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_49JGL_2015-10-28_final.stac-item
2015-11-27 12:04:51	ga_s2am_ard_3-2-1_49JHM_2015-11-27_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49KHP_2015-11-30_final.stac-item
2016-04-25 12:04:45	ga_s2am_ard_3-2-1_49JHN_2016-04-25_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_49JHM_2016-06-14_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JGL_2016-09-02_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JGM_2016-11-14_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-12-11_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHP_2016-12-21_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49JFM_2017-01-03_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGN_2017-01-20_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49JHN_2017-01-30_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-12_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49KGP_2017-06-02_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2017-06-19_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49JGL_2017-08-01_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGL_2017-11-19_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KGR_2018-04-28_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_49JGN_2018-06-04_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2018-11-04_final.stac-item
2018-11-21 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2018-11-21_final.stac-item
2019-01-10 12:05:25	ga_s2am_ard_3-2-1_49JGK_2019-01-10_final.stac-item
2019-01-20 12:04:42	ga_s2am_ard_3-2-1_49JGN_2019-01-20_final.stac-item
2019-02-09 12:04:53	ga_s2am_ard_3-2-1_49JHM_2019-02-09_final.stac-item
2019-02-19 12:04:53	ga_s2am_ard_3-2-1_49JHM_2019-02-19_final.stac-item
2019-03-04 12:14:22	ga_s2am_ard_3-2-1_49KGP_2019-03-04_final.stac-item
2019-03-14 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-03-14_final.stac-item
2019-03-21 12:04:55	ga_s2am_ard_3-2-1_49JHM_2019-03-21_final.stac-item
2019-04-03 12:14:42	ga_s2am_ard_3-2-1_49JGN_2019-04-03_final.stac-item
2019-04-20 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-04-20_final.stac-item
2019-06-12 12:14:01	ga_s2am_ard_3-2-1_49KGR_2019-06-12_final.stac-item
2019-06-12 12:14:24	ga_s2am_ard_3-2-1_49KHP_2019-06-12_final.stac-item
2019-09-30 12:14:28	ga_s2am_ard_3-2-1_49KGP_2019-09-30_final.stac-item
2019-10-27 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-10-27_final.stac-item
2019-11-06 12:05:11	ga_s2am_ard_3-2-1_49JFM_2019-11-06_final.stac-item
2019-11-09 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-11-09_final.stac-item
2019-12-16 12:04:51	ga_s2am_ard_3-2-1_49JHM_2019-12-16_final.stac-item
2020-01-15 12:05:23	ga_s2am_ard_3-2-1_49JGK_2020-01-15_final.stac-item
2020-02-27 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2020-02-27_final.stac-item
2020-02-27 12:14:55	ga_s2am_ard_3-2-1_49JFM_2020-02-27_final.stac-item
2020-04-14 12:04:30	ga_s2am_ard_3-2-1_49KGP_2020-04-14_final.stac-item
2020-05-07 12:14:31	ga_s2am_ard_3-2-1_49KGP_2020-05-07_final.stac-item
2020-05-17 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-05-17_final.stac-item
2020-05-27 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-05-27_final.stac-item
2020-06-03 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-06-03_final.stac-item
2020-06-06 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2020-06-06_final.stac-item
2020-08-12 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-08-12_final.stac-item
2020-09-01 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-09-01_final.stac-item
2020-09-14 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2020-09-14_final.stac-item
2020-09-21 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-09-21_final.stac-item
2020-12-03 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2020-12-03_final.stac-item
2021-01-19 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2021-01-19_final.stac-item
2021-02-08 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2021-02-08_final.stac-item
2021-09-16 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-09-16_final.stac-item
2021-10-06 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2021-10-06_final.stac-item
2021-11-05 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2021-11-05_final.stac-item
2021-12-15 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-12-15_final.stac-item
2022-02-16 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-02-16_final.stac-item
2022-04-14 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-04-14_final.stac-item
2022-05-04 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2022-05-04_final.stac-item
2022-05-04 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-05-04_final.stac-item
2022-05-07 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2022-05-07_final.stac-item
2022-05-14 12:04:37	ga_s2am_ard_3-2-1_49JHN_2022-05-14_final.stac-item
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-05-24_final.stac-item
2022-06-13 12:04:52	ga_s2am_ard_3-2-1_49JHN_2022-06-13_final.stac-item
2022-07-03 12:04:26	ga_s2am_ard_3-2-1_49KHQ_2022-07-03_final.stac-item
2022-08-15 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-08-15_final.stac-item
2022-08-15 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-08-15_final.stac-item
2022-08-25 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-08-25_final.stac-item
2022-09-14 12:14:23	ga_s2am_ard_3-2-1_49KGQ_2022-09-14_final.stac-item
2022-10-14 12:14:17	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2022-10-24 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-10-24_final.stac-item
2022-11-10 12:04:31	ga_s2am_ard_3-2-1_49KHP_2022-11-10_final.stac-item
2022-11-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2022-11-23_final.stac-item
2023-01-02 12:14:26	ga_s2am_ard_3-2-1_49KGP_2023-01-02_final.stac-item
2023-01-19 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-01-19_final.stac-item
2023-01-29 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2023-01-29_final.stac-item
2023-02-21 12:14:39	ga_s2am_ard_3-2-1_49JGN_2023-02-21_nrt.stac-item
2023-02-21 12:14:57	ga_s2am_ard_3-2-1_49JFM_2023-02-21_nrt.stac-item
2023-02-21 12:14:57	ga_s2am_ard_3-2-1_49JFM_2023-02-21_final
2023-02-28 12:04:26	ga_s2am_ard_3-2-1_49KGP_2023-02-28_final
2023-03-10 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-03-10_final
2023-05-09 12:04:42	ga_s2am_ard_3-2-1_49JHN_2023-05-09_final
2023-06-08 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-06-08_final
2023-06-11 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2023-06-11_final
2023-07-01 12:14:31	ga_s2am_ard_3-2-1_49KGP_2023-07-01_final
2023-08-17 12:04:37	ga_s2am_ard_3-2-1_49KGP_2023-08-17_final
2023-08-27 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2023-08-27_final
2023-08-27 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2023-08-27_final
2023-09-26 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2023-09-26_final
2023-10-06 12:05:30	ga_s2am_ard_3-2-1_49JGK_2023-10-06_final
2023-10-16 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-10-16_final
2023-10-16 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-10-16_final
2023-11-05 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-11-05_final
2023-11-08 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-11-08_final
2023-11-15 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-11-15_final
2023-11-18 12:14:25	ga_s2am_ard_3-2-1_49KGP_2023-11-18_final
2023-12-18 12:14:52	ga_s2am_ard_3-2-1_49JGM_2023-12-18_final
2024-01-14 12:04:36	ga_s2am_ard_3-2-1_49JHN_2024-01-14_final
2024-02-06 12:13:54	ga_s2am_ard_3-2-1_49KGR_2024-02-06_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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