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
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49JGM_2015-12-30_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGN_2016-01-26_final.stac-item
2016-02-12 11:56:22	ga_s2am_ard_3-2-1_50HLK_2016-02-12_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HNG_2016-06-18_final
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HPJ_2016-06-18_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50HMK_2016-07-21_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HPK_2016-09-26_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49JGN_2017-01-03_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HLH_2017-04-07_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HNG_2017-04-14_final
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGN_2017-08-21_final.stac-item
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_49JHM_2017-08-28_final.stac-item
2017-09-10 12:13:33	ga_s2am_ard_3-2-1_49JFM_2017-09-10_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHR_2017-09-27_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50HPJ_2017-11-27_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_50HPK_2018-01-06_final.stac-item
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_50HQJ_2018-02-15_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HMJ_2018-03-13_final.stac-item
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49JGM_2018-05-08_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNJ_2018-05-09_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50HLH_2018-06-11_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HNJ_2018-10-16_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KHR_2018-11-04_final.stac-item
2018-12-22 11:37:00	ga_s2am_ard_3-2-1_50HQH_2018-12-22_final.stac-item
2019-01-13 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-01-13_final.stac-item
2019-01-30 12:05:12	ga_s2am_ard_3-2-1_49JGL_2019-01-30_final.stac-item
2019-02-09 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-02-09_final.stac-item
2019-02-12 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-02-12_final.stac-item
2019-02-23 11:46:29	ga_s2am_ard_3-2-1_50HPK_2019-02-23_final.stac-item
2019-02-26 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2019-02-26_final.stac-item
2019-03-15 11:46:26	ga_s2am_ard_3-2-1_50HQK_2019-03-15_final.stac-item
2019-03-31 12:05:08	ga_s2am_ard_3-2-1_49JGL_2019-03-31_final.stac-item
2019-04-17 11:56:43	ga_s2am_ard_3-2-1_50HLK_2019-04-17_final.stac-item
2019-06-20 11:36:42	ga_s2am_ard_3-2-1_50HPK_2019-06-20_final.stac-item
2019-07-19 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-07-19_final.stac-item
2019-10-30 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-10-30_final.stac-item
2019-11-30 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2019-11-30_final.stac-item
2019-12-06 12:05:12	ga_s2am_ard_3-2-1_49JGL_2019-12-06_final.stac-item
2019-12-16 12:04:22	ga_s2am_ard_3-2-1_49KHP_2019-12-16_final.stac-item
2019-12-30 11:46:32	ga_s2am_ard_3-2-1_50HNK_2019-12-30_final.stac-item
2020-01-09 11:46:57	ga_s2am_ard_3-2-1_50HPH_2020-01-09_final.stac-item
2020-01-15 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2020-01-15_final.stac-item
2020-02-01 11:56:29	ga_s2am_ard_3-2-1_50HMK_2020-02-01_final.stac-item
2020-02-14 12:04:25	ga_s2am_ard_3-2-1_49KGP_2020-02-14_final.stac-item
2020-02-15 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2020-02-15_final.stac-item
2020-02-27 12:14:22	ga_s2am_ard_3-2-1_49KGP_2020-02-27_final.stac-item
2020-03-19 11:46:26	ga_s2am_ard_3-2-1_50HQK_2020-03-19_final.stac-item
2020-04-04 12:04:42	ga_s2am_ard_3-2-1_49JGN_2020-04-04_final.stac-item
2020-06-14 11:37:09	ga_s2am_ard_3-2-1_50HQH_2020-06-14_final.stac-item
2020-07-04 11:36:39	ga_s2am_ard_3-2-1_50HQK_2020-07-04_final.stac-item
2020-07-27 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-07-27_final.stac-item
2020-08-02 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-08-02_final.stac-item
2020-09-01 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-09-01_final.stac-item
2020-09-01 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-09-01_final.stac-item
2020-10-14 12:14:33	ga_s2am_ard_3-2-1_49KGP_2020-10-14_final.stac-item
2020-12-03 12:13:57	ga_s2am_ard_3-2-1_49KGR_2020-12-03_final.stac-item
2020-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2020-12-20_final.stac-item
2020-12-20 12:05:54	ga_s2am_ard_3-2-1_50JKN_2020-12-20_final.stac-item
2021-01-22 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-01-22_final.stac-item
2021-01-30 11:37:07	ga_s2am_ard_3-2-1_50HPH_2021-01-30_final.stac-item
2021-05-20 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-05-20_final
2021-06-11 12:14:22	ga_s2am_ard_3-2-1_49KHP_2021-06-11_final.stac-item
2021-07-01 12:14:43	ga_s2am_ard_3-2-1_49JGN_2021-07-01_final.stac-item
2021-09-07 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-09-07_final
2021-10-09 12:14:00	ga_s2am_ard_3-2-1_49KHR_2021-10-09_final.stac-item
2021-11-15 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-11-15_final.stac-item
2021-12-02 11:56:29	ga_s2am_ard_3-2-1_50HNK_2021-12-02_final.stac-item
2021-12-05 12:05:55	ga_s2am_ard_3-2-1_50JKN_2021-12-05_final.stac-item
2021-12-19 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-12-19_final.stac-item
2022-01-21 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2022-01-21_final.stac-item
2022-01-27 12:13:58	ga_s2am_ard_3-2-1_49KGR_2022-01-27_final.stac-item
2022-02-03 12:05:00	ga_s2am_ard_3-2-1_49JGM_2022-02-03_final.stac-item
2022-03-06 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2022-03-06_final.stac-item
2022-03-09 11:47:10	ga_s2am_ard_3-2-1_50HNH_2022-03-09_final.stac-item
2022-04-17 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-04-17_final.stac-item
2022-05-14 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-05-14_final.stac-item
2022-05-15 11:36:38	ga_s2am_ard_3-2-1_50HQK_2022-05-15_final.stac-item
2022-06-23 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-06-23_final.stac-item
2022-07-04 11:37:16	ga_s2am_ard_3-2-1_50HQH_2022-07-04_final.stac-item
2022-07-24 11:37:02	ga_s2am_ard_3-2-1_50HPJ_2022-07-24_final.stac-item
2022-08-26 11:46:50	ga_s2am_ard_3-2-1_50HNK_2022-08-26_final.stac-item
2022-09-24 12:14:48	ga_s2am_ard_3-2-1_49JGN_2022-09-24_final.stac-item
2023-01-02 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-01-02_final.stac-item
2023-02-05 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-02-05_final
2023-02-25 11:56:38	ga_s2am_ard_3-2-1_50HLK_2023-02-25_final
2023-04-13 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2023-04-13_final
2023-05-23 11:47:05	ga_s2am_ard_3-2-1_50HPH_2023-05-23_final
2023-06-08 12:04:31	ga_s2am_ard_3-2-1_49KHP_2023-06-08_final
2023-06-25 11:56:39	ga_s2am_ard_3-2-1_50HMK_2023-06-25_final
2023-07-28 12:04:51	ga_s2am_ard_3-2-1_49JGN_2023-07-28_final
2023-08-31 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-31_final
2023-09-06 12:04:51	ga_s2am_ard_3-2-1_49JGN_2023-09-06_final
2023-10-30 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-10-30_final
2023-11-05 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-11-05_final
2023-12-02 11:56:47	ga_s2am_ard_3-2-1_50HLJ_2023-12-02_final
2023-12-12 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2023-12-12_final
2024-01-04 12:04:42	ga_s2am_ard_3-2-1_49JGN_2024-01-04_final
2024-01-17 12:14:48	ga_s2am_ard_3-2-1_49JGM_2024-01-17_final
2024-03-01 11:56:14	ga_s2am_ard_3-2-1_50JKM_2024-03-01_final
2024-05-06 12:15:02	ga_s2am_ard_3-2-1_49JFM_2024-05-06_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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