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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JFM_2015-10-28_final.stac-item
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KHQ_2015-11-30_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JHN_2016-01-26_final.stac-item
2016-02-05 12:03:44	ga_s2am_ard_3-2-1_49KHQ_2016-02-05_final.stac-item
2016-04-22 11:56:28	ga_s2am_ard_3-2-1_50HNK_2016-04-22_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HQH_2016-05-09_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_49JHM_2016-06-14_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHP_2016-07-14_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2016-09-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2016-10-02_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HMG_2016-11-18_final
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HNG_2016-11-22_final
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2016-12-14_final.stac-item
2017-04-03 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-04-03_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KHQ_2017-04-23_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JHM_2017-05-10_final.stac-item
2017-06-09 12:03:49	ga_s2am_ard_3-2-1_49KHQ_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
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGN_2017-06-29_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KHQ_2017-07-12_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JHM_2017-08-18_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HMH_2017-08-25_final.stac-item
2017-10-20 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2017-10-20_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-11-19_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HQK_2017-11-20_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HQH_2017-12-10_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
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHQ_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
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HMJ_2018-07-11_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-07-17_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2018-08-06_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HQH_2018-08-27_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HQK_2018-10-26_final.stac-item
2018-11-25 11:46:22	ga_s2am_ard_3-2-1_50HQK_2018-11-25_final.stac-item
2018-12-22 11:36:26	ga_s2am_ard_3-2-1_50HQK_2018-12-22_final.stac-item
2019-01-11 11:36:29	ga_s2am_ard_3-2-1_50HQK_2019-01-11_final.stac-item
2019-01-11 11:36:37	ga_s2am_ard_3-2-1_50HQJ_2019-01-11_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 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-05-10_final.stac-item
2019-05-30 12:04:59	ga_s2am_ard_3-2-1_49JHM_2019-05-30_final.stac-item
2019-06-19 12:05:00	ga_s2am_ard_3-2-1_49JHM_2019-06-19_final.stac-item
2019-07-29 12:05:13	ga_s2am_ard_3-2-1_49JFM_2019-07-29_final.stac-item
2019-08-11 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-08-11_final.stac-item
2019-10-20 12:14:24	ga_s2am_ard_3-2-1_49KHP_2019-10-20_final.stac-item
2019-11-30 11:46:53	ga_s2am_ard_3-2-1_50HQH_2019-11-30_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
2020-03-08 12:14:27	ga_s2am_ard_3-2-1_49JHN_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
2020-05-27 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-05-27_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
2020-07-26 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-07-26_final.stac-item
2020-08-02 12:05:03	ga_s2am_ard_3-2-1_49JHM_2020-08-02_final.stac-item
2020-09-05 11:46:58	ga_s2am_ard_3-2-1_50HQH_2020-09-05_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_49KHQ_2020-10-04_final.stac-item
2020-10-04 12:14:22	ga_s2am_ard_3-2-1_49KHP_2020-10-04_final.stac-item
2020-10-14 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-10-14_final.stac-item
2020-11-13 12:14:25	ga_s2am_ard_3-2-1_49KHP_2020-11-13_final.stac-item
2020-11-13 12:14:49	ga_s2am_ard_3-2-1_49JFN_2020-11-13_final.stac-item
2020-12-03 12:14:20	ga_s2am_ard_3-2-1_49KHP_2020-12-03_final.stac-item
2021-01-16 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-01-16_final
2021-01-26 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-01-26_final
2021-02-12 11:46:52	ga_s2am_ard_3-2-1_50HQH_2021-02-12_final.stac-item
2021-03-14 11:46:53	ga_s2am_ard_3-2-1_50HQH_2021-03-14_final.stac-item
2021-03-14 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-03-14_final
2021-05-22 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-05-22_final.stac-item
2021-08-21 11:47:30	ga_s2am_ard_3-2-1_50HLG_2021-08-21_final
2021-09-19 12:14:23	ga_s2am_ard_3-2-1_49KHP_2021-09-19_final.stac-item
2021-09-29 12:14:27	ga_s2am_ard_3-2-1_49KHP_2021-09-29_final.stac-item
2022-01-15 11:36:28	ga_s2am_ard_3-2-1_50HQK_2022-01-15_final.stac-item
2022-02-23 12:04:25	ga_s2am_ard_3-2-1_49KGP_2022-02-23_final.stac-item
2022-06-06 12:14:16	ga_s2am_ard_3-2-1_49KHQ_2022-06-06_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
2022-09-24 12:14:28	ga_s2am_ard_3-2-1_49KHP_2022-09-24_final.stac-item
2022-10-04 12:14:28	ga_s2am_ard_3-2-1_49KHP_2022-10-04_final.stac-item
2022-10-14 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2023-01-03 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-01-03_final
2023-01-23 11:46:49	ga_s2am_ard_3-2-1_50HQH_2023-01-23_final.stac-item
2023-03-03 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-03-03_final
2023-03-04 11:46:50	ga_s2am_ard_3-2-1_50HQH_2023-03-04_final
2023-06-21 12:14:25	ga_s2am_ard_3-2-1_49KHP_2023-06-21_final
2023-07-11 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-07-11_final
2023-07-31 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-07-31_final
2023-08-10 12:14:25	ga_s2am_ard_3-2-1_49KHP_2023-08-10_final
2023-08-30 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-08-30_final
2023-09-19 12:14:24	ga_s2am_ard_3-2-1_49KHP_2023-09-19_final
2023-09-27 11:37:28	ga_s2am_ard_3-2-1_50HNG_2023-09-27_final
2023-09-29 12:14:23	ga_s2am_ard_3-2-1_49KHP_2023-09-29_final
2023-12-12 11:57:17	ga_s2am_ard_3-2-1_50HLG_2023-12-12_final
2024-02-06 12:13:36	ga_s2am_ard_3-2-1_49KHS_2024-02-06_final
2024-03-07 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-07_final
2024-04-17 11:47:30	ga_s2am_ard_3-2-1_50HLG_2024-04-17_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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