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
2016-04-22 11:56:28	ga_s2am_ard_3-2-1_50HLK_2016-04-22_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-07-14_final
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHP_2016-11-11_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HMH_2017-01-24_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HMH_2017-02-03_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HLH_2017-03-05_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49JGN_2017-03-31_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_49JGK_2017-04-30_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JHM_2017-06-09_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50HMK_2017-06-26_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JGL_2017-09-30_final.stac-item
2017-10-20 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2017-10-20_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JHN_2017-12-16_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_49JHM_2017-12-26_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HMH_2018-02-01_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HLK_2018-03-03_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50HLK_2018-03-23_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50HMK_2018-03-23_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JGL_2018-04-28_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JGK_2018-05-15_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_50HQK_2018-06-25_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2018-07-04_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HMJ_2018-07-28_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGK_2018-08-13_final.stac-item
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KGR_2018-09-25_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KHR_2018-09-25_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMK_2018-10-16_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HQK_2018-10-16_final.stac-item
2018-12-01 12:04:37	ga_s2am_ard_3-2-1_49JGN_2018-12-01_final.stac-item
2019-01-10 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2019-01-10_final.stac-item
2019-01-13 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2019-01-13_final.stac-item
2019-02-03 11:46:38	ga_s2am_ard_3-2-1_50HMK_2019-02-03_final.stac-item
2019-02-09 12:04:43	ga_s2am_ard_3-2-1_49JGN_2019-02-09_final.stac-item
2019-03-02 11:36:29	ga_s2am_ard_3-2-1_50HQK_2019-03-02_final.stac-item
2019-03-21 12:04:44	ga_s2am_ard_3-2-1_49JGN_2019-03-21_final.stac-item
2019-04-20 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-04-20_final.stac-item
2019-07-06 11:56:45	ga_s2am_ard_3-2-1_50HLK_2019-07-06_final.stac-item
2019-08-28 12:05:30	ga_s2am_ard_3-2-1_49JGK_2019-08-28_final.stac-item
2019-10-10 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-10-10_final.stac-item
2019-10-27 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-10-27_final.stac-item
2019-12-13 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-12-13_final.stac-item
2019-12-30 11:46:35	ga_s2am_ard_3-2-1_50HMK_2019-12-30_final.stac-item
2020-01-26 11:36:27	ga_s2am_ard_3-2-1_50HQK_2020-01-26_final.stac-item
2020-02-01 11:56:39	ga_s2am_ard_3-2-1_50HMJ_2020-02-01_final.stac-item
2020-02-18 11:46:38	ga_s2am_ard_3-2-1_50HMK_2020-02-18_final.stac-item
2020-03-09 11:47:09	ga_s2am_ard_3-2-1_50HMH_2020-03-09_final.stac-item
2020-04-14 12:05:28	ga_s2am_ard_3-2-1_49JGK_2020-04-14_final.stac-item
2020-04-17 12:15:00	ga_s2am_ard_3-2-1_49JFM_2020-04-17_final.stac-item
2020-04-24 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2020-04-24_final.stac-item
2020-05-14 12:05:34	ga_s2am_ard_3-2-1_49JGK_2020-05-14_final.stac-item
2020-07-23 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2020-07-23_final.stac-item
2020-07-27 11:47:15	ga_s2am_ard_3-2-1_50HMH_2020-07-27_final.stac-item
2020-09-15 11:46:45	ga_s2am_ard_3-2-1_50HMK_2020-09-15_final.stac-item
2020-10-01 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-10-01_final.stac-item
2020-10-11 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-10-11_final.stac-item
2020-12-24 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2020-12-24_final.stac-item
2021-01-09 12:05:27	ga_s2am_ard_3-2-1_50JKQ_2021-01-09_final.stac-item
2021-01-26 11:56:37	ga_s2am_ard_3-2-1_50HMK_2021-01-26_final.stac-item
2021-01-26 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-01-26_final.stac-item
2021-01-30 11:36:35	ga_s2am_ard_3-2-1_50HQK_2021-01-30_final.stac-item
2021-03-14 11:47:20	ga_s2am_ard_3-2-1_50HNG_2021-03-14_final
2021-04-23 11:47:06	ga_s2am_ard_3-2-1_50HMH_2021-04-23_final.stac-item
2021-07-01 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-07-01_final.stac-item
2021-07-02 11:47:30	ga_s2am_ard_3-2-1_50HLG_2021-07-02_final
2021-07-11 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-11_final
2021-08-04 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-04_final.stac-item
2021-08-14 11:56:39	ga_s2am_ard_3-2-1_50HMK_2021-08-14_final.stac-item
2021-08-24 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-08-24_final.stac-item
2021-10-26 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2021-10-26_final.stac-item
2021-12-09 11:47:13	ga_s2am_ard_3-2-1_50HLH_2021-12-09_final.stac-item
2021-12-26 11:36:35	ga_s2am_ard_3-2-1_50HQK_2021-12-26_final.stac-item
2022-01-17 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-01-17_final.stac-item
2022-03-06 11:36:40	ga_s2am_ard_3-2-1_50HQK_2022-03-06_final.stac-item
2022-05-21 11:56:43	ga_s2am_ard_3-2-1_50HMK_2022-05-21_final.stac-item
2022-06-27 11:46:53	ga_s2am_ard_3-2-1_50HMK_2022-06-27_final.stac-item
2022-08-13 11:36:46	ga_s2am_ard_3-2-1_50HQK_2022-08-13_final.stac-item
2022-09-11 12:05:40	ga_s2am_ard_3-2-1_49JGK_2022-09-11_final.stac-item
2022-10-04 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-10-04_final.stac-item
2022-10-04 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-10-04_final.stac-item
2022-10-15 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-10-15_final.stac-item
2022-11-27 11:56:40	ga_s2am_ard_3-2-1_50HLK_2022-11-27_final.stac-item
2023-01-22 12:14:17	ga_s2am_ard_3-2-1_49KHP_2023-01-22_final.stac-item
2023-01-30 11:37:15	ga_s2am_ard_3-2-1_50HQG_2023-01-30_final
2023-02-18 12:04:53	ga_s2am_ard_3-2-1_49JHM_2023-02-18_nrt.stac-item
2023-02-18 12:04:53	ga_s2am_ard_3-2-1_49JHM_2023-02-18_final
2023-02-28 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2023-02-28_final
2023-03-10 12:04:21	ga_s2am_ard_3-2-1_49KHP_2023-03-10_final
2023-03-10 12:04:41	ga_s2am_ard_3-2-1_49JGN_2023-03-10_final
2023-03-14 11:47:11	ga_s2am_ard_3-2-1_50HLH_2023-03-14_final
2023-05-26 11:57:09	ga_s2am_ard_3-2-1_50HMH_2023-05-26_final
2023-07-02 11:47:25	ga_s2am_ard_3-2-1_50HNG_2023-07-02_final
2023-07-12 11:47:32	ga_s2am_ard_3-2-1_50HLG_2023-07-12_final
2023-10-23 11:56:26	ga_s2am_ard_3-2-1_50HMK_2023-10-23_final
2023-12-05 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2023-12-05_final
2023-12-05 12:04:50	ga_s2am_ard_3-2-1_49JHM_2023-12-05_final
2024-01-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2024-01-04_final
2024-02-27 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2024-02-27_final
2024-03-21 11:57:07	ga_s2am_ard_3-2-1_50HMH_2024-03-21_final
2024-03-28 11:47:24	ga_s2am_ard_3-2-1_50HMG_2024-03-28_final
2024-04-26 12:15:12	ga_s2am_ard_3-2-1_49JGL_2024-04-26_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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