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
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HLH_2015-10-22_final.stac-item
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HMJ_2015-11-21_final.stac-item
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HNH_2015-11-21_final.stac-item
2015-11-27 12:03:46	ga_s2am_ard_3-2-1_49KHR_2015-11-27_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KGQ_2016-01-16_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50HNG_2016-02-06_final
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49JGN_2016-03-16_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HMH_2016-04-29_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_49JGL_2016-05-05_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KHP_2016-06-07_final.stac-item
2016-07-17 12:13:25	ga_s2am_ard_3-2-1_49KGR_2016-07-17_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_50HPJ_2016-08-24_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HLH_2016-10-26_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGL_2016-11-11_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49KHP_2017-02-19_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_50HQJ_2017-07-10_final.stac-item
2017-08-31 12:13:43	ga_s2am_ard_3-2-1_49KHR_2017-08-31_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49JGL_2017-11-09_final.stac-item
2017-12-09 12:14:36	ga_s2am_ard_3-2-1_49JFM_2017-12-09_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HLH_2018-02-01_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50HMH_2018-04-12_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGP_2018-09-05_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50HPJ_2018-10-03_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-05_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-10-22_final.stac-item
2019-01-27 11:56:26	ga_s2am_ard_3-2-1_50HNK_2019-01-27_final.stac-item
2019-04-27 11:56:33	ga_s2am_ard_3-2-1_50HNK_2019-04-27_final.stac-item
2019-06-13 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-06-13_final.stac-item
2019-06-16 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2019-06-16_final.stac-item
2019-06-22 12:14:02	ga_s2am_ard_3-2-1_49KGR_2019-06-22_final.stac-item
2019-07-20 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2019-07-20_final.stac-item
2019-08-25 11:56:32	ga_s2am_ard_3-2-1_50HNK_2019-08-25_final.stac-item
2019-10-01 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2019-10-01_final.stac-item
2019-11-20 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2019-11-20_final.stac-item
2019-12-16 12:04:55	ga_s2am_ard_3-2-1_49JGM_2019-12-16_final.stac-item
2020-03-02 11:57:01	ga_s2am_ard_3-2-1_50HMH_2020-03-02_final.stac-item
2020-04-07 12:15:08	ga_s2am_ard_3-2-1_49JGL_2020-04-07_final.stac-item
2020-04-28 11:47:05	ga_s2am_ard_3-2-1_50HPH_2020-04-28_final.stac-item
2020-05-05 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2020-05-05_final.stac-item
2020-05-08 11:46:45	ga_s2am_ard_3-2-1_50HMK_2020-05-08_final.stac-item
2020-05-08 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2020-05-08_final.stac-item
2020-06-06 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-06-06_final.stac-item
2020-08-15 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-08-15_final.stac-item
2020-09-04 12:15:00	ga_s2am_ard_3-2-1_49JGM_2020-09-04_final.stac-item
2020-12-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-17_final.stac-item
2020-12-23 12:15:09	ga_s2am_ard_3-2-1_49JGL_2020-12-23_final.stac-item
2020-12-27 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2020-12-27_final.stac-item
2021-01-10 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2021-01-10_final.stac-item
2021-01-13 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-13_final.stac-item
2021-02-18 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-02-18_final.stac-item
2021-02-21 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2021-02-21_final.stac-item
2021-02-22 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-02-22_final.stac-item
2021-04-13 11:47:11	ga_s2am_ard_3-2-1_50HPG_2021-04-13_final
2021-04-30 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2021-04-30_final.stac-item
2021-05-06 11:57:04	ga_s2am_ard_3-2-1_50HMH_2021-05-06_final.stac-item
2021-09-03 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-03_final.stac-item
2021-09-19 12:14:58	ga_s2am_ard_3-2-1_49JGM_2021-09-19_final.stac-item
2021-09-26 12:04:50	ga_s2am_ard_3-2-1_49JGN_2021-09-26_final.stac-item
2021-12-19 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-12-19_final.stac-item
2022-02-06 12:13:58	ga_s2am_ard_3-2-1_49KGR_2022-02-06_final.stac-item
2022-05-24 12:04:42	ga_s2am_ard_3-2-1_49KGP_2022-05-24_final.stac-item
2022-06-13 12:04:24	ga_s2am_ard_3-2-1_49KHQ_2022-06-13_final.stac-item
2022-06-17 11:46:45	ga_s2am_ard_3-2-1_50HPK_2022-06-17_final.stac-item
2022-08-26 11:47:19	ga_s2am_ard_3-2-1_50HNH_2022-08-26_final
2022-09-01 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-09-01_final.stac-item
2022-09-18 11:56:45	ga_s2am_ard_3-2-1_50HMK_2022-09-18_final.stac-item
2022-09-24 12:14:34	ga_s2am_ard_3-2-1_49KGP_2022-09-24_final.stac-item
2022-10-18 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-10-18_final.stac-item
2022-10-24 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2022-10-24_final.stac-item
2022-11-13 12:14:59	ga_s2am_ard_3-2-1_49JGM_2022-11-13_final.stac-item
2022-12-23 12:14:57	ga_s2am_ard_3-2-1_49JFM_2022-12-23_final.stac-item
2023-01-12 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-01-12_final.stac-item
2023-01-12 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-01-12_final.stac-item
2023-01-16 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2023-01-16_final.stac-item
2023-01-23 11:47:20	ga_s2am_ard_3-2-1_50HMG_2023-01-23_final
2023-01-29 12:05:27	ga_s2am_ard_3-2-1_49JGK_2023-01-29_final.stac-item
2023-02-01 12:14:58	ga_s2am_ard_3-2-1_49JFM_2023-02-01_final.stac-item
2023-02-01 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-01_final
2023-04-06 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-04-06_final
2023-05-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2023-05-02_final
2023-05-12 12:14:40	ga_s2am_ard_3-2-1_49JGN_2023-05-12_final
2023-06-09 11:37:06	ga_s2am_ard_3-2-1_50HQH_2023-06-09_final
2023-06-22 11:46:44	ga_s2am_ard_3-2-1_50HMK_2023-06-22_final
2023-07-12 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-07-12_final
2023-08-14 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-08-14_final
2023-08-21 11:47:23	ga_s2am_ard_3-2-1_50HPG_2023-08-21_final
2023-09-19 12:15:02	ga_s2am_ard_3-2-1_49JFM_2023-09-19_final
2023-09-20 11:46:32	ga_s2am_ard_3-2-1_50HQK_2023-09-20_final
2023-09-30 11:46:40	ga_s2am_ard_3-2-1_50HNK_2023-09-30_final
2023-09-30 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2023-09-30_final
2023-10-06 12:05:30	ga_s2am_ard_3-2-1_49JGK_2023-10-06_final
2023-10-09 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-09_final
2023-12-02 11:57:01	ga_s2am_ard_3-2-1_50HLH_2023-12-02_final
2023-12-09 11:47:09	ga_s2am_ard_3-2-1_50HLH_2023-12-09_final
2023-12-12 11:57:01	ga_s2am_ard_3-2-1_50HMH_2023-12-12_final
2023-12-29 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-12-29_final
2024-01-24 12:05:23	ga_s2am_ard_3-2-1_49JGK_2024-01-24_final
2024-02-06 12:13:50	ga_s2am_ard_3-2-1_49KHR_2024-02-06_final
2024-02-06 12:14:52	ga_s2am_ard_3-2-1_49JGM_2024-02-06_final
2024-02-17 11:47:04	ga_s2am_ard_3-2-1_50HNH_2024-02-17_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

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