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
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JHN_2016-06-24_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49JGN_2016-07-14_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-07-14_final
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_49JGM_2016-08-13_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KGR_2016-11-14_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KHQ_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
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KHR_2017-02-02_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49KHP_2017-02-19_final.stac-item
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HLJ_2017-06-26_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KHR_2017-07-09_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49KHR_2017-11-26_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49KGR_2018-01-08_final.stac-item
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-03-19_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49JGN_2018-05-18_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JHN_2018-06-24_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-06-27_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-07-07_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KGP_2018-07-27_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49JGN_2018-08-03_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JHM_2018-08-13_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGK_2018-08-23_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-10-15_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KHR_2018-11-04_final.stac-item
2018-11-14 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2018-11-14_final.stac-item
2018-11-14 12:14:15	ga_s2am_ard_3-2-1_49KHP_2018-11-14_final.stac-item
2018-11-21 12:05:22	ga_s2am_ard_3-2-1_49JGK_2018-11-21_final.stac-item
2018-12-04 12:13:46	ga_s2am_ard_3-2-1_49KHR_2018-12-04_final.stac-item
2018-12-11 12:04:19	ga_s2am_ard_3-2-1_49KHP_2018-12-11_final.stac-item
2018-12-31 12:04:54	ga_s2am_ard_3-2-1_49JGM_2018-12-31_final.stac-item
2019-01-10 12:04:56	ga_s2am_ard_3-2-1_49JGM_2019-01-10_final.stac-item
2019-01-30 12:04:43	ga_s2am_ard_3-2-1_49JGN_2019-01-30_final.stac-item
2019-02-09 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2019-02-09_final.stac-item
2019-03-01 12:04:23	ga_s2am_ard_3-2-1_49KHP_2019-03-01_final.stac-item
2019-05-23 12:14:24	ga_s2am_ard_3-2-1_49KHP_2019-05-23_final.stac-item
2019-07-09 12:04:36	ga_s2am_ard_3-2-1_49KGP_2019-07-09_final.stac-item
2019-08-15 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2019-08-15_final.stac-item
2019-09-07 12:04:30	ga_s2am_ard_3-2-1_49KGP_2019-09-07_final.stac-item
2019-10-27 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-10-27_final.stac-item
2019-11-09 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-11-09_final.stac-item
2019-11-09 12:15:13	ga_s2am_ard_3-2-1_49JGL_2019-11-09_final.stac-item
2019-11-26 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2019-11-26_final.stac-item
2019-12-09 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-12-09_final.stac-item
2019-12-29 12:14:26	ga_s2am_ard_3-2-1_49JHN_2019-12-29_final.stac-item
2019-12-29 12:14:36	ga_s2am_ard_3-2-1_49JGN_2019-12-29_final.stac-item
2020-01-15 12:04:25	ga_s2am_ard_3-2-1_49KGP_2020-01-15_final.stac-item
2020-02-07 12:14:04	ga_s2am_ard_3-2-1_49KGQ_2020-02-07_final.stac-item
2020-03-08 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2020-03-08_final.stac-item
2020-03-08 12:14:27	ga_s2am_ard_3-2-1_49JHN_2020-03-08_final.stac-item
2020-03-15 12:04:24	ga_s2am_ard_3-2-1_49KHP_2020-03-15_final.stac-item
2020-07-03 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-07-03_final.stac-item
2020-07-30 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-07-30_final.stac-item
2020-11-13 12:14:49	ga_s2am_ard_3-2-1_49JFN_2020-11-13_final.stac-item
2020-12-13 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2020-12-13_final.stac-item
2020-12-23 12:14:55	ga_s2am_ard_3-2-1_49JGM_2020-12-23_final.stac-item
2020-12-30 12:04:42	ga_s2am_ard_3-2-1_49JHN_2020-12-30_final.stac-item
2021-01-09 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-01-09_final.stac-item
2021-02-11 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-02-11_final
2021-03-13 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2021-03-13_final.stac-item
2021-03-13 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-03-13_final.stac-item
2021-04-29 12:04:28	ga_s2am_ard_3-2-1_49KGP_2021-04-29_final.stac-item
2021-06-28 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2021-06-28_final.stac-item
2021-06-28 12:04:29	ga_s2am_ard_3-2-1_49KHP_2021-06-28_final.stac-item
2021-06-28 12:05:02	ga_s2am_ard_3-2-1_49JGM_2021-06-28_final.stac-item
2021-08-20 12:15:13	ga_s2am_ard_3-2-1_49JGL_2021-08-20_final.stac-item
2021-09-26 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-09-26_final
2021-10-19 12:15:01	ga_s2am_ard_3-2-1_49JGM_2021-10-19_final.stac-item
2021-10-26 12:05:34	ga_s2am_ard_3-2-1_49JGK_2021-10-26_final.stac-item
2021-11-05 12:04:35	ga_s2am_ard_3-2-1_49KGP_2021-11-05_final.stac-item
2021-11-15 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2021-11-15_final.stac-item
2021-12-05 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2021-12-05_final.stac-item
2021-12-15 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2021-12-15_final.stac-item
2022-02-13 12:04:31	ga_s2am_ard_3-2-1_49KGP_2022-02-13_final.stac-item
2022-02-13 12:05:29	ga_s2am_ard_3-2-1_49JGK_2022-02-13_final.stac-item
2022-02-16 12:15:00	ga_s2am_ard_3-2-1_49JFM_2022-02-16_final.stac-item
2022-05-14 12:04:39	ga_s2am_ard_3-2-1_49KGP_2022-05-14_final.stac-item
2022-08-05 12:14:38	ga_s2am_ard_3-2-1_49KGP_2022-08-05_final.stac-item
2022-10-01 12:04:42	ga_s2am_ard_3-2-1_49KGP_2022-10-01_final.stac-item
2022-10-24 12:15:02	ga_s2am_ard_3-2-1_49JFM_2022-10-24_final.stac-item
2022-10-31 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-10-31_final.stac-item
2022-11-03 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2022-11-03_final.stac-item
2022-11-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-11-13_final.stac-item
2022-11-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2022-11-23_final.stac-item
2023-01-02 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-01-02_final.stac-item
2023-01-12 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2023-01-12_final.stac-item
2023-03-10 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-03-10_final
2023-03-10 12:04:28	ga_s2am_ard_3-2-1_49JHN_2023-03-10_final
2023-07-02 11:47:31	ga_s2am_ard_3-2-1_50HLG_2023-07-02_final
2023-11-05 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-11-05_final
2023-11-25 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-11-25_final
2023-11-28 12:14:49	ga_s2am_ard_3-2-1_49JGM_2023-11-28_final
2023-12-05 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2023-12-05_final
2024-01-07 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-01-07_final
2024-01-24 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2024-01-24_final
2024-02-03 12:05:25	ga_s2am_ard_3-2-1_49JGK_2024-02-03_final
2024-02-13 12:05:27	ga_s2am_ard_3-2-1_49JGK_2024-02-13_final
2024-02-23 12:04:40	ga_s2am_ard_3-2-1_49JGN_2024-02-23_final
2024-02-23 12:04:46	ga_s2am_ard_3-2-1_49JGN_2024-02-23_final
2024-03-04 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2024-03-04_final
2024-04-13 12:04:33	ga_s2am_ard_3-2-1_49KGP_2024-04-13_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

Other products

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