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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HLG_2015-11-14_final
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KHP_2015-12-30_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49KHP_2016-01-09_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49KHQ_2016-02-08_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HLG_2016-04-02_final
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHP_2016-07-14_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HMH_2016-07-21_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49JHN_2016-08-03_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2016-09-02_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HNG_2016-09-06_final
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_49JHN_2016-09-22_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KHP_2017-03-14_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50HLK_2017-03-18_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_49JHN_2017-04-10_final.stac-item
2017-05-07 11:56:10	ga_s2am_ard_3-2-1_50HMJ_2017-05-07_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JHM_2017-05-10_final.stac-item
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KHQ_2017-05-13_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JGN_2017-06-09_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JHM_2017-06-19_final.stac-item
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49KHP_2017-06-22_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2017-07-09_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KHP_2017-07-12_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KHQ_2017-07-12_final.stac-item
2017-07-19 12:03:48	ga_s2am_ard_3-2-1_49KHQ_2017-07-19_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KHQ_2017-08-01_final.stac-item
2017-11-16 12:04:39	ga_s2am_ard_3-2-1_49JGN_2017-11-16_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JGK_2017-11-26_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49JHM_2018-03-26_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-06-27_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HMH_2018-07-08_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-07-17_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHP_2018-07-27_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2018-08-06_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2018-08-16_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KHQ_2018-08-26_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KHQ_2018-09-25_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KHP_2018-11-04_final.stac-item
2019-01-03 12:14:15	ga_s2am_ard_3-2-1_49KHP_2019-01-03_final.stac-item
2019-03-24 12:14:20	ga_s2am_ard_3-2-1_49KHP_2019-03-24_final.stac-item
2019-04-23 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-04-23_final.stac-item
2019-04-30 12:05:00	ga_s2am_ard_3-2-1_49JHM_2019-04-30_final.stac-item
2019-05-10 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-05-10_final.stac-item
2019-05-10 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-05-10_final.stac-item
2019-05-23 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-05-23_final.stac-item
2019-05-30 12:04:59	ga_s2am_ard_3-2-1_49JHM_2019-05-30_final.stac-item
2019-07-02 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-07-02_final.stac-item
2019-07-29 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-07-29_final.stac-item
2019-08-01 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2019-08-01_final.stac-item
2019-08-11 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-08-11_final.stac-item
2020-02-07 12:14:13	ga_s2am_ard_3-2-1_49KHP_2020-02-07_final.stac-item
2020-02-17 12:14:15	ga_s2am_ard_3-2-1_49KHP_2020-02-17_final.stac-item
2020-03-08 12:14:17	ga_s2am_ard_3-2-1_49KHP_2020-03-08_final.stac-item
2020-04-17 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2020-04-17_final.stac-item
2020-04-17 12:14:21	ga_s2am_ard_3-2-1_49KHP_2020-04-17_final.stac-item
2020-05-07 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2020-05-07_final.stac-item
2020-05-27 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-05-27_final.stac-item
2020-06-06 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-06-06_final.stac-item
2020-07-13 12:05:01	ga_s2am_ard_3-2-1_49JHM_2020-07-13_final.stac-item
2020-07-23 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-07-23_final.stac-item
2020-08-02 12:05:03	ga_s2am_ard_3-2-1_49JHM_2020-08-02_final.stac-item
2020-10-01 12:05:14	ga_s2am_ard_3-2-1_49JFM_2020-10-01_final.stac-item
2020-10-04 12:14:22	ga_s2am_ard_3-2-1_49KHP_2020-10-04_final.stac-item
2021-01-26 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-01-26_final
2021-04-02 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2021-04-02_final.stac-item
2021-05-22 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-05-22_final.stac-item
2021-06-25 11:57:13	ga_s2am_ard_3-2-1_50HMH_2021-06-25_final.stac-item
2021-07-11 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-11_final
2021-09-10 11:47:28	ga_s2am_ard_3-2-1_50HLG_2021-09-10_final
2021-10-30 11:47:32	ga_s2am_ard_3-2-1_50HLG_2021-10-30_final
2021-12-09 11:47:25	ga_s2am_ard_3-2-1_50HLG_2021-12-09_final
2021-12-19 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-12-19_final
2022-02-23 12:04:25	ga_s2am_ard_3-2-1_49KGP_2022-02-23_final.stac-item
2022-05-07 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-05-07_final.stac-item
2022-06-06 12:14:29	ga_s2am_ard_3-2-1_49KHP_2022-06-06_final.stac-item
2022-07-06 12:14:34	ga_s2am_ard_3-2-1_49KHP_2022-07-06_final.stac-item
2022-07-16 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-07-16_final.stac-item
2022-07-26 12:14:31	ga_s2am_ard_3-2-1_49KHP_2022-07-26_final.stac-item
2022-08-05 12:14:32	ga_s2am_ard_3-2-1_49KHP_2022-08-05_final.stac-item
2022-08-25 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-08-25_final
2022-09-24 12:14:28	ga_s2am_ard_3-2-1_49KHP_2022-09-24_final.stac-item
2022-10-14 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2022-11-03 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-11-03_final.stac-item
2022-11-13 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-11-13_final.stac-item
2022-11-23 12:14:21	ga_s2am_ard_3-2-1_49KHP_2022-11-23_final.stac-item
2022-12-03 12:14:21	ga_s2am_ard_3-2-1_49KHP_2022-12-03_final.stac-item
2022-12-13 12:14:21	ga_s2am_ard_3-2-1_49KHP_2022-12-13_final.stac-item
2023-02-21 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-02-21_nrt.stac-item
2023-02-21 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-02-21_final
2023-03-04 11:47:17	ga_s2am_ard_3-2-1_50HNG_2023-03-04_final
2023-03-13 12:14:17	ga_s2am_ard_3-2-1_49KHP_2023-03-13_final
2023-04-12 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-04-12_final
2023-05-02 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-05-02_final
2023-05-06 11:57:20	ga_s2am_ard_3-2-1_50HMG_2023-05-06_final
2023-05-12 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-05-12_final
2023-05-26 11:57:23	ga_s2am_ard_3-2-1_50HMG_2023-05-26_final
2023-06-11 12:14:25	ga_s2am_ard_3-2-1_49KHP_2023-06-11_final
2023-10-09 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-10-09_final
2023-11-29 11:47:20	ga_s2am_ard_3-2-1_50HLG_2023-11-29_final
2024-02-06 12:13:36	ga_s2am_ard_3-2-1_49KHS_2024-02-06_final
2024-03-11 11:57:20	ga_s2am_ard_3-2-1_50HMG_2024-03-11_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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