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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50HMK_2015-12-04_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50HLJ_2016-03-03_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JKP_2016-04-02_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HQK_2016-10-26_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLH_2016-10-29_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2016-11-21_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HMG_2016-12-08_final
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JKP_2016-12-11_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50JKP_2017-01-20_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HPK_2017-03-05_final.stac-item
2017-04-01 11:34:45	ga_s2am_ard_3-2-1_50HPH_2017-04-01_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HNH_2017-05-04_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49KGP_2017-06-02_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HNJ_2017-06-13_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JFM_2017-09-30_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49KHR_2018-01-05_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49KHR_2018-03-26_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HNK_2018-05-19_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JKN_2018-05-22_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HQJ_2018-05-29_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KGP_2018-06-17_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HMH_2018-06-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HMK_2018-07-18_final.stac-item
2018-11-18 11:56:34	ga_s2am_ard_3-2-1_50HLK_2018-11-18_final.stac-item
2018-12-01 12:04:52	ga_s2am_ard_3-2-1_49JGM_2018-12-01_final.stac-item
2018-12-02 11:36:43	ga_s2am_ard_3-2-1_50HPJ_2018-12-02_final.stac-item
2019-01-04 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2019-01-04_final.stac-item
2019-02-23 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2019-02-23_final.stac-item
2019-03-25 11:46:29	ga_s2am_ard_3-2-1_50HQK_2019-03-25_final.stac-item
2019-04-10 12:04:33	ga_s2am_ard_3-2-1_49KGP_2019-04-10_final.stac-item
2019-04-24 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-04-24_final.stac-item
2019-05-24 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-05-24_final.stac-item
2019-06-03 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2019-06-03_final.stac-item
2019-08-18 12:05:58	ga_s2am_ard_3-2-1_50JKN_2019-08-18_final.stac-item
2019-09-01 11:47:07	ga_s2am_ard_3-2-1_50HNH_2019-09-01_final.stac-item
2019-09-08 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2019-09-08_final.stac-item
2019-10-28 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2019-10-28_final.stac-item
2019-11-07 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2019-11-07_final.stac-item
2019-12-07 11:36:31	ga_s2am_ard_3-2-1_50HQK_2019-12-07_final.stac-item
2019-12-19 12:13:48	ga_s2am_ard_3-2-1_49KHR_2019-12-19_final.stac-item
2019-12-23 11:55:54	ga_s2am_ard_3-2-1_50JKN_2019-12-23_final.stac-item
2019-12-29 12:14:54	ga_s2am_ard_3-2-1_49JFM_2019-12-29_final.stac-item
2020-01-05 12:05:35	ga_s2am_ard_3-2-1_50JKP_2020-01-05_final.stac-item
2020-01-19 11:46:27	ga_s2am_ard_3-2-1_50HPK_2020-01-19_final.stac-item
2020-01-28 12:14:49	ga_s2am_ard_3-2-1_49JGM_2020-01-28_final.stac-item
2020-01-29 11:46:26	ga_s2am_ard_3-2-1_50HPK_2020-01-29_final.stac-item
2020-02-07 12:13:50	ga_s2am_ard_3-2-1_49KGR_2020-02-07_final.stac-item
2020-04-04 12:04:14	ga_s2am_ard_3-2-1_49KGQ_2020-04-04_final.stac-item
2020-05-21 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-05-21_final.stac-item
2020-06-03 12:04:13	ga_s2am_ard_3-2-1_49KHR_2020-06-03_final.stac-item
2020-07-07 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2020-07-07_final.stac-item
2020-08-15 12:15:06	ga_s2am_ard_3-2-1_49JFM_2020-08-15_final.stac-item
2020-09-15 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2020-09-15_final.stac-item
2020-11-20 12:05:58	ga_s2am_ard_3-2-1_50JKN_2020-11-20_final.stac-item
2020-11-27 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2020-11-27_final.stac-item
2020-12-20 12:04:59	ga_s2am_ard_3-2-1_49JGM_2020-12-20_final.stac-item
2021-01-19 12:04:32	ga_s2am_ard_3-2-1_49KGP_2021-01-19_final.stac-item
2021-01-26 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-01-26_final
2021-02-11 12:14:25	ga_s2am_ard_3-2-1_49KGP_2021-02-11_final.stac-item
2021-02-15 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2021-02-15_final.stac-item
2021-05-06 11:56:35	ga_s2am_ard_3-2-1_50HMK_2021-05-06_final.stac-item
2021-05-20 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2021-05-20_final.stac-item
2021-05-20 11:37:11	ga_s2am_ard_3-2-1_50HQG_2021-05-20_final
2021-05-30 11:36:35	ga_s2am_ard_3-2-1_50HQK_2021-05-30_final.stac-item
2021-07-25 11:56:40	ga_s2am_ard_3-2-1_50HMK_2021-07-25_final.stac-item
2021-09-10 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2021-09-10_final.stac-item
2021-09-26 12:04:31	ga_s2am_ard_3-2-1_49KHP_2021-09-26_final.stac-item
2021-10-06 12:04:36	ga_s2am_ard_3-2-1_49KGP_2021-10-06_final.stac-item
2021-10-10 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2021-10-10_final.stac-item
2021-10-17 11:37:12	ga_s2am_ard_3-2-1_50HPH_2021-10-17_final.stac-item
2021-12-09 11:46:31	ga_s2am_ard_3-2-1_50HNK_2021-12-09_final.stac-item
2022-01-08 11:46:49	ga_s2am_ard_3-2-1_50HPJ_2022-01-08_final.stac-item
2022-01-18 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2022-01-18_final.stac-item
2022-02-07 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-02-07_final.stac-item
2022-04-04 12:04:29	ga_s2am_ard_3-2-1_49KHP_2022-04-04_final.stac-item
2022-04-28 11:47:15	ga_s2am_ard_3-2-1_50HMH_2022-04-28_final.stac-item
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-05-24_final.stac-item
2022-10-21 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-10-21_final.stac-item
2022-10-21 12:05:42	ga_s2am_ard_3-2-1_50JKP_2022-10-21_final.stac-item
2022-10-31 12:05:33	ga_s2am_ard_3-2-1_49JGK_2022-10-31_final.stac-item
2022-11-14 11:46:40	ga_s2am_ard_3-2-1_50HNK_2022-11-14_final.stac-item
2022-11-20 12:05:42	ga_s2am_ard_3-2-1_50JKP_2022-11-20_final.stac-item
2023-02-08 12:05:54	ga_s2am_ard_3-2-1_50JKN_2023-02-08_final
2023-05-02 12:13:55	ga_s2am_ard_3-2-1_49KHR_2023-05-02_final
2023-05-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2023-05-02_final
2023-06-01 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-06-01_final
2023-07-22 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-07-22_final
2023-11-18 12:14:39	ga_s2am_ard_3-2-1_49JGN_2023-11-18_final
2023-11-19 11:46:31	ga_s2am_ard_3-2-1_50HPK_2023-11-19_final
2023-11-25 12:05:38	ga_s2am_ard_3-2-1_49JGJ_2023-11-25_final
2023-11-28 12:14:49	ga_s2am_ard_3-2-1_49JGM_2023-11-28_final
2023-12-09 11:46:32	ga_s2am_ard_3-2-1_50HNK_2023-12-09_final
2023-12-26 11:37:04	ga_s2am_ard_3-2-1_50HPH_2023-12-26_final
2024-01-04 12:05:11	ga_s2am_ard_3-2-1_49JGL_2024-01-04_final
2024-01-04 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2024-01-04_final
2024-01-18 11:46:57	ga_s2am_ard_3-2-1_50HNH_2024-01-18_final
2024-02-20 11:57:20	ga_s2am_ard_3-2-1_50HLG_2024-02-20_final
2024-03-04 12:04:32	ga_s2am_ard_3-2-1_49KGP_2024-03-04_final
2024-03-24 12:04:29	ga_s2am_ard_3-2-1_49KHP_2024-03-24_final
2024-03-27 12:13:55	ga_s2am_ard_3-2-1_49KHR_2024-03-27_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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