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
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JGM_2015-12-07_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50HLJ_2016-05-22_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_50HPJ_2016-08-24_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49KHR_2016-10-05_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHR_2016-11-11_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49JGM_2017-01-03_final.stac-item
2017-01-13 12:14:33	ga_s2am_ard_3-2-1_49JGM_2017-01-13_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49JGM_2017-10-07_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HQJ_2017-11-07_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49JGN_2017-11-09_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HMJ_2017-12-03_final.stac-item
2017-12-06 12:03:42	ga_s2am_ard_3-2-1_49KHR_2017-12-06_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-02-14_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HPJ_2018-03-17_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_50HPH_2018-05-26_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_50HQJ_2018-06-25_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50HQJ_2018-10-03_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50HLJ_2018-10-19_final.stac-item
2019-01-13 12:14:52	ga_s2am_ard_3-2-1_49JGM_2019-01-13_final.stac-item
2019-02-13 11:47:12	ga_s2am_ard_3-2-1_50HLH_2019-02-13_final.stac-item
2019-03-14 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-03-14_final.stac-item
2019-03-31 12:05:01	ga_s2am_ard_3-2-1_49JGM_2019-03-31_final.stac-item
2019-04-14 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2019-04-14_final.stac-item
2019-04-14 11:47:09	ga_s2am_ard_3-2-1_50HNH_2019-04-14_final.stac-item
2019-05-11 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-05-11_final.stac-item
2019-06-13 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-06-13_final.stac-item
2019-06-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final.stac-item
2019-07-09 12:05:20	ga_s2am_ard_3-2-1_49JGL_2019-07-09_final.stac-item
2019-09-01 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2019-09-01_final.stac-item
2019-10-27 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-10-27_final.stac-item
2019-10-31 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-10-31_final.stac-item
2019-11-09 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-11-09_final.stac-item
2019-11-26 12:05:15	ga_s2am_ard_3-2-1_49JGL_2019-11-26_final.stac-item
2019-11-29 12:14:55	ga_s2am_ard_3-2-1_49JGM_2019-11-29_final.stac-item
2019-12-16 12:04:55	ga_s2am_ard_3-2-1_49JGM_2019-12-16_final.stac-item
2020-01-12 11:56:49	ga_s2am_ard_3-2-1_50HLJ_2020-01-12_final.stac-item
2020-01-25 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2020-01-25_final.stac-item
2020-01-29 11:47:07	ga_s2am_ard_3-2-1_50HLH_2020-01-29_final.stac-item
2020-02-18 11:46:30	ga_s2am_ard_3-2-1_50HNK_2020-02-18_final.stac-item
2020-04-01 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-04-01_final.stac-item
2020-05-01 11:56:17	ga_s2am_ard_3-2-1_50JKM_2020-05-01_final.stac-item
2020-05-21 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-05-21_final.stac-item
2020-05-28 11:46:40	ga_s2am_ard_3-2-1_50HPK_2020-05-28_final.stac-item
2020-07-17 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-07-17_final.stac-item
2020-08-12 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-08-12_final.stac-item
2020-08-23 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-08-23_final.stac-item
2020-10-08 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-10-08_final.stac-item
2020-11-13 12:13:58	ga_s2am_ard_3-2-1_49KHR_2020-11-13_final.stac-item
2020-12-10 12:05:11	ga_s2am_ard_3-2-1_49JGL_2020-12-10_final.stac-item
2020-12-13 12:14:57	ga_s2am_ard_3-2-1_49JFM_2020-12-13_final.stac-item
2021-02-28 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-02-28_final.stac-item
2021-03-20 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-03-20_final.stac-item
2021-05-06 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2021-05-06_final.stac-item
2021-05-23 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2021-05-23_final.stac-item
2021-06-25 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-06-25_final.stac-item
2021-07-25 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2021-07-25_final.stac-item
2021-07-31 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-07-31_final.stac-item
2021-08-11 11:47:05	ga_s2am_ard_3-2-1_50HPH_2021-08-11_final.stac-item
2021-11-15 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-11-15_final.stac-item
2021-11-25 12:05:29	ga_s2am_ard_3-2-1_49JGK_2021-11-25_final.stac-item
2021-12-15 12:05:29	ga_s2am_ard_3-2-1_49JGK_2021-12-15_final.stac-item
2021-12-22 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2021-12-22_final.stac-item
2022-01-17 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-01-17_final.stac-item
2022-02-03 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-03_final.stac-item
2022-02-03 12:06:10	ga_s2am_ard_3-2-1_50JKM_2022-02-03_final.stac-item
2022-03-05 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-03-05_final.stac-item
2022-04-28 11:46:39	ga_s2am_ard_3-2-1_50HPK_2022-04-28_final.stac-item
2022-05-05 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-05_final.stac-item
2022-06-07 11:47:10	ga_s2am_ard_3-2-1_50HPH_2022-06-07_final.stac-item
2022-06-30 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-06-30_final.stac-item
2022-07-26 12:14:05	ga_s2am_ard_3-2-1_49KHR_2022-07-26_final.stac-item
2022-08-06 11:47:13	ga_s2am_ard_3-2-1_50HPH_2022-08-06_final.stac-item
2022-08-13 11:37:04	ga_s2am_ard_3-2-1_50HPJ_2022-08-13_final.stac-item
2022-09-11 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2022-09-11_final.stac-item
2022-09-25 11:46:50	ga_s2am_ard_3-2-1_50HQJ_2022-09-25_final.stac-item
2022-10-05 11:46:55	ga_s2am_ard_3-2-1_50HPJ_2022-10-05_final.stac-item
2022-10-18 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2022-10-18_final.stac-item
2022-10-31 12:05:33	ga_s2am_ard_3-2-1_49JGK_2022-10-31_final.stac-item
2022-11-20 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-11-20_final.stac-item
2023-02-18 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-02-18_nrt.stac-item
2023-02-18 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-02-18_final
2023-04-03 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-04-03_final
2023-06-02 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-06-02_final
2023-07-12 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-07-12_final
2023-08-17 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-08-17_final
2023-08-17 12:05:35	ga_s2am_ard_3-2-1_49JGK_2023-08-17_final
2023-09-16 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-09-16_final
2023-11-05 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-11-05_final
2023-11-06 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2023-11-06_final
2023-11-25 12:04:37	ga_s2am_ard_3-2-1_49JHN_2023-11-25_final
2023-11-25 12:05:38	ga_s2am_ard_3-2-1_49JGJ_2023-11-25_final
2023-12-02 11:56:58	ga_s2am_ard_3-2-1_50HMH_2023-12-02_final
2023-12-12 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2023-12-12_final
2024-01-28 11:47:05	ga_s2am_ard_3-2-1_50HMH_2024-01-28_final
2024-02-06 12:14:52	ga_s2am_ard_3-2-1_49JGM_2024-02-06_final
2024-02-06 12:14:56	ga_s2am_ard_3-2-1_49JFM_2024-02-06_final
2024-02-07 11:46:30	ga_s2am_ard_3-2-1_50HNK_2024-02-07_final
2024-02-13 12:05:27	ga_s2am_ard_3-2-1_49JGK_2024-02-13_final
2024-02-16 12:14:25	ga_s2am_ard_3-2-1_49KGP_2024-02-16_final
2024-04-23 12:05:18	ga_s2am_ard_3-2-1_49JGL_2024-04-23_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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