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_49JGM_2015-10-28_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHS_2016-05-18_final
2016-08-06 12:13:25	ga_s2am_ard_3-2-1_49KGQ_2016-08-06_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_49JGM_2016-08-13_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-10-05_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_49KHR_2016-10-12_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHR_2016-12-21_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JFM_2016-12-24_final.stac-item
2016-12-24 12:14:52	ga_s2am_ard_3-2-1_49JGL_2016-12-24_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49JGM_2016-12-31_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49JFM_2017-01-03_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49JGL_2017-01-03_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGL_2017-01-20_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49JGM_2017-02-02_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHR_2017-02-12_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KGQ_2017-02-22_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KGR_2017-04-23_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGL_2017-11-19_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49KHR_2017-11-26_final.stac-item
2017-12-09 12:14:36	ga_s2am_ard_3-2-1_49JGM_2017-12-09_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGL_2017-12-16_final.stac-item
2018-01-15 12:03:40	ga_s2am_ard_3-2-1_49KHR_2018-01-15_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JGJ_2018-04-25_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGJ_2018-08-13_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49JGM_2018-10-15_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49JGK_2018-10-22_final.stac-item
2018-11-14 12:14:50	ga_s2am_ard_3-2-1_49JGM_2018-11-14_final.stac-item
2018-12-31 12:05:09	ga_s2am_ard_3-2-1_49JGL_2018-12-31_final.stac-item
2019-02-12 12:14:56	ga_s2am_ard_3-2-1_49JFM_2019-02-12_final.stac-item
2019-06-09 12:05:17	ga_s2am_ard_3-2-1_49JGL_2019-06-09_final.stac-item
2019-06-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final.stac-item
2019-07-09 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-09_final.stac-item
2019-09-10 12:14:58	ga_s2am_ard_3-2-1_49JFM_2019-09-10_final.stac-item
2019-10-20 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-10-20_final.stac-item
2019-10-27 12:05:18	ga_s2am_ard_3-2-1_49JGL_2019-10-27_final.stac-item
2019-11-19 12:13:56	ga_s2am_ard_3-2-1_49KHR_2019-11-19_final.stac-item
2019-11-19 12:15:12	ga_s2am_ard_3-2-1_49JGL_2019-11-19_final.stac-item
2019-12-09 12:15:06	ga_s2am_ard_3-2-1_49JGL_2019-12-09_final.stac-item
2020-01-05 12:03:54	ga_s2am_ard_3-2-1_49KHR_2020-01-05_final.stac-item
2020-05-17 12:15:05	ga_s2am_ard_3-2-1_49JFM_2020-05-17_final.stac-item
2020-06-26 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-06-26_final.stac-item
2020-07-26 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-07-26_final.stac-item
2020-08-22 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-08-22_final.stac-item
2020-10-11 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-10-11_final.stac-item
2020-11-23 12:13:56	ga_s2am_ard_3-2-1_49KHR_2020-11-23_final.stac-item
2020-11-23 12:15:01	ga_s2am_ard_3-2-1_49JFM_2020-11-23_final.stac-item
2020-12-30 12:05:00	ga_s2am_ard_3-2-1_49JGM_2020-12-30_final.stac-item
2021-01-12 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-01-12_final.stac-item
2021-03-13 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-03-13_final.stac-item
2021-05-19 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-05-19_final.stac-item
2021-06-11 12:13:59	ga_s2am_ard_3-2-1_49KGR_2021-06-11_final.stac-item
2021-06-28 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-06-28_final.stac-item
2021-07-11 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-07-11_final.stac-item
2021-08-10 12:14:01	ga_s2am_ard_3-2-1_49KGR_2021-08-10_final.stac-item
2021-10-26 12:04:36	ga_s2am_ard_3-2-1_49KGP_2021-10-26_final.stac-item
2021-12-08 12:13:53	ga_s2am_ard_3-2-1_49KHR_2021-12-08_final.stac-item
2022-01-07 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2022-01-07_final.stac-item
2022-02-03 12:03:59	ga_s2am_ard_3-2-1_49KHR_2022-02-03_final.stac-item
2022-02-16 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-02-16_final.stac-item
2022-03-15 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-03-15_final.stac-item
2022-03-18 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-03-18_final.stac-item
2022-03-28 12:13:57	ga_s2am_ard_3-2-1_49KHR_2022-03-28_final.stac-item
2022-05-04 12:04:47	ga_s2am_ard_3-2-1_49JHN_2022-05-04_final.stac-item
2022-05-24 12:04:06	ga_s2am_ard_3-2-1_49KHR_2022-05-24_final.stac-item
2022-05-24 12:04:20	ga_s2am_ard_3-2-1_49KHQ_2022-05-24_final.stac-item
2022-06-13 12:04:45	ga_s2am_ard_3-2-1_49KGP_2022-06-13_final.stac-item
2022-07-13 12:04:47	ga_s2am_ard_3-2-1_49KGP_2022-07-13_final.stac-item
2022-08-12 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-08-12_final.stac-item
2022-10-24 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-10-24_final.stac-item
2022-11-10 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-11-10_final.stac-item
2022-11-20 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-11-20_final.stac-item
2022-12-10 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-12-10_final.stac-item
2022-12-23 12:14:54	ga_s2am_ard_3-2-1_49JGM_2022-12-23_final.stac-item
2022-12-30 12:04:59	ga_s2am_ard_3-2-1_49JGM_2022-12-30_final.stac-item
2023-01-19 12:04:55	ga_s2am_ard_3-2-1_49JGM_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
2023-02-11 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-11_nrt.stac-item
2023-02-11 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-11_final
2023-02-11 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-11_nrt.stac-item
2023-02-11 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-11_final
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_nrt.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_final
2023-04-02 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-04-02_final
2023-05-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2023-05-02_final
2023-05-09 12:03:59	ga_s2am_ard_3-2-1_49KHR_2023-05-09_final
2023-05-22 12:13:43	ga_s2am_ard_3-2-1_49KHS_2023-05-22_final
2023-08-07 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2023-08-07_final
2023-10-06 12:05:30	ga_s2am_ard_3-2-1_49JGK_2023-10-06_final
2023-10-09 12:13:54	ga_s2am_ard_3-2-1_49KHR_2023-10-09_final
2023-10-09 12:13:58	ga_s2am_ard_3-2-1_49KGR_2023-10-09_final
2023-10-26 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-10-26_final
2023-10-29 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-29_final
2023-11-05 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-11-05_final
2023-12-08 12:15:05	ga_s2am_ard_3-2-1_49JGL_2023-12-08_final
2024-01-04 12:03:56	ga_s2am_ard_3-2-1_49KHR_2024-01-04_final
2024-02-03 12:04:56	ga_s2am_ard_3-2-1_49JGM_2024-02-03_final
2024-02-13 12:04:58	ga_s2am_ard_3-2-1_49JGM_2024-02-13_final
2024-02-23 12:04:58	ga_s2am_ard_3-2-1_49JGM_2024-02-23_final
2024-03-07 12:14:57	ga_s2am_ard_3-2-1_49JGM_2024-03-07_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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