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
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49KGP_2015-10-21_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JGN_2015-12-07_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHQ_2016-05-18_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHR_2016-07-14_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2016-08-26_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49JGN_2016-09-15_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KGP_2016-09-15_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-02_final
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHN_2016-11-11_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 12:13:15	ga_s2am_ard_3-2-1_49JGM_2016-12-24_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49KHQ_2017-01-30_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49JGL_2017-02-02_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KHR_2017-02-02_final.stac-item
2017-03-01 12:03:41	ga_s2am_ard_3-2-1_49KHR_2017-03-01_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JGM_2017-03-01_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JGM_2017-05-10_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGR_2017-07-12_final.stac-item
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49JFM_2017-10-20_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KGP_2017-11-29_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KGR_2017-11-29_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_49KHQ_2018-01-05_final.stac-item
2018-01-25 12:02:44	ga_s2am_ard_3-2-1_49KHR_2018-01-25_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-02-27_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-03-06_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49KHQ_2018-04-15_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49KHR_2018-04-18_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49KHR_2018-06-17_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49KGQ_2018-06-24_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-06-27_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-07-07_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHN_2018-07-14_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2018-07-17_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JHM_2018-07-24_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KGQ_2018-08-23_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-15_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2018-11-04_final.stac-item
2018-11-14 12:14:36	ga_s2am_ard_3-2-1_49JGN_2018-11-14_final.stac-item
2018-12-24 12:14:19	ga_s2am_ard_3-2-1_49KGP_2018-12-24_final.stac-item
2018-12-31 12:04:40	ga_s2am_ard_3-2-1_49JGN_2018-12-31_final.stac-item
2019-03-31 12:04:31	ga_s2am_ard_3-2-1_49KGP_2019-03-31_final.stac-item
2019-05-10 12:04:10	ga_s2am_ard_3-2-1_49KHR_2019-05-10_final.stac-item
2019-05-30 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-05-30_final.stac-item
2019-06-22 12:14:31	ga_s2am_ard_3-2-1_49KGP_2019-06-22_final.stac-item
2019-07-02 12:15:15	ga_s2am_ard_3-2-1_49JGL_2019-07-02_final.stac-item
2019-07-19 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-07-19_final.stac-item
2019-08-31 12:13:55	ga_s2am_ard_3-2-1_49KHR_2019-08-31_final.stac-item
2019-10-10 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-10-10_final.stac-item
2019-10-10 12:15:13	ga_s2am_ard_3-2-1_49JGL_2019-10-10_final.stac-item
2019-10-20 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-10-20_final.stac-item
2019-11-29 12:14:41	ga_s2am_ard_3-2-1_49JGN_2019-11-29_final.stac-item
2019-12-29 12:13:53	ga_s2am_ard_3-2-1_49KGR_2019-12-29_final.stac-item
2020-01-15 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2020-01-15_final.stac-item
2020-04-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-04-04_final.stac-item
2020-05-17 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-05-17_final.stac-item
2020-07-26 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-07-26_final.stac-item
2020-08-15 12:14:33	ga_s2am_ard_3-2-1_49KGP_2020-08-15_final.stac-item
2020-09-01 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-09-01_final.stac-item
2020-10-04 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-10-04_final.stac-item
2020-12-10 12:04:28	ga_s2am_ard_3-2-1_49KGP_2020-12-10_final.stac-item
2021-01-02 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-01-02_final.stac-item
2021-01-19 12:04:32	ga_s2am_ard_3-2-1_49KGP_2021-01-19_final.stac-item
2021-02-28 12:04:28	ga_s2am_ard_3-2-1_49KHP_2021-02-28_final.stac-item
2021-03-10 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2021-03-10_final.stac-item
2021-04-02 12:14:24	ga_s2am_ard_3-2-1_49KGP_2021-04-02_final.stac-item
2021-04-29 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2021-04-29_final.stac-item
2021-06-01 12:14:19	ga_s2am_ard_3-2-1_49KHP_2021-06-01_final.stac-item
2021-06-18 12:04:28	ga_s2am_ard_3-2-1_49KHP_2021-06-18_final.stac-item
2021-11-25 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-11-25_final
2021-12-05 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2021-12-05_final.stac-item
2022-01-14 12:04:32	ga_s2am_ard_3-2-1_49KGP_2022-01-14_final.stac-item
2022-01-17 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-01-17_final.stac-item
2022-01-27 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-01-27_final.stac-item
2022-03-08 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-03-08_final.stac-item
2022-05-24 12:04:49	ga_s2am_ard_3-2-1_49JHN_2022-05-24_final.stac-item
2022-06-26 12:15:09	ga_s2am_ard_3-2-1_49JGM_2022-06-26_final.stac-item
2022-07-03 12:04:44	ga_s2am_ard_3-2-1_49KGP_2022-07-03_final.stac-item
2022-07-13 12:04:31	ga_s2am_ard_3-2-1_49KGQ_2022-07-13_final.stac-item
2022-11-23 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-11-23_final.stac-item
2022-12-10 12:04:32	ga_s2am_ard_3-2-1_49KGP_2022-12-10_final.stac-item
2022-12-13 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-12-13_final.stac-item
2023-01-02 12:14:26	ga_s2am_ard_3-2-1_49KGP_2023-01-02_final.stac-item
2023-01-12 12:14:25	ga_s2am_ard_3-2-1_49KGP_2023-01-12_final.stac-item
2023-04-12 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-04-12_final
2023-04-22 12:14:40	ga_s2am_ard_3-2-1_49JGN_2023-04-22_final
2023-06-08 12:05:33	ga_s2am_ard_3-2-1_49JGK_2023-06-08_final
2023-07-08 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-07-08_final
2023-07-28 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-07-28_final
2023-08-07 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-08-07_final
2023-08-20 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-08-20_final
2023-09-06 12:04:36	ga_s2am_ard_3-2-1_49KGP_2023-09-06_final
2023-09-19 12:13:57	ga_s2am_ard_3-2-1_49KHR_2023-09-19_final
2023-10-19 12:13:58	ga_s2am_ard_3-2-1_49KGR_2023-10-19_final
2023-12-18 12:14:23	ga_s2am_ard_3-2-1_49KGP_2023-12-18_final
2023-12-25 12:04:28	ga_s2am_ard_3-2-1_49KGP_2023-12-25_final
2024-01-27 12:14:21	ga_s2am_ard_3-2-1_49KGP_2024-01-27_final
2024-04-06 12:14:25	ga_s2am_ard_3-2-1_49KGP_2024-04-06_final
2024-04-23 12:05:00	ga_s2am_ard_3-2-1_49JHM_2024-04-23_final
2024-04-26 12:15:12	ga_s2am_ard_3-2-1_49JGL_2024-04-26_final
2024-05-16 12:14:59	ga_s2am_ard_3-2-1_49JGM_2024-05-16_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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