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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_49KHQ_2015-10-08_final.stac-item
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_49KHP_2015-10-21_final.stac-item
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JGL_2015-10-21_final.stac-item
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JGM_2015-10-21_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KGP_2015-10-28_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HMG_2015-11-14_final
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_49JGN_2015-11-27_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49JFM_2016-01-09_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49JGM_2016-01-09_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50HLH_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50HLJ_2016-03-03_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KHR_2016-03-09_final.stac-item
2016-04-25 12:03:51	ga_s2am_ard_3-2-1_49KHQ_2016-04-25_final.stac-item
2016-06-17 12:13:46	ga_s2am_ard_3-2-1_49KHR_2016-06-17_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2016-06-27_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HLH_2016-07-21_final.stac-item
2016-08-06 12:13:25	ga_s2am_ard_3-2-1_49KHQ_2016-08-06_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2016-11-21_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-12-11_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGL_2017-01-20_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KGQ_2017-02-12_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49JFM_2017-02-22_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2017-03-31_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2017-09-07_final.stac-item
2017-09-20 12:14:37	ga_s2am_ard_3-2-1_49JGM_2017-09-20_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KGP_2017-09-30_final.stac-item
2017-10-30 12:13:43	ga_s2am_ard_3-2-1_49KHQ_2017-10-30_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KGR_2017-11-09_final.stac-item
2018-01-25 12:02:44	ga_s2am_ard_3-2-1_49KGQ_2018-01-25_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JHN_2018-04-25_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLH_2018-07-31_final.stac-item
2019-01-30 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-01-30_final.stac-item
2019-01-30 12:04:25	ga_s2am_ard_3-2-1_49KHP_2019-01-30_final.stac-item
2019-01-30 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-30_final.stac-item
2019-02-09 12:03:56	ga_s2am_ard_3-2-1_49KHR_2019-02-09_final.stac-item
2019-02-19 12:04:27	ga_s2am_ard_3-2-1_49KGP_2019-02-19_final.stac-item
2019-02-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2019-02-22_final.stac-item
2019-03-14 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-03-14_final.stac-item
2019-03-14 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-03-14_final.stac-item
2019-06-23 11:47:18	ga_s2am_ard_3-2-1_50HLH_2019-06-23_final.stac-item
2019-11-26 12:03:59	ga_s2am_ard_3-2-1_49KHR_2019-11-26_final.stac-item
2019-11-29 12:15:10	ga_s2am_ard_3-2-1_49JGL_2019-11-29_final.stac-item
2019-12-09 12:13:55	ga_s2am_ard_3-2-1_49KGR_2019-12-09_final.stac-item
2019-12-09 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-12-09_final.stac-item
2019-12-16 12:05:09	ga_s2am_ard_3-2-1_49JGL_2019-12-16_final.stac-item
2020-01-25 12:03:52	ga_s2am_ard_3-2-1_49KHR_2020-01-25_final.stac-item
2020-01-28 12:14:05	ga_s2am_ard_3-2-1_49KGQ_2020-01-28_final.stac-item
2020-01-28 12:14:52	ga_s2am_ard_3-2-1_49JFM_2020-01-28_final.stac-item
2020-02-21 11:56:49	ga_s2am_ard_3-2-1_50HLJ_2020-02-21_final.stac-item
2020-03-05 12:05:25	ga_s2am_ard_3-2-1_49JGK_2020-03-05_final.stac-item
2020-04-01 11:56:36	ga_s2am_ard_3-2-1_50HLK_2020-04-01_final.stac-item
2020-07-20 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-07-20_final.stac-item
2020-08-15 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-08-15_final.stac-item
2020-08-15 12:14:14	ga_s2am_ard_3-2-1_49KHQ_2020-08-15_final.stac-item
2020-09-08 11:56:44	ga_s2am_ard_3-2-1_50HLK_2020-09-08_final.stac-item
2020-10-01 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-10-01_final.stac-item
2020-10-01 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-10-01_final.stac-item
2021-01-29 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2021-01-29_final.stac-item
2021-01-29 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-01-29_final.stac-item
2021-09-10 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-09-10_final.stac-item
2021-11-28 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-11-28_final.stac-item
2022-03-15 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-03-15_final.stac-item
2022-04-07 12:14:28	ga_s2am_ard_3-2-1_49KGP_2022-04-07_final.stac-item
2022-05-04 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2022-05-04_final.stac-item
2022-05-21 11:56:46	ga_s2am_ard_3-2-1_50HLK_2022-05-21_final.stac-item
2022-05-24 12:04:42	ga_s2am_ard_3-2-1_49KGP_2022-05-24_final.stac-item
2022-06-23 12:04:46	ga_s2am_ard_3-2-1_49KHP_2022-06-23_final.stac-item
2022-08-26 11:47:22	ga_s2am_ard_3-2-1_50HMH_2022-08-26_final.stac-item
2022-09-04 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-09-04_final.stac-item
2022-10-05 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2022-10-05_final.stac-item
2022-10-31 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2022-10-31_final.stac-item
2022-11-10 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2022-11-10_final.stac-item
2022-12-20 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2022-12-20_final.stac-item
2023-02-11 12:13:53	ga_s2am_ard_3-2-1_49KHR_2023-02-11_final
2023-02-18 12:04:57	ga_s2am_ard_3-2-1_49JGM_2023-02-18_final
2023-02-18 12:05:26	ga_s2am_ard_3-2-1_49JGK_2023-02-18_nrt.stac-item
2023-02-18 12:05:26	ga_s2am_ard_3-2-1_49JGK_2023-02-18_final
2023-05-06 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-05-06_final
2023-06-02 11:47:18	ga_s2am_ard_3-2-1_50HLH_2023-06-02_final
2023-06-28 12:04:46	ga_s2am_ard_3-2-1_49JHN_2023-06-28_final
2023-07-05 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-07-05_final
2023-07-15 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-07-15_final
2023-08-07 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2023-08-07_final
2023-09-03 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-09-03_final
2023-09-09 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-09-09_final
2023-09-09 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2023-09-09_final
2023-10-29 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-10-29_final
2023-11-02 11:57:08	ga_s2am_ard_3-2-1_50HLH_2023-11-02_final
2023-11-05 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-11-05_final
2023-11-12 11:56:39	ga_s2am_ard_3-2-1_50HLK_2023-11-12_final
2023-12-08 12:14:15	ga_s2am_ard_3-2-1_49KHP_2023-12-08_final
2023-12-09 11:47:19	ga_s2am_ard_3-2-1_50HMG_2023-12-09_final
2024-01-17 12:13:50	ga_s2am_ard_3-2-1_49KGR_2024-01-17_final
2024-02-10 11:57:05	ga_s2am_ard_3-2-1_50HLH_2024-02-10_final
2024-02-16 12:14:25	ga_s2am_ard_3-2-1_49KGP_2024-02-16_final
2024-02-26 12:15:09	ga_s2am_ard_3-2-1_49JGL_2024-02-26_final
2024-03-01 11:57:09	ga_s2am_ard_3-2-1_50HLH_2024-03-01_final
2024-03-14 12:04:46	ga_s2am_ard_3-2-1_49JGN_2024-03-14_final
2024-04-03 12:03:57	ga_s2am_ard_3-2-1_49KHR_2024-04-03_final
2024-04-03 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2024-04-03_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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