Search ga_s2am_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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KGR_2015-11-30_final.stac-item
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50HNK_2016-06-21_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGP_2016-06-27_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49JGN_2016-08-26_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KGP_2016-12-04_final.stac-item
2016-12-24 12:14:52	ga_s2am_ard_3-2-1_49JGL_2016-12-24_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HMJ_2017-02-03_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HNJ_2017-05-04_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HNH_2017-06-13_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGP_2017-07-12_final.stac-item
2017-07-22 12:13:45	ga_s2am_ard_3-2-1_49KGR_2017-07-22_final.stac-item
2017-09-30 12:13:18	ga_s2am_ard_3-2-1_49KHR_2017-09-30_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HLK_2017-11-13_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50HMJ_2018-02-21_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49KGP_2018-03-16_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50HLH_2018-06-21_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-07-07_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKN_2018-08-10_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JKN_2018-09-09_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JKN_2018-09-19_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HPJ_2018-10-16_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HQJ_2018-10-26_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-11-01_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_50HQK_2018-11-02_final.stac-item
2018-11-15 11:46:24	ga_s2am_ard_3-2-1_50HQK_2018-11-15_final.stac-item
2018-12-08 11:57:01	ga_s2am_ard_3-2-1_50HLH_2018-12-08_final.stac-item
2019-04-03 12:13:59	ga_s2am_ard_3-2-1_49KGR_2019-04-03_final.stac-item
2019-04-11 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2019-04-11_final.stac-item
2019-04-20 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-04-20_final.stac-item
2019-05-30 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-05-30_final.stac-item
2019-06-02 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-06-02_final.stac-item
2019-06-29 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2019-06-29_final.stac-item
2019-07-02 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2019-07-02_final.stac-item
2019-07-22 12:14:32	ga_s2am_ard_3-2-1_49KGP_2019-07-22_final.stac-item
2019-08-01 12:14:03	ga_s2am_ard_3-2-1_49KGR_2019-08-01_final.stac-item
2019-11-10 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2019-11-10_final.stac-item
2019-12-23 11:57:03	ga_s2am_ard_3-2-1_50HLH_2019-12-23_final.stac-item
2020-01-19 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2020-01-19_final.stac-item
2020-01-28 12:13:47	ga_s2am_ard_3-2-1_49KHR_2020-01-28_final.stac-item
2020-02-01 11:56:41	ga_s2am_ard_3-2-1_50HLJ_2020-02-01_final.stac-item
2020-02-27 12:14:55	ga_s2am_ard_3-2-1_49JFM_2020-02-27_final.stac-item
2020-03-22 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2020-03-22_final.stac-item
2020-03-25 12:05:25	ga_s2am_ard_3-2-1_49JGK_2020-03-25_final.stac-item
2020-07-23 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-07-23_final.stac-item
2020-10-11 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-10-11_final.stac-item
2020-10-24 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-10-24_final.stac-item
2020-10-24 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-10-24_final.stac-item
2020-10-25 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-10-25_final.stac-item
2020-11-24 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2020-11-24_final.stac-item
2020-12-04 11:46:36	ga_s2am_ard_3-2-1_50HNK_2020-12-04_final.stac-item
2020-12-04 11:47:01	ga_s2am_ard_3-2-1_50HPH_2020-12-04_final.stac-item
2020-12-20 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2020-12-20_final.stac-item
2020-12-24 11:46:29	ga_s2am_ard_3-2-1_50HQK_2020-12-24_final.stac-item
2021-02-02 11:47:02	ga_s2am_ard_3-2-1_50HPH_2021-02-02_final.stac-item
2021-02-11 12:14:55	ga_s2am_ard_3-2-1_49JGM_2021-02-11_final.stac-item
2021-02-21 12:13:58	ga_s2am_ard_3-2-1_49KGR_2021-02-21_final.stac-item
2021-02-21 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2021-02-21_final.stac-item
2021-06-15 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-06-15_final.stac-item
2021-06-25 11:57:22	ga_s2am_ard_3-2-1_50HMG_2021-06-25_final
2021-07-28 12:04:26	ga_s2am_ard_3-2-1_49KHP_2021-07-28_final.stac-item
2021-09-03 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-09-03_final.stac-item
2021-10-29 12:14:03	ga_s2am_ard_3-2-1_49KGR_2021-10-29_final.stac-item
2021-11-16 11:36:53	ga_s2am_ard_3-2-1_50HPJ_2021-11-16_final.stac-item
2021-11-28 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-11-28_final.stac-item
2021-12-29 11:46:31	ga_s2am_ard_3-2-1_50HQK_2021-12-29_final.stac-item
2022-01-14 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-01-14_final.stac-item
2022-01-31 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2022-01-31_final.stac-item
2022-02-26 12:13:57	ga_s2am_ard_3-2-1_49KHR_2022-02-26_final.stac-item
2022-02-26 12:14:44	ga_s2am_ard_3-2-1_49JGN_2022-02-26_final.stac-item
2022-03-09 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2022-03-09_final.stac-item
2022-03-22 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2022-03-22_final.stac-item
2022-04-25 11:36:41	ga_s2am_ard_3-2-1_50HQK_2022-04-25_final.stac-item
2022-08-19 11:56:12	ga_s2am_ard_3-2-1_50JKN_2022-08-19_final.stac-item
2022-10-08 11:56:06	ga_s2am_ard_3-2-1_50JKN_2022-10-08_final.stac-item
2022-10-14 12:14:03	ga_s2am_ard_3-2-1_49KGR_2022-10-14_final.stac-item
2022-12-13 12:14:41	ga_s2am_ard_3-2-1_49JGN_2022-12-13_final.stac-item
2022-12-30 12:05:28	ga_s2am_ard_3-2-1_49JGK_2022-12-30_final.stac-item
2023-04-03 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-04-03_final
2023-04-09 12:04:34	ga_s2am_ard_3-2-1_49KHP_2023-04-09_final
2023-05-02 12:14:27	ga_s2am_ard_3-2-1_49KGP_2023-05-02_final
2023-05-29 12:04:50	ga_s2am_ard_3-2-1_49JGN_2023-05-29_final
2023-06-12 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2023-06-12_final
2023-07-08 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-07-08_final
2023-07-21 12:13:58	ga_s2am_ard_3-2-1_49KHR_2023-07-21_final
2023-08-10 12:13:59	ga_s2am_ard_3-2-1_49KHR_2023-08-10_final
2023-08-21 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2023-08-21_final
2023-10-13 11:57:20	ga_s2am_ard_3-2-1_50HLG_2023-10-13_final
2023-10-16 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2023-10-16_final
2023-12-16 11:36:30	ga_s2am_ard_3-2-1_50HQK_2023-12-16_final
2024-01-07 12:13:54	ga_s2am_ard_3-2-1_49KGR_2024-01-07_final
2024-02-06 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-02-06_final
2024-02-07 11:46:34	ga_s2am_ard_3-2-1_50HPK_2024-02-07_final
2024-02-14 11:37:00	ga_s2am_ard_3-2-1_50HQH_2024-02-14_final
2024-02-17 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2024-02-17_final
2024-02-27 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2024-02-27_final
2024-03-11 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2024-03-11_final
2024-03-18 11:46:38	ga_s2am_ard_3-2-1_50HNK_2024-03-18_final
2024-03-18 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2024-03-18_final
2024-03-25 11:37:22	ga_s2am_ard_3-2-1_50HPG_2024-03-25_final
2024-05-07 11:47:05	ga_s2am_ard_3-2-1_50HPH_2024-05-07_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

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