final.stac-item
2019-03-03 11:56:06	ga_s2bm_ard_3-2-1_50JMM_2019-03-03_final.stac-item
2019-03-26 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2019-03-26_final.stac-item
2019-04-09 11:46:30	ga_s2bm_ard_3-2-1_50JML_2019-04-09_final.stac-item
2019-05-29 11:46:42	ga_s2bm_ard_3-2-1_50HPK_2019-05-29_final.stac-item
2019-06-18 11:46:34	ga_s2bm_ard_3-2-1_50JML_2019-06-18_final.stac-item
2019-08-07 11:47:17	ga_s2bm_ard_3-2-1_50HMH_2019-08-07_final.stac-item
2019-09-02 12:05:00	ga_s2bm_ard_3-2-1_50JKS_2019-09-02_final.stac-item
2019-09-13 11:37:03	ga_s2bm_ard_3-2-1_50HQH_2019-09-13_final.stac-item
2019-09-16 11:46:26	ga_s2bm_ard_3-2-1_50JML_2019-09-16_final.stac-item
2019-11-15 11:46:25	ga_s2bm_ard_3-2-1_50JML_2019-11-15_final.stac-item
2019-11-15 11:47:05	ga_s2bm_ard_3-2-1_50HNH_2019-11-15_final.stac-item
2019-12-11 12:05:32	ga_s2bm_ard_3-2-1_50JLP_2019-12-11_final.stac-item
2020-02-13 11:47:02	ga_s2bm_ard_3-2-1_50HNH_2020-02-13_final.stac-item
2020-02-20 11:36:48	ga_s2bm_ard_3-2-1_50HPJ_2020-02-20_final.stac-item
2020-02-29 12:05:23	ga_s2bm_ard_3-2-1_50JKQ_2020-02-29_final.stac-item
2020-03-24 11:46:24	ga_s2bm_ard_3-2-1_50JML_2020-03-24_final.stac-item
2020-03-24 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2020-03-24_final.stac-item
2020-04-22 12:14:07	ga_s2bm_ard_3-2-1_49KGQ_2020-04-22_final.stac-item
2020-05-09 12:05:20	ga_s2bm_ard_3-2-1_49JGK_2020-05-09_final.stac-item
2020-05-10 11:37:05	ga_s2bm_ard_3-2-1_50HPH_2020-05-10_final.stac-item
2020-05-13 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2020-05-13_final.stac-item
2020-06-05 11:56:10	ga_s2bm_ard_3-2-1_50JMM_2020-06-05_final.stac-item
2020-06-08 12:05:40	ga_s2bm_ard_3-2-1_50JLP_2020-06-08_final.stac-item
2020-07-22 11:46:15	ga_s2bm_ard_3-2-1_50JMM_2020-07-22_final.stac-item
2020-09-03 11:56:39	ga_s2bm_ard_3-2-1_50HMK_2020-09-03_final.stac-item
2020-11-02 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2020-11-02_final.stac-item
2020-11-12 11:55:43	ga_s2bm_ard_3-2-1_50JLP_2020-11-12_final.stac-item
2020-11-12 11:55:57	ga_s2bm_ard_3-2-1_50JLN_2020-11-12_final.stac-item
2020-11-12 11:56:26	ga_s2bm_ard_3-2-1_50JML_2020-11-12_final.stac-item
2020-12-02 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2020-12-02_final.stac-item
2020-12-22 11:55:38	ga_s2bm_ard_3-2-1_50JLP_2020-12-22_final.stac-item
2021-01-14 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2021-01-14_final.stac-item
2021-01-21 11:56:14	ga_s2bm_ard_3-2-1_50JKM_2021-01-21_final.stac-item
2021-03-15 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2021-03-15_final.stac-item
2021-04-17 12:14:08	ga_s2bm_ard_3-2-1_49KGQ_2021-04-17_final.stac-item
2021-05-24 12:04:54	ga_s2bm_ard_3-2-1_50JLS_2021-05-24_final.stac-item
2021-06-13 12:04:49	ga_s2bm_ard_3-2-1_50JKT_2021-06-13_final.stac-item
2021-06-23 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2021-06-23_final.stac-item
2021-08-12 12:04:23	ga_s2bm_ard_3-2-1_49KGQ_2021-08-12_final.stac-item
2021-10-15 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2021-10-15_final.stac-item
2021-10-15 11:46:39	ga_s2bm_ard_3-2-1_50HNK_2021-10-15_final.stac-item
2021-12-07 11:57:01	ga_s2bm_ard_3-2-1_50HMH_2021-12-07_final.stac-item
2022-01-03 11:46:30	ga_s2bm_ard_3-2-1_50HPK_2022-01-03_final.stac-item
2022-02-22 11:46:46	ga_s2bm_ard_3-2-1_50HNJ_2022-02-22_final.stac-item
2022-03-17 11:57:04	ga_s2bm_ard_3-2-1_50HMH_2022-03-17_final.stac-item
2022-04-16 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2022-04-16_final.stac-item
2022-04-30 11:37:00	ga_s2bm_ard_3-2-1_50HPH_2022-04-30_final.stac-item
2022-07-12 11:46:30	ga_s2bm_ard_3-2-1_50JML_2022-07-12_final.stac-item
2022-08-17 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2022-08-17_final.stac-item
2022-08-21 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2022-08-21_final.stac-item
2022-10-09 12:14:11	ga_s2bm_ard_3-2-1_49KGQ_2022-10-09_final.stac-item
2022-10-13 11:55:45	ga_s2bm_ard_3-2-1_50JKP_2022-10-13_final.stac-item
2022-11-05 12:04:26	ga_s2bm_ard_3-2-1_49KHP_2022-11-05_final.stac-item
2022-11-05 12:04:55	ga_s2bm_ard_3-2-1_49JHM_2022-11-05_final.stac-item
2022-11-29 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2022-11-29_final.stac-item
2022-12-02 11:55:51	ga_s2bm_ard_3-2-1_50JMN_2022-12-02_final.stac-item
2022-12-02 11:56:49	ga_s2bm_ard_3-2-1_50HMJ_2022-12-02_final.stac-item
2022-12-19 11:46:47	ga_s2bm_ard_3-2-1_50HPJ_2022-12-19_final.stac-item
2022-12-22 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2022-12-22_final.stac-item
2023-01-04 12:04:16	ga_s2bm_ard_3-2-1_49KGQ_2023-01-04_final.stac-item
2023-01-28 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2023-01-28_final.stac-item
2023-01-28 11:47:18	ga_s2bm_ard_3-2-1_50HNG_2023-01-28_final
2023-02-03 12:04:52	ga_s2bm_ard_3-2-1_49JGM_2023-02-03_final.stac-item
2023-03-29 11:46:33	ga_s2bm_ard_3-2-1_50HQK_2023-03-29_final
2023-04-17 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2023-04-17_final
2023-05-01 11:56:10	ga_s2bm_ard_3-2-1_50JMM_2023-05-01_final
2023-05-14 12:04:43	ga_s2bm_ard_3-2-1_50JLT_2023-05-14_final
2023-06-27 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2023-06-27_final
2023-07-10 11:56:16	ga_s2bm_ard_3-2-1_50JLM_2023-07-10_final
2023-07-24 11:36:40	ga_s2bm_ard_3-2-1_50HQK_2023-07-24_final
2023-08-19 11:56:27	ga_s2bm_ard_3-2-1_50JML_2023-08-19_final
2023-08-23 11:37:22	ga_s2bm_ard_3-2-1_50HQG_2023-08-23_final
2023-09-01 12:04:51	ga_s2bm_ard_3-2-1_49JGN_2023-09-01_final
2023-10-11 12:04:44	ga_s2bm_ard_3-2-1_50JKT_2023-10-11_final
2023-10-22 11:37:08	ga_s2bm_ard_3-2-1_50HPH_2023-10-22_final
2023-10-24 12:13:59	ga_s2bm_ard_3-2-1_49KGR_2023-10-24_final
2023-11-10 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2023-11-10_final
2023-11-24 11:46:25	ga_s2bm_ard_3-2-1_50HQK_2023-11-24_final
2023-12-17 11:56:22	ga_s2bm_ard_3-2-1_50JML_2023-12-17_final
2024-01-16 11:56:21	ga_s2bm_ard_3-2-1_50JML_2024-01-16_final
2024-01-30 11:37:00	ga_s2bm_ard_3-2-1_50HQH_2024-01-30_final
2024-02-11 12:15:12	ga_s2bm_ard_3-2-1_49JGL_2024-02-11_final
2024-03-16 11:56:06	ga_s2bm_ard_3-2-1_50JMM_2024-03-16_final
2024-03-29 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2024-03-29_final
2024-04-02 11:46:55	ga_s2bm_ard_3-2-1_50HNJ_2024-04-02_final
2024-04-05 11:56:06	ga_s2bm_ard_3-2-1_50JMM_2024-04-05_final
2024-04-08 12:04:17	ga_s2bm_ard_3-2-1_49KGQ_2024-04-08_final
2024-05-11 12:15:11	ga_s2bm_ard_3-2-1_49JGL_2024-05-11_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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