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
2015-09-11 12:14:44	ga_s2am_ard_3-2-1_49JFM_2015-09-11_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49JGL_2015-11-30_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_49JGM_2015-12-27_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JHM_2016-10-02_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGM_2016-11-01_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMG_2016-11-05_final
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JGL_2016-11-24_final.stac-item
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_49JGL_2017-05-20_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50HMJ_2017-05-27_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JGM_2017-06-09_final.stac-item
2017-08-08 12:04:43	ga_s2am_ard_3-2-1_49JGK_2017-08-08_final.stac-item
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_49JHN_2017-08-28_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHR_2017-09-27_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49KHR_2017-10-10_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HLH_2017-10-24_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KHR_2017-11-29_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGQ_2017-12-19_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JGL_2018-01-08_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49JGM_2018-01-25_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49JFM_2018-02-17_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JGL_2018-04-25_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLK_2018-05-22_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49JGL_2018-05-28_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_49KHP_2018-06-04_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_49KHQ_2018-06-04_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HMH_2018-06-18_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGN_2018-06-24_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49KGP_2018-06-24_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGL_2018-07-17_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGN_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2018-08-23_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HLK_2018-08-30_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JGM_2018-09-02_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HMJ_2018-09-19_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMK_2018-10-16_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-11-01_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HMK_2018-11-05_final.stac-item
2018-11-25 11:46:33	ga_s2am_ard_3-2-1_50HMK_2018-11-25_final.stac-item
2018-12-11 12:05:06	ga_s2am_ard_3-2-1_49JGL_2018-12-11_final.stac-item
2018-12-21 12:04:23	ga_s2am_ard_3-2-1_49KGP_2018-12-21_final.stac-item
2019-01-03 12:14:15	ga_s2am_ard_3-2-1_49KHP_2019-01-03_final.stac-item
2019-03-21 12:04:58	ga_s2am_ard_3-2-1_49JGM_2019-03-21_final.stac-item
2019-06-19 12:05:33	ga_s2am_ard_3-2-1_49JGK_2019-06-19_final.stac-item
2019-07-09 12:05:34	ga_s2am_ard_3-2-1_49JGK_2019-07-09_final.stac-item
2019-12-16 12:04:55	ga_s2am_ard_3-2-1_49JGM_2019-12-16_final.stac-item
2020-01-19 11:46:34	ga_s2am_ard_3-2-1_50HMK_2020-01-19_final.stac-item
2020-01-25 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2020-01-25_final.stac-item
2020-03-05 12:05:11	ga_s2am_ard_3-2-1_49JGL_2020-03-05_final.stac-item
2020-03-09 11:47:09	ga_s2am_ard_3-2-1_50HMH_2020-03-09_final.stac-item
2020-03-12 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2020-03-12_final.stac-item
2020-03-28 12:14:52	ga_s2am_ard_3-2-1_49JGM_2020-03-28_final.stac-item
2020-04-01 11:56:36	ga_s2am_ard_3-2-1_50HLK_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 12:15:02	ga_s2am_ard_3-2-1_49JFM_2020-04-27_final.stac-item
2020-06-10 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-06-10_final.stac-item
2020-10-04 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-10-04_final.stac-item
2020-11-30 12:05:00	ga_s2am_ard_3-2-1_49JGM_2020-11-30_final.stac-item
2020-12-17 11:56:34	ga_s2am_ard_3-2-1_50HMK_2020-12-17_final.stac-item
2021-01-12 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-01-12_final.stac-item
2021-01-23 11:47:28	ga_s2am_ard_3-2-1_50HLG_2021-01-23_final
2021-02-28 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-28_final
2021-03-03 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-03-03_final.stac-item
2021-03-10 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-03-10_final.stac-item
2021-03-23 12:15:09	ga_s2am_ard_3-2-1_49JGL_2021-03-23_final.stac-item
2021-03-27 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2021-03-27_final.stac-item
2021-04-26 11:57:03	ga_s2am_ard_3-2-1_50HLH_2021-04-26_final.stac-item
2021-05-26 11:57:14	ga_s2am_ard_3-2-1_50HLH_2021-05-26_final.stac-item
2021-06-18 12:05:10	ga_s2am_ard_3-2-1_49JGL_2021-06-18_final.stac-item
2021-07-01 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-07-01_final.stac-item
2021-07-08 12:04:49	ga_s2am_ard_3-2-1_49JGN_2021-07-08_final.stac-item
2021-07-28 12:04:02	ga_s2am_ard_3-2-1_49KHR_2021-07-28_final.stac-item
2021-08-14 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2021-08-14_final.stac-item
2021-08-27 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-27_final.stac-item
2021-10-10 11:47:15	ga_s2am_ard_3-2-1_50HMH_2021-10-10_final.stac-item
2021-10-23 11:57:28	ga_s2am_ard_3-2-1_50HLG_2021-10-23_final
2021-11-25 12:05:29	ga_s2am_ard_3-2-1_49JGK_2021-11-25_final.stac-item
2021-12-19 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-12-19_final.stac-item
2022-05-31 11:57:17	ga_s2am_ard_3-2-1_50HLH_2022-05-31_final.stac-item
2022-06-13 12:04:56	ga_s2am_ard_3-2-1_49JGN_2022-06-13_final.stac-item
2022-09-01 12:04:43	ga_s2am_ard_3-2-1_49KGP_2022-09-01_final.stac-item
2022-09-28 11:57:13	ga_s2am_ard_3-2-1_50HMH_2022-09-28_final.stac-item
2022-10-05 11:47:17	ga_s2am_ard_3-2-1_50HMH_2022-10-05_final.stac-item
2022-10-08 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-10-08_final.stac-item
2022-11-03 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-11-03_final.stac-item
2022-11-04 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2022-11-04_final.stac-item
2022-11-23 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-11-23_final.stac-item
2022-11-30 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-11-30_final.stac-item
2022-12-03 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-12-03_final.stac-item
2023-02-02 11:47:10	ga_s2am_ard_3-2-1_50HLH_2023-02-02_final
2023-03-07 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2023-03-07_final
2023-03-27 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2023-03-27_final
2023-03-27 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2023-03-27_final
2023-04-26 11:56:40	ga_s2am_ard_3-2-1_50HLK_2023-04-26_final
2023-05-09 12:05:29	ga_s2am_ard_3-2-1_49JGK_2023-05-09_final
2023-10-16 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-10-16_final
2023-11-05 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-11-05_final
2023-12-08 12:13:49	ga_s2am_ard_3-2-1_49KHR_2023-12-08_final
2023-12-09 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2023-12-09_final
2023-12-15 12:05:11	ga_s2am_ard_3-2-1_49JGL_2023-12-15_final
2024-01-24 12:05:08	ga_s2am_ard_3-2-1_49JGL_2024-01-24_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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