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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KHR_2016-01-16_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGM_2016-01-26_final.stac-item
2016-05-28 12:13:49	ga_s2am_ard_3-2-1_49KHQ_2016-05-28_final.stac-item
2016-06-17 12:14:44	ga_s2am_ard_3-2-1_49JFM_2016-06-17_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JGM_2016-06-24_final.stac-item
2016-07-07 12:14:44	ga_s2am_ard_3-2-1_49JFM_2016-07-07_final.stac-item
2016-07-07 12:14:44	ga_s2am_ard_3-2-1_49JGL_2016-07-07_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JGL_2016-07-24_final.stac-item
2016-07-27 12:14:46	ga_s2am_ard_3-2-1_49JGM_2016-07-27_final.stac-item
2016-09-05 12:14:41	ga_s2am_ard_3-2-1_49JGL_2016-09-05_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-02_final
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49JGM_2016-10-05_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KGP_2016-11-11_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGJ_2017-05-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGL_2017-05-30_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHP_2017-09-27_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HLH_2017-10-24_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JGL_2017-11-26_final.stac-item
2017-11-26 12:05:06	ga_s2am_ard_3-2-1_49JGL_2017-11-26_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49JHM_2018-01-05_final.stac-item
2018-02-07 12:14:38	ga_s2am_ard_3-2-1_49JGL_2018-02-07_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-02-17_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-02-24_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HLH_2018-03-10_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49JGM_2018-03-29_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JHM_2018-04-05_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49JGM_2018-04-18_final.stac-item
2018-06-14 12:02:48	ga_s2am_ard_3-2-1_49KHR_2018-06-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGN_2018-07-14_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KHR_2018-07-24_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JHN_2018-09-02_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-09-12_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HLH_2018-09-19_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-15_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-10-15_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-10-22_final.stac-item
2018-11-11 12:04:08	ga_s2am_ard_3-2-1_49KHQ_2018-11-11_final.stac-item
2018-11-14 12:14:50	ga_s2am_ard_3-2-1_49JGM_2018-11-14_final.stac-item
2018-12-28 11:56:33	ga_s2am_ard_3-2-1_50HLK_2018-12-28_final.stac-item
2018-12-31 12:04:36	ga_s2am_ard_3-2-1_49JHN_2018-12-31_final.stac-item
2019-04-23 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-04-23_final.stac-item
2019-06-19 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-06-19_final.stac-item
2019-06-19 12:05:33	ga_s2am_ard_3-2-1_49JGK_2019-06-19_final.stac-item
2019-06-26 11:57:14	ga_s2am_ard_3-2-1_50HLH_2019-06-26_final.stac-item
2019-09-07 12:05:14	ga_s2am_ard_3-2-1_49JGL_2019-09-07_final.stac-item
2019-10-07 12:05:17	ga_s2am_ard_3-2-1_49JGL_2019-10-07_final.stac-item
2019-10-17 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-10-17_final.stac-item
2019-10-30 12:15:05	ga_s2am_ard_3-2-1_49JGM_2019-10-30_final.stac-item
2019-12-29 12:14:51	ga_s2am_ard_3-2-1_49JGM_2019-12-29_final.stac-item
2020-01-05 12:03:54	ga_s2am_ard_3-2-1_49KHR_2020-01-05_final.stac-item
2020-01-05 12:04:40	ga_s2am_ard_3-2-1_49JGN_2020-01-05_final.stac-item
2020-02-01 11:56:41	ga_s2am_ard_3-2-1_50HLJ_2020-02-01_final.stac-item
2020-03-22 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-03-22_final.stac-item
2020-03-28 12:14:17	ga_s2am_ard_3-2-1_49KHP_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 12:05:02	ga_s2am_ard_3-2-1_49JGM_2020-04-24_final.stac-item
2020-04-27 12:14:58	ga_s2am_ard_3-2-1_49JGM_2020-04-27_final.stac-item
2020-06-03 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-06-03_final.stac-item
2020-06-26 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-06-26_final.stac-item
2020-08-22 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-08-22_final.stac-item
2020-09-01 12:04:36	ga_s2am_ard_3-2-1_49KGP_2020-09-01_final.stac-item
2020-10-28 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-10-28_final.stac-item
2020-11-30 12:03:59	ga_s2am_ard_3-2-1_49KHR_2020-11-30_final.stac-item
2020-12-23 12:15:09	ga_s2am_ard_3-2-1_49JGL_2020-12-23_final.stac-item
2020-12-30 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2020-12-30_final.stac-item
2020-12-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2020-12-30_final.stac-item
2021-01-09 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-09_final
2021-01-09 12:04:32	ga_s2am_ard_3-2-1_49KGP_2021-01-09_final.stac-item
2021-02-01 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-02-01_final.stac-item
2021-04-12 12:14:36	ga_s2am_ard_3-2-1_49JGN_2021-04-12_final.stac-item
2021-04-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2021-04-22_final.stac-item
2021-04-26 11:56:37	ga_s2am_ard_3-2-1_50HLK_2021-04-26_final.stac-item
2021-05-22 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-05-22_final.stac-item
2021-06-21 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-06-21_final.stac-item
2021-06-28 12:04:01	ga_s2am_ard_3-2-1_49KHR_2021-06-28_final.stac-item
2021-07-11 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2021-07-11_final.stac-item
2021-07-18 12:04:02	ga_s2am_ard_3-2-1_49KHR_2021-07-18_final.stac-item
2021-08-20 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-08-20_final.stac-item
2021-09-06 12:04:57	ga_s2am_ard_3-2-1_49JHM_2021-09-06_final.stac-item
2021-11-05 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-11-05_final
2021-11-15 12:05:30	ga_s2am_ard_3-2-1_49JGK_2021-11-15_final.stac-item
2022-01-11 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-01-11_final.stac-item
2022-02-20 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-02-20_final.stac-item
2022-03-28 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final.stac-item
2022-04-01 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2022-04-01_final.stac-item
2022-09-04 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-09-04_final.stac-item
2022-10-08 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-10-08_final.stac-item
2022-10-18 11:57:12	ga_s2am_ard_3-2-1_50HLH_2022-10-18_final.stac-item
2023-01-09 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-01-09_final
2023-02-12 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-02-12_nrt.stac-item
2023-02-12 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-02-12_final
2023-03-25 12:50:59	ga_s2am_ard_3-2-1_48LWP_2023-03-25_final
2023-04-06 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-06_final
2023-04-09 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-04-09_final
2023-07-31 12:15:01	ga_s2am_ard_3-2-1_49JGM_2023-07-31_final
2023-09-09 12:15:15	ga_s2am_ard_3-2-1_49JGL_2023-09-09_final
2023-11-25 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-11-25_final
2023-11-25 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-11-25_final
2024-01-24 12:03:53	ga_s2am_ard_3-2-1_49KHR_2024-01-24_final
2024-02-03 12:03:55	ga_s2am_ard_3-2-1_49KHR_2024-02-03_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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