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
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HNG_2016-01-07_final
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_49JGK_2016-02-05_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JGK_2016-06-24_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KGP_2016-07-14_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JHN_2016-09-02_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49KGP_2016-10-05_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-22_final
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HNJ_2016-12-05_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49JHN_2017-02-19_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JKM_2017-02-19_final.stac-item
2017-05-17 11:56:36	ga_s2am_ard_3-2-1_50HLH_2017-05-17_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50HPJ_2017-06-13_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HMK_2017-07-03_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HQH_2017-07-03_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KGP_2017-08-01_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JGM_2017-10-27_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HLJ_2017-12-03_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-02-14_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-03-06_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGN_2018-03-09_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGM_2018-06-24_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HNK_2018-06-28_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2018-07-17_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50HNK_2018-08-10_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49JGN_2018-10-25_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-11-01_final.stac-item
2019-01-13 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2019-01-13_final.stac-item
2019-01-14 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2019-01-14_final.stac-item
2019-02-16 11:56:26	ga_s2am_ard_3-2-1_50HNK_2019-02-16_final.stac-item
2019-02-23 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2019-02-23_final.stac-item
2019-04-11 11:36:50	ga_s2am_ard_3-2-1_50HQJ_2019-04-11_final.stac-item
2019-05-30 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-05-30_final.stac-item
2019-06-09 12:05:29	ga_s2am_ard_3-2-1_50JKQ_2019-06-09_final.stac-item
2019-07-29 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-29_final.stac-item
2019-08-02 11:47:11	ga_s2am_ard_3-2-1_50HNH_2019-08-02_final.stac-item
2019-09-04 11:56:36	ga_s2am_ard_3-2-1_50HMK_2019-09-04_final.stac-item
2019-09-07 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-09-07_final.stac-item
2019-09-08 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2019-09-08_final.stac-item
2019-09-17 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-09-17_final.stac-item
2019-09-30 12:14:43	ga_s2am_ard_3-2-1_49JGN_2019-09-30_final.stac-item
2019-10-10 12:15:13	ga_s2am_ard_3-2-1_49JGL_2019-10-10_final.stac-item
2019-10-27 12:05:44	ga_s2am_ard_3-2-1_50JKP_2019-10-27_final.stac-item
2019-10-30 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-10-30_final.stac-item
2019-12-26 12:04:37	ga_s2am_ard_3-2-1_50JKT_2019-12-26_final.stac-item
2020-01-02 11:55:41	ga_s2am_ard_3-2-1_50JKP_2020-01-02_final.stac-item
2020-03-15 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-03-15_final.stac-item
2020-03-25 12:04:39	ga_s2am_ard_3-2-1_50JKT_2020-03-25_final.stac-item
2020-04-17 12:14:41	ga_s2am_ard_3-2-1_49JGN_2020-04-17_final.stac-item
2020-04-17 12:15:10	ga_s2am_ard_3-2-1_49JGL_2020-04-17_final.stac-item
2020-06-14 11:37:09	ga_s2am_ard_3-2-1_50HQH_2020-06-14_final.stac-item
2020-06-20 11:56:36	ga_s2am_ard_3-2-1_50HNK_2020-06-20_final.stac-item
2020-06-20 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2020-06-20_final.stac-item
2020-08-26 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2020-08-26_final.stac-item
2020-09-14 12:14:49	ga_s2am_ard_3-2-1_49JFN_2020-09-14_final.stac-item
2020-11-03 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-11-03_final.stac-item
2020-11-13 12:14:02	ga_s2am_ard_3-2-1_49KGR_2020-11-13_final.stac-item
2020-11-20 12:04:30	ga_s2am_ard_3-2-1_49KHP_2020-11-20_final.stac-item
2020-11-30 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2020-11-30_final.stac-item
2021-02-11 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2021-02-11_final.stac-item
2021-04-02 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2021-04-02_final.stac-item
2021-04-09 12:05:22	ga_s2am_ard_3-2-1_50JKQ_2021-04-09_final.stac-item
2021-04-19 12:04:23	ga_s2am_ard_3-2-1_49KHP_2021-04-19_final.stac-item
2021-05-12 12:14:26	ga_s2am_ard_3-2-1_49KGP_2021-05-12_final.stac-item
2021-10-13 11:56:19	ga_s2am_ard_3-2-1_50JKM_2021-10-13_final.stac-item
2021-10-30 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2021-10-30_final.stac-item
2021-11-12 11:55:48	ga_s2am_ard_3-2-1_50JKP_2021-11-12_final.stac-item
2021-12-06 11:36:37	ga_s2am_ard_3-2-1_50HPK_2021-12-06_final.stac-item
2021-12-19 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-12-19_final.stac-item
2021-12-22 11:57:07	ga_s2am_ard_3-2-1_50HMH_2021-12-22_final.stac-item
2022-01-31 11:55:46	ga_s2am_ard_3-2-1_50JKP_2022-01-31_final.stac-item
2022-02-14 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2022-02-14_final.stac-item
2022-03-28 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2022-03-28_final.stac-item
2022-03-28 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-03-28_final.stac-item
2022-06-23 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-06-23_final.stac-item
2022-06-26 12:15:23	ga_s2am_ard_3-2-1_49JGL_2022-06-26_final.stac-item
2022-10-04 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-10-04_final.stac-item
2022-10-08 11:56:32	ga_s2am_ard_3-2-1_50JLL_2022-10-08_final.stac-item
2022-10-18 11:56:33	ga_s2am_ard_3-2-1_50HNK_2022-10-18_final.stac-item
2022-10-31 12:05:45	ga_s2am_ard_3-2-1_50JKP_2022-10-31_final.stac-item
2022-11-20 12:06:05	ga_s2am_ard_3-2-1_50JLM_2022-11-20_final.stac-item
2022-11-30 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2022-11-30_final.stac-item
2022-12-07 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2022-12-07_final.stac-item
2022-12-14 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2022-12-14_final.stac-item
2022-12-14 11:47:06	ga_s2am_ard_3-2-1_50HNH_2022-12-14_final.stac-item
2023-02-12 11:47:05	ga_s2am_ard_3-2-1_50HNH_2023-02-12_final
2023-03-01 11:37:00	ga_s2am_ard_3-2-1_50HQH_2023-03-01_final
2023-03-03 12:13:51	ga_s2am_ard_3-2-1_49KHR_2023-03-03_final
2023-05-19 12:04:33	ga_s2am_ard_3-2-1_49KGP_2023-05-19_final
2023-05-23 11:47:27	ga_s2am_ard_3-2-1_50HMG_2023-05-23_final
2023-07-02 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2023-07-02_final
2023-08-28 11:37:08	ga_s2am_ard_3-2-1_50HQH_2023-08-28_final
2023-09-26 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2023-09-26_final
2023-10-19 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-19_final
2023-10-30 11:46:37	ga_s2am_ard_3-2-1_50HNK_2023-10-30_final
2023-11-06 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2023-11-06_final
2023-12-09 11:46:32	ga_s2am_ard_3-2-1_50HNK_2023-12-09_final
2024-01-28 11:46:32	ga_s2am_ard_3-2-1_50HNK_2024-01-28_final
2024-02-07 11:47:13	ga_s2am_ard_3-2-1_50HPG_2024-02-07_final
2024-02-13 12:05:23	ga_s2am_ard_3-2-1_50JKQ_2024-02-13_final
2024-02-23 12:05:24	ga_s2am_ard_3-2-1_50JKQ_2024-02-23_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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