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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HNK_2015-11-14_final.stac-item
2015-11-24 11:56:24	ga_s2am_ard_3-2-1_50HMK_2015-11-24_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49JGN_2015-11-30_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HPH_2016-01-07_final.stac-item
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49JFM_2016-01-09_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNG_2016-03-20_final
2016-05-25 12:03:53	ga_s2am_ard_3-2-1_49KHR_2016-05-25_final.stac-item
2016-06-17 12:13:46	ga_s2am_ard_3-2-1_49KHR_2016-06-17_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JKN_2016-07-01_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49JGN_2016-07-14_final.stac-item
2016-07-17 12:13:25	ga_s2am_ard_3-2-1_49KHR_2016-07-17_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGP_2016-09-12_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HNG_2016-12-15_final
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HQJ_2016-12-15_final.stac-item
2017-01-04 11:46:21	ga_s2am_ard_3-2-1_50HNK_2017-01-04_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HNK_2017-01-14_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HPK_2017-02-03_final.stac-item
2017-07-06 11:56:07	ga_s2am_ard_3-2-1_50HNK_2017-07-06_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KHQ_2017-07-09_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KGP_2017-07-29_final.stac-item
2017-08-19 11:30:19	ga_s2am_ard_3-2-1_50HQK_2017-08-19_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50HLH_2018-02-21_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50HNH_2018-04-09_final.stac-item
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JKN_2018-04-15_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-10-02_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-10-05_final.stac-item
2018-11-14 12:15:05	ga_s2am_ard_3-2-1_49JGL_2018-11-14_final.stac-item
2018-11-25 11:46:30	ga_s2am_ard_3-2-1_50HNK_2018-11-25_final.stac-item
2018-12-04 12:14:18	ga_s2am_ard_3-2-1_49KGP_2018-12-04_final.stac-item
2019-01-04 11:46:32	ga_s2am_ard_3-2-1_50HNK_2019-01-04_final.stac-item
2019-02-03 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2019-02-03_final.stac-item
2019-04-11 11:36:50	ga_s2am_ard_3-2-1_50HQJ_2019-04-11_final.stac-item
2019-04-24 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-04-24_final.stac-item
2019-06-19 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-06-19_final.stac-item
2019-08-11 12:15:00	ga_s2am_ard_3-2-1_49JGM_2019-08-11_final.stac-item
2019-08-28 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2019-08-28_final.stac-item
2019-10-07 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-10-07_final.stac-item
2019-11-07 11:37:05	ga_s2am_ard_3-2-1_50HQH_2019-11-07_final.stac-item
2019-11-29 12:13:54	ga_s2am_ard_3-2-1_49KHR_2019-11-29_final.stac-item
2020-01-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2020-01-08_final.stac-item
2020-01-12 11:55:54	ga_s2am_ard_3-2-1_50JKN_2020-01-12_final.stac-item
2020-01-18 12:14:21	ga_s2am_ard_3-2-1_49KGP_2020-01-18_final.stac-item
2020-01-19 11:46:24	ga_s2am_ard_3-2-1_50HQK_2020-01-19_final.stac-item
2020-02-08 11:46:29	ga_s2am_ard_3-2-1_50HNK_2020-02-08_final.stac-item
2020-03-22 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2020-03-22_final.stac-item
2020-04-01 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2020-04-01_final.stac-item
2020-04-17 12:14:27	ga_s2am_ard_3-2-1_49KGP_2020-04-17_final.stac-item
2020-07-03 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-07-03_final.stac-item
2020-11-17 11:56:39	ga_s2am_ard_3-2-1_50HMK_2020-11-17_final.stac-item
2020-11-30 12:04:31	ga_s2am_ard_3-2-1_49KGP_2020-11-30_final.stac-item
2020-12-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2020-12-23_final.stac-item
2021-01-29 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-01-29_final.stac-item
2021-03-24 11:46:28	ga_s2am_ard_3-2-1_50HQK_2021-03-24_final.stac-item
2021-04-22 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2021-04-22_final.stac-item
2021-05-19 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-05-19_final
2021-05-23 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-05-23_final.stac-item
2021-05-26 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-05-26_final.stac-item
2021-07-01 12:14:00	ga_s2am_ard_3-2-1_49KGR_2021-07-01_final.stac-item
2021-07-18 12:05:15	ga_s2am_ard_3-2-1_50JKR_2021-07-18_final.stac-item
2021-08-01 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2021-08-01_final.stac-item
2021-08-10 12:15:02	ga_s2am_ard_3-2-1_49JFM_2021-08-10_final.stac-item
2021-08-17 12:05:03	ga_s2am_ard_3-2-1_49JGM_2021-08-17_final.stac-item
2021-09-03 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-03_final.stac-item
2021-09-06 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-09-06_final.stac-item
2021-09-09 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-09-09_final.stac-item
2021-10-16 12:04:33	ga_s2am_ard_3-2-1_49KHP_2021-10-16_final.stac-item
2021-11-25 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-11-25_final.stac-item
2021-11-28 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-11-28_final.stac-item
2021-12-16 11:37:13	ga_s2am_ard_3-2-1_50HPH_2021-12-16_final.stac-item
2021-12-29 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2021-12-29_final.stac-item
2022-04-27 12:14:46	ga_s2am_ard_3-2-1_49JGN_2022-04-27_final.stac-item
2022-04-28 11:47:19	ga_s2am_ard_3-2-1_50HLH_2022-04-28_final.stac-item
2022-05-07 12:13:59	ga_s2am_ard_3-2-1_49KHR_2022-05-07_final.stac-item
2022-06-03 12:05:34	ga_s2am_ard_3-2-1_50JKQ_2022-06-03_final.stac-item
2022-06-26 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-06-26_final.stac-item
2022-08-02 12:05:07	ga_s2am_ard_3-2-1_49JHM_2022-08-02_final.stac-item
2022-08-22 12:04:12	ga_s2am_ard_3-2-1_49KHR_2022-08-22_final.stac-item
2022-09-11 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-09-11_final.stac-item
2022-10-28 11:56:43	ga_s2am_ard_3-2-1_50HLK_2022-10-28_final.stac-item
2023-01-13 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2023-01-13_final.stac-item
2023-01-22 12:13:50	ga_s2am_ard_3-2-1_49KHR_2023-01-22_final.stac-item
2023-02-18 12:05:09	ga_s2am_ard_3-2-1_49JGL_2023-02-18_final
2023-03-01 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2023-03-01_final
2023-03-04 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-03-04_final
2023-05-16 11:56:00	ga_s2am_ard_3-2-1_50JKN_2023-05-16_final
2023-06-25 11:57:09	ga_s2am_ard_3-2-1_50HMH_2023-06-25_final
2023-07-02 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2023-07-02_final
2023-07-08 12:05:46	ga_s2am_ard_3-2-1_50JKP_2023-07-08_final
2023-08-27 12:06:01	ga_s2am_ard_3-2-1_50JKN_2023-08-27_final
2023-09-07 11:37:12	ga_s2am_ard_3-2-1_50HPH_2023-09-07_final
2023-09-16 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-09-16_final
2023-09-30 11:46:36	ga_s2am_ard_3-2-1_50HPK_2023-09-30_final
2023-11-18 12:14:43	ga_s2am_ard_3-2-1_49JFN_2023-11-18_final
2023-12-02 11:55:51	ga_s2am_ard_3-2-1_50JKN_2023-12-02_final
2023-12-22 11:57:05	ga_s2am_ard_3-2-1_50HLH_2023-12-22_final
2024-01-08 11:46:58	ga_s2am_ard_3-2-1_50HPH_2024-01-08_final
2024-01-18 11:47:01	ga_s2am_ard_3-2-1_50HMH_2024-01-18_final
2024-02-06 12:14:23	ga_s2am_ard_3-2-1_49KGP_2024-02-06_final
2024-02-23 12:05:13	ga_s2am_ard_3-2-1_49JGL_2024-02-23_final
2024-03-14 12:04:31	ga_s2am_ard_3-2-1_49KGP_2024-03-14_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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