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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQJ_2015-12-21_final.stac-item
2016-03-29 12:14:39	ga_s2am_ard_3-2-1_49JGM_2016-03-29_final.stac-item
2016-04-18 12:13:45	ga_s2am_ard_3-2-1_49KHR_2016-04-18_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HMJ_2016-06-18_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2016-06-27_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2016-10-22_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HNG_2016-11-12_final
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KGP_2016-11-21_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HPH_2016-11-22_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KGR_2016-11-24_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HMG_2016-12-15_final
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2017-01-03_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HMK_2017-05-24_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HNJ_2017-07-03_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HMH_2017-08-25_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HMK_2017-08-25_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KGR_2017-11-09_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-02-14_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-02-17_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-02-27_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-02-27_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HMJ_2018-05-19_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-08-13_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKP_2018-08-13_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HMK_2018-08-27_final.stac-item
2018-11-14 12:13:53	ga_s2am_ard_3-2-1_49KGR_2018-11-14_final.stac-item
2018-12-21 12:04:34	ga_s2am_ard_3-2-1_50JKT_2018-12-21_final.stac-item
2018-12-24 12:14:48	ga_s2am_ard_3-2-1_49JGM_2018-12-24_final.stac-item
2018-12-31 12:04:25	ga_s2am_ard_3-2-1_49KGP_2018-12-31_final.stac-item
2019-03-01 12:04:41	ga_s2am_ard_3-2-1_49JGN_2019-03-01_final.stac-item
2019-03-04 12:13:53	ga_s2am_ard_3-2-1_49KGR_2019-03-04_final.stac-item
2019-03-04 12:14:22	ga_s2am_ard_3-2-1_49KGP_2019-03-04_final.stac-item
2019-07-03 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2019-07-03_final.stac-item
2019-08-02 11:46:45	ga_s2am_ard_3-2-1_50HMK_2019-08-02_final.stac-item
2019-08-08 12:04:50	ga_s2am_ard_3-2-1_49JGN_2019-08-08_final.stac-item
2019-08-18 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2019-08-18_final.stac-item
2019-11-09 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-11-09_final.stac-item
2019-11-23 11:56:00	ga_s2am_ard_3-2-1_50JKN_2019-11-23_final.stac-item
2019-11-27 11:37:03	ga_s2am_ard_3-2-1_50HQH_2019-11-27_final.stac-item
2019-12-19 12:13:48	ga_s2am_ard_3-2-1_49KHR_2019-12-19_final.stac-item
2019-12-19 12:13:52	ga_s2am_ard_3-2-1_49KGR_2019-12-19_final.stac-item
2020-01-05 12:04:37	ga_s2am_ard_3-2-1_49JHN_2020-01-05_final.stac-item
2020-02-24 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2020-02-24_final.stac-item
2020-03-05 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2020-03-05_final.stac-item
2020-07-03 12:04:11	ga_s2am_ard_3-2-1_49KHR_2020-07-03_final.stac-item
2020-07-03 12:04:47	ga_s2am_ard_3-2-1_49JHN_2020-07-03_final.stac-item
2020-07-14 11:37:07	ga_s2am_ard_3-2-1_50HQH_2020-07-14_final.stac-item
2020-07-20 11:56:41	ga_s2am_ard_3-2-1_50HMK_2020-07-20_final.stac-item
2020-07-27 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-07-27_final.stac-item
2020-08-12 12:04:48	ga_s2am_ard_3-2-1_50JKT_2020-08-12_final.stac-item
2020-08-19 11:55:52	ga_s2am_ard_3-2-1_50JKP_2020-08-19_final.stac-item
2020-08-23 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2020-08-23_final.stac-item
2020-08-25 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-08-25_final.stac-item
2020-11-20 12:04:02	ga_s2am_ard_3-2-1_49KHR_2020-11-20_final.stac-item
2021-01-06 11:56:26	ga_s2am_ard_3-2-1_50JLL_2021-01-06_final.stac-item
2021-01-06 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-01-06_final
2021-01-10 11:37:07	ga_s2am_ard_3-2-1_50HPH_2021-01-10_final.stac-item
2021-02-08 12:04:42	ga_s2am_ard_3-2-1_50JKT_2021-02-08_final.stac-item
2021-02-28 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2021-02-28_final.stac-item
2021-03-17 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-03-17_final
2021-05-23 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2021-05-23_final.stac-item
2021-05-23 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-05-23_final.stac-item
2021-06-05 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-06-05_final
2021-06-25 11:56:27	ga_s2am_ard_3-2-1_50JLL_2021-06-25_final.stac-item
2021-06-25 11:57:15	ga_s2am_ard_3-2-1_50HLH_2021-06-25_final.stac-item
2021-06-28 12:04:33	ga_s2am_ard_3-2-1_49KGP_2021-06-28_final.stac-item
2021-07-02 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-07-02_final
2021-07-15 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2021-07-15_final.stac-item
2021-08-07 12:04:45	ga_s2am_ard_3-2-1_49JHN_2021-08-07_final.stac-item
2021-08-14 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-14_final.stac-item
2021-08-17 12:04:45	ga_s2am_ard_3-2-1_50JKT_2021-08-17_final.stac-item
2021-08-24 11:57:22	ga_s2am_ard_3-2-1_50HMG_2021-08-24_final
2021-10-07 11:37:31	ga_s2am_ard_3-2-1_50HNG_2021-10-07_final
2021-10-30 11:47:21	ga_s2am_ard_3-2-1_50HPG_2021-10-30_final
2021-10-30 11:47:25	ga_s2am_ard_3-2-1_50HNG_2021-10-30_final
2021-12-29 11:46:55	ga_s2am_ard_3-2-1_50HQH_2021-12-29_final.stac-item
2022-03-09 11:46:57	ga_s2am_ard_3-2-1_50HQH_2022-03-09_final.stac-item
2022-05-17 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-05-17_final.stac-item
2022-06-17 11:46:52	ga_s2am_ard_3-2-1_50HMK_2022-06-17_final.stac-item
2022-12-31 11:37:02	ga_s2am_ard_3-2-1_50HQH_2022-12-31_final.stac-item
2023-02-12 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-02-12_final
2023-02-22 11:47:25	ga_s2am_ard_3-2-1_50HLG_2023-02-22_final
2023-04-23 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-04-23_final
2023-05-23 11:47:13	ga_s2am_ard_3-2-1_50HMH_2023-05-23_final
2023-06-15 11:57:15	ga_s2am_ard_3-2-1_50HMH_2023-06-15_final
2023-08-11 11:47:25	ga_s2am_ard_3-2-1_50HNG_2023-08-11_final
2023-08-21 11:47:33	ga_s2am_ard_3-2-1_50HLG_2023-08-21_final
2023-08-31 11:47:29	ga_s2am_ard_3-2-1_50HMG_2023-08-31_final
2023-11-22 11:57:18	ga_s2am_ard_3-2-1_50HLG_2023-11-22_final
2023-11-25 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-11-25_final
2023-11-29 11:46:54	ga_s2am_ard_3-2-1_50HPH_2023-11-29_final
2024-01-11 11:57:17	ga_s2am_ard_3-2-1_50HLG_2024-01-11_final
2024-02-27 11:47:26	ga_s2am_ard_3-2-1_50HLG_2024-02-27_final
2024-03-01 11:57:22	ga_s2am_ard_3-2-1_50HLG_2024-03-01_final
2024-03-14 12:05:00	ga_s2am_ard_3-2-1_49JGM_2024-03-14_final
2024-04-04 11:37:18	ga_s2am_ard_3-2-1_50HPG_2024-04-04_final
2024-04-07 11:46:56	ga_s2am_ard_3-2-1_50HPH_2024-04-07_final
2024-04-27 11:47:29	ga_s2am_ard_3-2-1_50HLG_2024-04-27_final
2024-05-27 11:47:03	ga_s2am_ard_3-2-1_50HPH_2024-05-27_final
2024-06-06 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2024-06-06_nrt

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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