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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHS_2015-10-28_final.stac-item
2016-01-19 12:15:17	ga_s2am_ard_3-2-1_49JGM_2016-01-19_final.stac-item
2016-03-06 12:03:43	ga_s2am_ard_3-2-1_49KHR_2016-03-06_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGP_2016-06-27_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JGK_2016-08-23_final.stac-item
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49JGN_2016-11-04_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JGN_2016-11-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KHR_2016-11-24_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLG_2016-11-28_final
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KHR_2016-12-04_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49KGP_2017-04-20_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50HLK_2017-05-27_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGM_2017-07-09_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JHM_2017-07-09_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50HLH_2017-08-25_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KHQ_2017-11-09_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JGM_2017-11-26_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2018-03-16_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-04_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-07-07_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HLK_2018-07-11_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49KGP_2018-08-03_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-08-06_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49KHP_2018-08-16_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50HMH_2018-08-20_final.stac-item
2018-11-24 12:14:34	ga_s2am_ard_3-2-1_49JGN_2018-11-24_final.stac-item
2018-12-14 12:14:33	ga_s2am_ard_3-2-1_49JGN_2018-12-14_final.stac-item
2018-12-31 12:04:25	ga_s2am_ard_3-2-1_49KGP_2018-12-31_final.stac-item
2019-01-10 12:04:41	ga_s2am_ard_3-2-1_49JGN_2019-01-10_final.stac-item
2019-03-01 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2019-03-01_final.stac-item
2019-03-01 12:04:26	ga_s2am_ard_3-2-1_49KGP_2019-03-01_final.stac-item
2019-03-04 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-03-04_final.stac-item
2019-07-09 12:04:51	ga_s2am_ard_3-2-1_49JGN_2019-07-09_final.stac-item
2019-07-09 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-09_final.stac-item
2019-08-08 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-08-08_final.stac-item
2019-08-08 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-08-08_final.stac-item
2019-08-15 11:56:43	ga_s2am_ard_3-2-1_50HLK_2019-08-15_final.stac-item
2019-08-21 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-08-21_final.stac-item
2019-08-21 12:14:23	ga_s2am_ard_3-2-1_49KHP_2019-08-21_final.stac-item
2019-08-25 11:57:11	ga_s2am_ard_3-2-1_50HLH_2019-08-25_final.stac-item
2019-10-20 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-10-20_final.stac-item
2019-10-27 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-10-27_final.stac-item
2019-11-06 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-11-06_final.stac-item
2019-11-16 12:04:44	ga_s2am_ard_3-2-1_49JHN_2019-11-16_final.stac-item
2019-11-19 12:15:12	ga_s2am_ard_3-2-1_49JGL_2019-11-19_final.stac-item
2019-12-19 12:13:52	ga_s2am_ard_3-2-1_49KGR_2019-12-19_final.stac-item
2019-12-19 12:14:21	ga_s2am_ard_3-2-1_49KGP_2019-12-19_final.stac-item
2019-12-29 12:13:53	ga_s2am_ard_3-2-1_49KGR_2019-12-29_final.stac-item
2020-01-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2020-01-08_final.stac-item
2020-03-15 12:04:39	ga_s2am_ard_3-2-1_49JHN_2020-03-15_final.stac-item
2020-03-15 12:04:42	ga_s2am_ard_3-2-1_49JGN_2020-03-15_final.stac-item
2020-05-18 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-05-18_final.stac-item
2020-07-03 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2020-07-03_final.stac-item
2020-07-13 12:04:36	ga_s2am_ard_3-2-1_49KGP_2020-07-13_final.stac-item
2020-08-12 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-08-12_final.stac-item
2020-10-21 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2020-10-21_final.stac-item
2020-11-20 12:04:45	ga_s2am_ard_3-2-1_49JHN_2020-11-20_final.stac-item
2020-12-20 12:04:41	ga_s2am_ard_3-2-1_49JHN_2020-12-20_final.stac-item
2021-02-08 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-02-08_final.stac-item
2021-02-28 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-02-28_final.stac-item
2021-04-02 12:14:42	ga_s2am_ard_3-2-1_49JFN_2021-04-02_final.stac-item
2021-04-26 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2021-04-26_final.stac-item
2021-05-26 11:57:13	ga_s2am_ard_3-2-1_50HMH_2021-05-26_final.stac-item
2021-07-08 12:04:34	ga_s2am_ard_3-2-1_49KGP_2021-07-08_final.stac-item
2021-07-15 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2021-07-15_final.stac-item
2021-07-28 12:05:00	ga_s2am_ard_3-2-1_49JHM_2021-07-28_final.stac-item
2021-08-04 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-04_final.stac-item
2021-08-17 12:04:59	ga_s2am_ard_3-2-1_49JHM_2021-08-17_final.stac-item
2021-09-29 12:13:44	ga_s2am_ard_3-2-1_49KHS_2021-09-29_final
2021-10-19 12:15:01	ga_s2am_ard_3-2-1_49JGM_2021-10-19_final.stac-item
2021-11-08 12:13:43	ga_s2am_ard_3-2-1_49KHS_2021-11-08_final
2021-11-25 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-11-25_final.stac-item
2022-02-03 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2022-02-03_final.stac-item
2022-05-04 12:04:04	ga_s2am_ard_3-2-1_49KHR_2022-05-04_final.stac-item
2022-05-31 11:57:17	ga_s2am_ard_3-2-1_50HLH_2022-05-31_final.stac-item
2022-06-30 11:57:19	ga_s2am_ard_3-2-1_50HMH_2022-06-30_final.stac-item
2022-08-22 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-08-22_final.stac-item
2022-10-24 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-10-24_final.stac-item
2022-10-24 12:15:12	ga_s2am_ard_3-2-1_49JGL_2022-10-24_final.stac-item
2022-11-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-11-13_final.stac-item
2022-11-23 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-11-23_final.stac-item
2022-12-30 12:04:30	ga_s2am_ard_3-2-1_49KGP_2022-12-30_final.stac-item
2023-01-03 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-01-03_final
2023-02-01 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-02-01_final
2023-02-12 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-02-12_final
2023-02-22 11:47:25	ga_s2am_ard_3-2-1_50HLG_2023-02-22_final
2023-03-13 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2023-03-13_final
2023-04-09 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-04-09_final
2023-05-26 11:57:23	ga_s2am_ard_3-2-1_50HMG_2023-05-26_final
2023-06-02 11:47:18	ga_s2am_ard_3-2-1_50HLH_2023-06-02_final
2023-07-02 11:47:29	ga_s2am_ard_3-2-1_50HMG_2023-07-02_final
2023-08-10 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2023-08-10_final
2023-10-26 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2023-10-26_final
2023-11-25 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-11-25_final
2023-11-25 12:04:55	ga_s2am_ard_3-2-1_49JGM_2023-11-25_final
2024-02-07 11:47:22	ga_s2am_ard_3-2-1_50HLG_2024-02-07_final
2024-02-13 12:03:56	ga_s2am_ard_3-2-1_49KHR_2024-02-13_final
2024-02-23 12:04:29	ga_s2am_ard_3-2-1_49KGP_2024-02-23_final
2024-02-23 12:04:40	ga_s2am_ard_3-2-1_49JGN_2024-02-23_final
2024-04-17 11:47:27	ga_s2am_ard_3-2-1_50HMG_2024-04-17_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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