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_49JGL_2015-10-21_final.stac-item
2015-11-20 12:14:39	ga_s2am_ard_3-2-1_49JGL_2015-11-20_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KGP_2015-12-30_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KHQ_2016-01-16_final.stac-item
2016-01-26 12:04:01	ga_s2am_ard_3-2-1_49KHR_2016-01-26_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49KGQ_2016-02-08_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHR_2016-05-18_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HLH_2016-07-01_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KGP_2016-08-26_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGK_2016-11-01_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KHR_2016-11-24_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JGM_2016-12-24_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HMH_2017-07-03_final.stac-item
2017-08-12 11:40:50	ga_s2am_ard_3-2-1_50HMH_2017-08-12_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_49KGP_2017-11-06_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HMH_2017-11-20_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KHR_2017-12-19_final.stac-item
2018-02-07 12:14:38	ga_s2am_ard_3-2-1_49JGL_2018-02-07_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-02-17_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-02-24_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HLJ_2018-03-03_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-03-06_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JFM_2018-04-28_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49JGL_2018-05-28_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49JGM_2018-08-03_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_49KHR_2018-08-03_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HLK_2018-08-30_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HLH_2018-10-26_final.stac-item
2018-11-18 11:56:34	ga_s2am_ard_3-2-1_50HLK_2018-11-18_final.stac-item
2018-12-21 12:04:23	ga_s2am_ard_3-2-1_49KGP_2018-12-21_final.stac-item
2019-02-09 12:03:56	ga_s2am_ard_3-2-1_49KHR_2019-02-09_final.stac-item
2019-04-10 12:05:31	ga_s2am_ard_3-2-1_49JGK_2019-04-10_final.stac-item
2019-04-23 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-04-23_final.stac-item
2019-05-13 12:14:02	ga_s2am_ard_3-2-1_49KGR_2019-05-13_final.stac-item
2019-06-16 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-06-16_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_49KHR_2019-07-09_final.stac-item
2019-07-29 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-29_final.stac-item
2019-08-05 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2019-08-05_final.stac-item
2019-09-17 12:03:58	ga_s2am_ard_3-2-1_49KHR_2019-09-17_final.stac-item
2019-11-09 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-11-09_final.stac-item
2019-12-29 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-12-29_final.stac-item
2020-01-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2020-01-08_final.stac-item
2020-04-01 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2020-04-01_final.stac-item
2020-06-03 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-06-03_final.stac-item
2020-08-12 12:04:34	ga_s2am_ard_3-2-1_49KHP_2020-08-12_final.stac-item
2020-08-22 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-08-22_final.stac-item
2020-10-04 12:14:33	ga_s2am_ard_3-2-1_49KGP_2020-10-04_final.stac-item
2020-10-04 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-10-04_final.stac-item
2020-10-21 12:04:04	ga_s2am_ard_3-2-1_49KHR_2020-10-21_final.stac-item
2020-12-07 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-07_final.stac-item
2020-12-20 12:04:59	ga_s2am_ard_3-2-1_49JGM_2020-12-20_final.stac-item
2021-01-09 12:04:32	ga_s2am_ard_3-2-1_49KGP_2021-01-09_final.stac-item
2021-01-23 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-01-23_final.stac-item
2021-02-01 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-02-01_final.stac-item
2021-03-27 11:57:02	ga_s2am_ard_3-2-1_50HMH_2021-03-27_final.stac-item
2021-04-26 11:57:08	ga_s2am_ard_3-2-1_50HMH_2021-04-26_final.stac-item
2021-07-11 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-07-11_final.stac-item
2021-08-10 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-08-10_final.stac-item
2021-10-03 11:57:10	ga_s2am_ard_3-2-1_50HMH_2021-10-03_final.stac-item
2021-10-26 12:04:04	ga_s2am_ard_3-2-1_49KHR_2021-10-26_final.stac-item
2021-11-05 12:04:03	ga_s2am_ard_3-2-1_49KHR_2021-11-05_final.stac-item
2021-11-19 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-11-19_final
2021-12-15 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-12-15_final.stac-item
2022-01-14 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-01-14_final.stac-item
2022-02-07 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-02-07_final.stac-item
2022-02-10 11:57:08	ga_s2am_ard_3-2-1_50HLH_2022-02-10_final.stac-item
2022-02-16 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-02-16_final.stac-item
2022-02-20 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-02-20_final.stac-item
2022-05-07 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-05-07_final.stac-item
2022-05-24 12:04:06	ga_s2am_ard_3-2-1_49KHR_2022-05-24_final.stac-item
2022-06-03 12:04:50	ga_s2am_ard_3-2-1_49JHN_2022-06-03_final.stac-item
2022-06-23 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-06-23_final.stac-item
2022-07-16 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-07-16_final.stac-item
2022-08-05 12:15:11	ga_s2am_ard_3-2-1_49JFM_2022-08-05_final.stac-item
2022-09-01 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-09-01_final.stac-item
2022-09-11 12:05:40	ga_s2am_ard_3-2-1_49JGK_2022-09-11_final.stac-item
2022-09-14 12:14:37	ga_s2am_ard_3-2-1_49KGP_2022-09-14_final.stac-item
2022-10-28 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-10-28_final.stac-item
2023-01-13 11:47:07	ga_s2am_ard_3-2-1_50HMH_2023-01-13_final.stac-item
2023-01-26 11:57:17	ga_s2am_ard_3-2-1_50HMG_2023-01-26_final
2023-02-08 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-02-08_final
2023-02-11 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-11_nrt.stac-item
2023-02-11 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-11_final
2023-02-11 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-11_nrt.stac-item
2023-02-11 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-11_final
2023-02-18 12:05:09	ga_s2am_ard_3-2-1_49JGL_2023-02-18_nrt.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_nrt.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_final
2023-05-16 11:56:41	ga_s2am_ard_3-2-1_50HLK_2023-05-16_final
2023-05-26 11:56:43	ga_s2am_ard_3-2-1_50HLK_2023-05-26_final
2023-08-30 12:15:01	ga_s2am_ard_3-2-1_49JGM_2023-08-30_final
2023-09-26 12:05:03	ga_s2am_ard_3-2-1_49JGM_2023-09-26_final
2023-09-26 12:05:17	ga_s2am_ard_3-2-1_49JGL_2023-09-26_final
2023-11-28 12:13:47	ga_s2am_ard_3-2-1_49KHR_2023-11-28_final
2023-12-09 11:47:04	ga_s2am_ard_3-2-1_50HMH_2023-12-09_final
2023-12-25 12:03:56	ga_s2am_ard_3-2-1_49KHR_2023-12-25_final
2024-01-07 12:14:52	ga_s2am_ard_3-2-1_49JGM_2024-01-07_final
2024-01-14 12:04:54	ga_s2am_ard_3-2-1_49JGM_2024-01-14_final
2024-03-21 11:56:45	ga_s2am_ard_3-2-1_50HLK_2024-03-21_final
2024-04-03 12:03:57	ga_s2am_ard_3-2-1_49KHR_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

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