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
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JGM_2015-10-21_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49JGM_2015-12-30_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGK_2016-09-12_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49KHR_2016-10-05_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HLG_2016-11-15_final
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49KGP_2017-01-20_final.stac-item
2017-03-14 12:13:13	ga_s2am_ard_3-2-1_49KHR_2017-03-14_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHR_2017-09-27_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49JHM_2017-10-07_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KHR_2017-11-29_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JGL_2018-01-08_final.stac-item
2018-01-18 12:14:35	ga_s2am_ard_3-2-1_49JFM_2018-01-18_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49JGL_2018-01-28_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HLH_2018-02-01_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-02-14_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50HLJ_2018-02-21_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-03-06_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49JGN_2018-03-16_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGL_2018-04-05_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JGL_2018-06-14_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGL_2018-06-24_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JHN_2018-06-24_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-04_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-08-16_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HLK_2018-09-19_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49JGN_2018-11-04_final.stac-item
2018-11-28 11:56:46	ga_s2am_ard_3-2-1_50HLJ_2018-11-28_final.stac-item
2018-12-24 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-12-24_final.stac-item
2018-12-24 12:15:03	ga_s2am_ard_3-2-1_49JGL_2018-12-24_final.stac-item
2019-01-03 12:14:15	ga_s2am_ard_3-2-1_49KHP_2019-01-03_final.stac-item
2019-01-10 12:04:56	ga_s2am_ard_3-2-1_49JGM_2019-01-10_final.stac-item
2019-01-13 12:14:52	ga_s2am_ard_3-2-1_49JGM_2019-01-13_final.stac-item
2019-02-12 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-02-12_final.stac-item
2019-03-31 12:05:15	ga_s2am_ard_3-2-1_49JGL_2019-03-31_final.stac-item
2019-05-23 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-05-23_final.stac-item
2019-05-23 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-05-23_final.stac-item
2019-08-28 12:04:00	ga_s2am_ard_3-2-1_49KHR_2019-08-28_final.stac-item
2019-10-17 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-10-17_final.stac-item
2019-10-21 11:47:17	ga_s2am_ard_3-2-1_50HLH_2019-10-21_final.stac-item
2019-11-13 11:57:11	ga_s2am_ard_3-2-1_50HLH_2019-11-13_final.stac-item
2019-11-29 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2019-11-29_final.stac-item
2019-12-03 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2019-12-03_final.stac-item
2020-01-15 12:04:55	ga_s2am_ard_3-2-1_49JGM_2020-01-15_final.stac-item
2020-02-14 12:04:54	ga_s2am_ard_3-2-1_49JGM_2020-02-14_final.stac-item
2020-02-24 12:04:55	ga_s2am_ard_3-2-1_49JGM_2020-02-24_final.stac-item
2020-03-28 12:15:06	ga_s2am_ard_3-2-1_49JGL_2020-03-28_final.stac-item
2020-04-01 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2020-04-01_final.stac-item
2020-04-24 12:04:01	ga_s2am_ard_3-2-1_49KHR_2020-04-24_final.stac-item
2020-04-27 12:13:57	ga_s2am_ard_3-2-1_49KHR_2020-04-27_final.stac-item
2020-06-06 12:15:06	ga_s2am_ard_3-2-1_49JFM_2020-06-06_final.stac-item
2020-09-21 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-09-21_final.stac-item
2020-11-13 12:15:03	ga_s2am_ard_3-2-1_49JFM_2020-11-13_final.stac-item
2020-12-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2020-12-30_final.stac-item
2021-02-01 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-02-01_final.stac-item
2021-02-25 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-02-25_final.stac-item
2021-04-29 12:04:28	ga_s2am_ard_3-2-1_49KGP_2021-04-29_final.stac-item
2021-05-12 12:13:54	ga_s2am_ard_3-2-1_49KHR_2021-05-12_final.stac-item
2021-06-18 12:05:17	ga_s2am_ard_3-2-1_49JGL_2021-06-18_final.stac-item
2021-07-31 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-07-31_final
2021-08-20 12:14:29	ga_s2am_ard_3-2-1_49KGP_2021-08-20_final.stac-item
2021-08-21 11:47:30	ga_s2am_ard_3-2-1_50HLG_2021-08-21_final
2021-08-27 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-27_final.stac-item
2021-09-23 11:56:43	ga_s2am_ard_3-2-1_50HLK_2021-09-23_final.stac-item
2021-11-08 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-11-08_final.stac-item
2021-12-15 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-12-15_final.stac-item
2022-01-14 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-01-14_final.stac-item
2022-02-16 12:14:42	ga_s2am_ard_3-2-1_49JGN_2022-02-16_final.stac-item
2022-07-26 12:15:06	ga_s2am_ard_3-2-1_49JGM_2022-07-26_final.stac-item
2022-07-30 11:56:50	ga_s2am_ard_3-2-1_50HLK_2022-07-30_final.stac-item
2022-08-12 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-08-12_final.stac-item
2022-09-14 12:14:51	ga_s2am_ard_3-2-1_49JGN_2022-09-14_final.stac-item
2022-10-31 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-10-31_final.stac-item
2022-11-07 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2022-11-07_final.stac-item
2022-11-30 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-11-30_final.stac-item
2022-11-30 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-11-30_final.stac-item
2023-01-02 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-01-02_final.stac-item
2023-01-12 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-01-12_final.stac-item
2023-01-19 12:03:54	ga_s2am_ard_3-2-1_49KHR_2023-01-19_final.stac-item
2023-02-01 12:14:58	ga_s2am_ard_3-2-1_49JFM_2023-02-01_final.stac-item
2023-02-08 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-02-08_final
2023-02-08 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-02-08_final
2023-03-27 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2023-03-27_final
2023-04-02 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-04-02_final
2023-05-29 12:05:00	ga_s2am_ard_3-2-1_49JHM_2023-05-29_final
2023-07-18 12:03:49	ga_s2am_ard_3-2-1_49KHS_2023-07-18_final
2023-07-28 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-07-28_final
2023-09-06 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-09-06_final
2023-09-16 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-09-16_final
2023-10-13 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-10-13_final
2023-12-02 11:56:47	ga_s2am_ard_3-2-1_50HLJ_2023-12-02_final
2023-12-02 11:57:01	ga_s2am_ard_3-2-1_50HLH_2023-12-02_final
2023-12-25 12:03:56	ga_s2am_ard_3-2-1_49KHR_2023-12-25_final
2024-01-04 12:04:39	ga_s2am_ard_3-2-1_49JHN_2024-01-04_final
2024-01-14 12:04:54	ga_s2am_ard_3-2-1_49JGM_2024-01-14_final
2024-01-31 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2024-01-31_final
2024-02-06 12:13:50	ga_s2am_ard_3-2-1_49KHR_2024-02-06_final
2024-02-07 11:47:10	ga_s2am_ard_3-2-1_50HLH_2024-02-07_final
2024-02-13 12:05:27	ga_s2am_ard_3-2-1_49JGK_2024-02-13_final
2024-02-23 12:04:38	ga_s2am_ard_3-2-1_49JHN_2024-02-23_final
2024-05-06 12:14:44	ga_s2am_ard_3-2-1_49JGN_2024-05-06_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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