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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_49KGP_2015-10-08_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49JHN_2016-03-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGK_2016-04-15_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2016-09-12_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JHN_2016-10-12_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGN_2016-11-21_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49JGM_2016-12-21_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49JGM_2017-01-30_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49JHN_2017-03-31_final.stac-item
2017-08-11 12:14:43	ga_s2am_ard_3-2-1_49JGM_2017-08-11_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49KGP_2017-09-07_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49KGP_2017-10-10_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGL_2017-12-16_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JHN_2018-01-08_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49JGN_2018-01-28_final.stac-item
2019-03-24 12:14:25	ga_s2am_ard_3-2-1_49KGP_2019-03-24_final.stac-item
2019-04-20 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-04-20_final.stac-item
2019-05-03 12:15:00	ga_s2am_ard_3-2-1_49JGM_2019-05-03_final.stac-item
2019-05-03 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-05-03_final.stac-item
2019-05-10 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-05-10_final.stac-item
2019-06-09 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-06-09_final.stac-item
2019-06-22 12:14:45	ga_s2am_ard_3-2-1_49JGN_2019-06-22_final.stac-item
2019-07-22 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-22_final.stac-item
2019-07-29 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-07-29_final.stac-item
2019-07-29 12:04:51	ga_s2am_ard_3-2-1_49JGN_2019-07-29_final.stac-item
2019-08-18 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-08-18_final.stac-item
2019-09-07 12:05:28	ga_s2am_ard_3-2-1_49JGK_2019-09-07_final.stac-item
2019-10-27 12:05:12	ga_s2am_ard_3-2-1_49JFM_2019-10-27_final.stac-item
2019-10-30 12:15:00	ga_s2am_ard_3-2-1_49JFM_2019-10-30_final.stac-item
2019-11-06 12:04:59	ga_s2am_ard_3-2-1_49JHM_2019-11-06_final.stac-item
2019-11-06 12:05:18	ga_s2am_ard_3-2-1_49JGL_2019-11-06_final.stac-item
2019-12-19 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-12-19_final.stac-item
2020-01-28 12:14:34	ga_s2am_ard_3-2-1_49JGN_2020-01-28_final.stac-item
2020-02-07 12:14:19	ga_s2am_ard_3-2-1_49KGP_2020-02-07_final.stac-item
2020-02-27 12:14:36	ga_s2am_ard_3-2-1_49JGN_2020-02-27_final.stac-item
2020-03-15 12:04:53	ga_s2am_ard_3-2-1_49JHM_2020-03-15_final.stac-item
2020-05-04 12:05:00	ga_s2am_ard_3-2-1_49JHM_2020-05-04_final.stac-item
2020-05-07 12:15:00	ga_s2am_ard_3-2-1_49JGM_2020-05-07_final.stac-item
2020-05-27 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-05-27_final.stac-item
2020-07-23 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-07-23_final.stac-item
2020-08-05 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-08-05_final.stac-item
2020-08-22 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-08-22_final.stac-item
2020-09-01 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-09-01_final.stac-item
2020-10-31 12:04:47	ga_s2am_ard_3-2-1_49JHN_2020-10-31_final.stac-item
2020-11-03 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-11-03_final.stac-item
2020-11-10 12:04:46	ga_s2am_ard_3-2-1_49JHN_2020-11-10_final.stac-item
2020-12-03 12:15:09	ga_s2am_ard_3-2-1_49JGL_2020-12-03_final.stac-item
2020-12-23 12:14:55	ga_s2am_ard_3-2-1_49JGM_2020-12-23_final.stac-item
2021-02-18 12:04:56	ga_s2am_ard_3-2-1_49JHM_2021-02-18_final.stac-item
2021-10-26 12:05:02	ga_s2am_ard_3-2-1_49JHM_2021-10-26_final.stac-item
2021-11-05 12:04:50	ga_s2am_ard_3-2-1_49JGN_2021-11-05_final.stac-item
2021-12-05 12:04:56	ga_s2am_ard_3-2-1_49JHM_2021-12-05_final.stac-item
2022-01-17 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-01-17_final.stac-item
2022-02-13 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-02-13_final.stac-item
2022-02-16 12:14:57	ga_s2am_ard_3-2-1_49JGM_2022-02-16_final.stac-item
2022-02-23 12:04:48	ga_s2am_ard_3-2-1_49JGN_2022-02-23_final.stac-item
2022-03-28 12:14:21	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final.stac-item
2022-04-14 12:04:49	ga_s2am_ard_3-2-1_49JGN_2022-04-14_final.stac-item
2022-05-07 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-05-07_final.stac-item
2022-05-24 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-05-24_final.stac-item
2022-06-13 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-06-13_final.stac-item
2022-06-23 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-06-23_final.stac-item
2022-06-26 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-06-26_final.stac-item
2022-07-03 12:04:59	ga_s2am_ard_3-2-1_49JGN_2022-07-03_final.stac-item
2022-09-01 12:04:55	ga_s2am_ard_3-2-1_49JHN_2022-09-01_final.stac-item
2022-09-11 12:04:53	ga_s2am_ard_3-2-1_49JHN_2022-09-11_final.stac-item
2022-11-03 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-11-03_final.stac-item
2022-11-20 12:04:47	ga_s2am_ard_3-2-1_49JGN_2022-11-20_final.stac-item
2022-12-10 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-12-10_final.stac-item
2023-01-02 12:14:40	ga_s2am_ard_3-2-1_49JGN_2023-01-02_final.stac-item
2023-01-19 12:04:41	ga_s2am_ard_3-2-1_49JGN_2023-01-19_final.stac-item
2023-02-08 12:04:41	ga_s2am_ard_3-2-1_49JHN_2023-02-08_final
2023-03-03 12:14:53	ga_s2am_ard_3-2-1_49JGM_2023-03-03_final
2023-04-19 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-04-19_final
2023-05-09 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-05-09_final
2023-05-19 12:04:59	ga_s2am_ard_3-2-1_49JHM_2023-05-19_final
2023-07-08 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-07-08_final
2023-08-17 12:04:52	ga_s2am_ard_3-2-1_49JGN_2023-08-17_final
2023-08-17 12:05:35	ga_s2am_ard_3-2-1_49JGK_2023-08-17_final
2023-08-27 12:05:03	ga_s2am_ard_3-2-1_49JHM_2023-08-27_final
2023-08-30 12:14:32	ga_s2am_ard_3-2-1_49KGP_2023-08-30_final
2023-09-16 12:04:46	ga_s2am_ard_3-2-1_49JHN_2023-09-16_final
2023-09-16 12:04:50	ga_s2am_ard_3-2-1_49JGN_2023-09-16_final
2023-10-06 12:04:47	ga_s2am_ard_3-2-1_49JGN_2023-10-06_final
2023-10-06 12:04:58	ga_s2am_ard_3-2-1_49JHM_2023-10-06_final
2023-10-09 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-10-09_final
2023-10-09 12:14:56	ga_s2am_ard_3-2-1_49JGM_2023-10-09_final
2023-11-08 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-11-08_final
2023-11-15 12:04:55	ga_s2am_ard_3-2-1_49JHM_2023-11-15_final
2023-11-28 12:15:03	ga_s2am_ard_3-2-1_49JGL_2023-11-28_final
2023-12-05 12:04:54	ga_s2am_ard_3-2-1_49JGM_2023-12-05_final
2023-12-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-12-25_final
2024-01-04 12:04:53	ga_s2am_ard_3-2-1_49JHM_2024-01-04_final
2024-01-07 12:14:52	ga_s2am_ard_3-2-1_49JGM_2024-01-07_final
2024-01-17 12:15:02	ga_s2am_ard_3-2-1_49JGL_2024-01-17_final
2024-04-06 12:14:29	ga_s2am_ard_3-2-1_49JHN_2024-04-06_final
2024-04-16 12:15:02	ga_s2am_ard_3-2-1_49JFM_2024-04-16_final
2024-05-03 12:04:49	ga_s2am_ard_3-2-1_49JGN_2024-05-03_final
2024-05-13 12:04:34	ga_s2am_ard_3-2-1_49KGP_2024-05-13_final
2024-05-23 12:05:00	ga_s2am_ard_3-2-1_49JGM_2024-05-23_nrt

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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