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_50JKP_2015-10-28_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KGQ_2015-12-30_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HLJ_2016-01-03_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HMG_2016-07-08_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JHM_2016-07-24_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HPJ_2016-10-23_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPH_2016-11-02_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HMG_2016-11-28_final
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50HPK_2017-02-13_final.stac-item
2017-03-21 12:03:40	ga_s2am_ard_3-2-1_49KHR_2017-03-21_final.stac-item
2017-03-24 12:13:37	ga_s2am_ard_3-2-1_49KHR_2017-03-24_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KGQ_2017-04-23_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKN_2017-06-19_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKT_2017-09-17_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHP_2017-09-27_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49KGR_2017-10-10_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HMH_2017-10-24_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JGL_2017-10-27_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HPJ_2017-12-10_final.stac-item
2018-02-07 12:13:40	ga_s2am_ard_3-2-1_49KHR_2018-02-07_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLL_2018-05-22_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JLM_2018-06-11_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLM_2018-06-14_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50HLH_2018-08-10_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HMJ_2018-08-27_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HPJ_2018-08-27_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JGN_2018-09-05_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_50HQH_2018-09-23_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JKQ_2018-10-02_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HPH_2018-10-16_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLM_2018-10-19_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_50HPK_2018-11-02_final.stac-item
2018-11-28 11:56:05	ga_s2am_ard_3-2-1_50JKM_2018-11-28_final.stac-item
2019-01-20 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-20_final.stac-item
2019-02-13 11:47:12	ga_s2am_ard_3-2-1_50HLH_2019-02-13_final.stac-item
2019-03-22 11:36:36	ga_s2am_ard_3-2-1_50HPK_2019-03-22_final.stac-item
2019-10-20 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-10-20_final.stac-item
2019-11-13 11:55:48	ga_s2am_ard_3-2-1_50JKP_2019-11-13_final.stac-item
2019-11-19 12:15:12	ga_s2am_ard_3-2-1_49JGL_2019-11-19_final.stac-item
2019-12-27 11:36:43	ga_s2am_ard_3-2-1_50HQJ_2019-12-27_final.stac-item
2020-01-09 11:47:01	ga_s2am_ard_3-2-1_50HNH_2020-01-09_final.stac-item
2020-02-01 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2020-02-01_final.stac-item
2020-02-04 12:05:47	ga_s2am_ard_3-2-1_50JKN_2020-02-04_final.stac-item
2020-02-17 12:13:48	ga_s2am_ard_3-2-1_49KHR_2020-02-17_final.stac-item
2020-02-24 12:05:59	ga_s2am_ard_3-2-1_50JLM_2020-02-24_final.stac-item
2020-03-05 12:05:25	ga_s2am_ard_3-2-1_49JGK_2020-03-05_final.stac-item
2020-03-05 12:05:36	ga_s2am_ard_3-2-1_50JKP_2020-03-05_final.stac-item
2020-04-15 11:37:02	ga_s2am_ard_3-2-1_50HQH_2020-04-15_final.stac-item
2020-06-23 12:04:10	ga_s2am_ard_3-2-1_49KHR_2020-06-23_final.stac-item
2020-07-27 11:46:39	ga_s2am_ard_3-2-1_50HPK_2020-07-27_final.stac-item
2020-12-20 12:04:41	ga_s2am_ard_3-2-1_49JHN_2020-12-20_final.stac-item
2020-12-23 12:14:55	ga_s2am_ard_3-2-1_49JGM_2020-12-23_final.stac-item
2021-01-03 11:46:30	ga_s2am_ard_3-2-1_50HQK_2021-01-03_final.stac-item
2021-02-25 11:55:46	ga_s2am_ard_3-2-1_50JKP_2021-02-25_final.stac-item
2021-04-10 11:36:29	ga_s2am_ard_3-2-1_50HQK_2021-04-10_final.stac-item
2021-05-03 11:46:35	ga_s2am_ard_3-2-1_50HNK_2021-05-03_final.stac-item
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final.stac-item
2021-06-21 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-06-21_final.stac-item
2021-08-24 11:57:22	ga_s2am_ard_3-2-1_50HMG_2021-08-24_final
2021-08-27 12:05:17	ga_s2am_ard_3-2-1_49JGL_2021-08-27_final.stac-item
2021-09-06 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-09-06_final.stac-item
2021-09-19 12:13:42	ga_s2am_ard_3-2-1_49KHS_2021-09-19_final
2021-12-09 11:46:32	ga_s2am_ard_3-2-1_50HMK_2021-12-09_final.stac-item
2022-01-24 12:04:31	ga_s2am_ard_3-2-1_49KGP_2022-01-24_final.stac-item
2022-02-20 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-02-20_final.stac-item
2022-02-23 12:04:48	ga_s2am_ard_3-2-1_49JGN_2022-02-23_final.stac-item
2022-03-18 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-03-18_final.stac-item
2022-03-28 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final.stac-item
2022-04-14 12:04:45	ga_s2am_ard_3-2-1_50JKT_2022-04-14_final.stac-item
2022-04-18 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2022-04-18_final.stac-item
2022-05-04 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-05-04_final.stac-item
2022-06-06 12:14:35	ga_s2am_ard_3-2-1_49KGP_2022-06-06_final.stac-item
2022-06-24 11:37:15	ga_s2am_ard_3-2-1_50HQH_2022-06-24_final.stac-item
2022-06-27 11:47:19	ga_s2am_ard_3-2-1_50HNH_2022-06-27_final.stac-item
2022-07-04 11:37:01	ga_s2am_ard_3-2-1_50HQJ_2022-07-04_final.stac-item
2022-07-06 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-07-06_final.stac-item
2022-07-10 11:55:59	ga_s2am_ard_3-2-1_50JKP_2022-07-10_final.stac-item
2022-08-26 11:47:29	ga_s2am_ard_3-2-1_50HPG_2022-08-26_final
2022-09-11 12:05:51	ga_s2am_ard_3-2-1_50JKP_2022-09-11_final.stac-item
2022-10-28 11:56:03	ga_s2am_ard_3-2-1_50JKN_2022-10-28_final.stac-item
2022-12-04 11:46:41	ga_s2am_ard_3-2-1_50HMK_2022-12-04_final.stac-item
2022-12-23 12:15:08	ga_s2am_ard_3-2-1_49JGL_2022-12-23_final.stac-item
2023-02-01 12:14:58	ga_s2am_ard_3-2-1_49JFM_2023-02-01_final.stac-item
2023-02-05 11:56:10	ga_s2am_ard_3-2-1_50JLM_2023-02-05_final
2023-02-09 11:37:05	ga_s2am_ard_3-2-1_50HPH_2023-02-09_final.stac-item
2023-04-06 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-04-06_final
2023-04-19 12:05:54	ga_s2am_ard_3-2-1_50JKN_2023-04-19_final
2023-05-12 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-05-12_final
2023-05-23 11:47:27	ga_s2am_ard_3-2-1_50HMG_2023-05-23_final
2023-08-04 11:56:04	ga_s2am_ard_3-2-1_50JKN_2023-08-04_final
2023-08-30 12:14:00	ga_s2am_ard_3-2-1_49KHR_2023-08-30_final
2023-09-19 12:14:30	ga_s2am_ard_3-2-1_49KGP_2023-09-19_final
2023-10-20 11:47:06	ga_s2am_ard_3-2-1_50HNH_2023-10-20_final
2023-10-23 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-10-23_final
2023-12-12 11:55:55	ga_s2am_ard_3-2-1_50JKN_2023-12-12_final
2024-01-31 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2024-01-31_final
2024-02-07 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2024-02-07_final
2024-02-13 12:05:12	ga_s2am_ard_3-2-1_49JGL_2024-02-13_final
2024-03-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2024-03-18_final
2024-04-17 11:47:20	ga_s2am_ard_3-2-1_50HPG_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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