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
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KHQ_2016-03-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KHR_2016-03-16_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNH_2016-03-20_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLP_2016-04-02_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KGQ_2016-04-15_final.stac-item
2016-04-15 12:05:35	ga_s2am_ard_3-2-1_50JLP_2016-04-15_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JKS_2016-07-24_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KGR_2016-08-26_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HMJ_2016-09-06_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HQK_2016-11-12_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-12-11_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50HNK_2017-01-07_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JKN_2017-02-16_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50HNK_2017-03-08_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JLM_2017-03-11_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JHN_2017-05-10_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JGM_2017-08-18_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49KHR_2017-10-17_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_49JGN_2017-11-06_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HPJ_2017-11-20_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_50JKS_2018-01-05_final.stac-item
2018-01-25 12:02:44	ga_s2am_ard_3-2-1_49KHR_2018-01-25_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-02-27_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JLN_2018-03-23_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50HNJ_2018-04-09_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JML_2018-05-02_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50HPH_2018-05-16_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGN_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHM_2018-07-14_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HQJ_2018-07-15_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HNJ_2018-08-27_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-25_final.stac-item
2018-12-04 12:14:47	ga_s2am_ard_3-2-1_49JGM_2018-12-04_final.stac-item
2019-01-07 11:55:51	ga_s2am_ard_3-2-1_50JLN_2019-01-07_final.stac-item
2019-04-27 11:56:03	ga_s2am_ard_3-2-1_50JKN_2019-04-27_final.stac-item
2019-07-22 12:15:05	ga_s2am_ard_3-2-1_49JFM_2019-07-22_final.stac-item
2019-08-21 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-08-21_final.stac-item
2019-08-29 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2019-08-29_final.stac-item
2019-10-04 11:55:55	ga_s2am_ard_3-2-1_50JMN_2019-10-04_final.stac-item
2019-10-24 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2019-10-24_final.stac-item
2019-11-06 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-11-06_final.stac-item
2019-11-16 12:05:02	ga_s2am_ard_3-2-1_49JGM_2019-11-16_final.stac-item
2019-11-23 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2019-11-23_final.stac-item
2019-11-26 12:05:41	ga_s2am_ard_3-2-1_50JKP_2019-11-26_final.stac-item
2020-02-01 11:56:00	ga_s2am_ard_3-2-1_50JMM_2020-02-01_final.stac-item
2020-02-08 11:46:29	ga_s2am_ard_3-2-1_50HNK_2020-02-08_final.stac-item
2020-02-24 12:04:52	ga_s2am_ard_3-2-1_50JKS_2020-02-24_final.stac-item
2020-04-18 11:47:07	ga_s2am_ard_3-2-1_50HNH_2020-04-18_final.stac-item
2020-06-26 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-06-26_final.stac-item
2020-07-04 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2020-07-04_final.stac-item
2020-10-01 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-10-01_final.stac-item
2020-10-02 11:36:40	ga_s2am_ard_3-2-1_50HQK_2020-10-02_final.stac-item
2020-10-05 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-05_final.stac-item
2020-12-17 11:55:44	ga_s2am_ard_3-2-1_50JKP_2020-12-17_final.stac-item
2021-02-15 11:56:24	ga_s2am_ard_3-2-1_50JLL_2021-02-15_final.stac-item
2021-03-17 11:55:55	ga_s2am_ard_3-2-1_50JLN_2021-03-17_final.stac-item
2021-03-20 12:05:36	ga_s2am_ard_3-2-1_50JKP_2021-03-20_final.stac-item
2021-04-23 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2021-04-23_final.stac-item
2021-05-20 11:37:13	ga_s2am_ard_3-2-1_50HPH_2021-05-20_final.stac-item
2021-05-23 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2021-05-23_final.stac-item
2021-06-05 11:56:26	ga_s2am_ard_3-2-1_50JLL_2021-06-05_final.stac-item
2021-06-28 12:04:44	ga_s2am_ard_3-2-1_49JHN_2021-06-28_final.stac-item
2021-07-05 11:55:49	ga_s2am_ard_3-2-1_50JKP_2021-07-05_final.stac-item
2021-08-17 12:05:32	ga_s2am_ard_3-2-1_49JGK_2021-08-17_final.stac-item
2021-09-03 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-03_final.stac-item
2021-09-07 11:37:13	ga_s2am_ard_3-2-1_50HPH_2021-09-07_final.stac-item
2021-09-13 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-09-13_final.stac-item
2021-10-10 11:47:07	ga_s2am_ard_3-2-1_50HPH_2021-10-10_final.stac-item
2022-02-06 12:13:54	ga_s2am_ard_3-2-1_49KHR_2022-02-06_final.stac-item
2022-02-06 12:15:19	ga_s2am_ard_3-2-1_49JGK_2022-02-06_final.stac-item
2022-05-05 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-05-05_final.stac-item
2022-08-05 12:14:38	ga_s2am_ard_3-2-1_49KGP_2022-08-05_final.stac-item
2022-09-01 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-09-01_final.stac-item
2022-09-11 12:05:08	ga_s2am_ard_3-2-1_50JKS_2022-09-11_final.stac-item
2022-09-21 12:04:50	ga_s2am_ard_3-2-1_49JHN_2022-09-21_final.stac-item
2022-10-15 11:46:42	ga_s2am_ard_3-2-1_50HNK_2022-10-15_final.stac-item
2022-11-20 12:05:38	ga_s2am_ard_3-2-1_50JLP_2022-11-20_final.stac-item
2023-01-09 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-01-09_final.stac-item
2023-03-07 11:57:19	ga_s2am_ard_3-2-1_50HLG_2023-03-07_final
2023-03-13 12:14:38	ga_s2am_ard_3-2-1_49JGN_2023-03-13_final
2023-04-03 11:46:25	ga_s2am_ard_3-2-1_50JML_2023-04-03_final
2023-04-22 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-04-22_final
2023-06-12 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2023-06-12_final
2023-08-14 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2023-08-14_final
2023-08-28 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2023-08-28_final
2023-09-06 12:05:02	ga_s2am_ard_3-2-1_50JKS_2023-09-06_final
2023-09-07 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2023-09-07_final
2023-09-16 12:06:08	ga_s2am_ard_3-2-1_50JLM_2023-09-16_final
2023-09-23 11:55:44	ga_s2am_ard_3-2-1_50JLP_2023-09-23_final
2023-10-06 12:04:29	ga_s2am_ard_3-2-1_49KHP_2023-10-06_final
2023-10-30 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2023-10-30_final
2023-11-19 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2023-11-19_final
2023-12-22 11:56:22	ga_s2am_ard_3-2-1_50JLL_2023-12-22_final
2024-01-04 12:04:24	ga_s2am_ard_3-2-1_49KHP_2024-01-04_final
2024-01-17 12:13:46	ga_s2am_ard_3-2-1_49KHR_2024-01-17_final
2024-02-06 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-02-06_final
2024-02-10 11:56:10	ga_s2am_ard_3-2-1_50JKM_2024-02-10_final
2024-02-10 11:56:26	ga_s2am_ard_3-2-1_50HNK_2024-02-10_final
2024-03-08 11:47:03	ga_s2am_ard_3-2-1_50HPH_2024-03-08_final
2024-03-31 11:56:10	ga_s2am_ard_3-2-1_50JLM_2024-03-31_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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