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_50HQH_2016-01-07_final.stac-item
2016-03-29 12:13:41	ga_s2am_ard_3-2-1_49KGR_2016-03-29_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HLG_2016-04-02_final
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JGL_2016-06-24_final.stac-item
2016-07-27 12:13:48	ga_s2am_ard_3-2-1_49KGR_2016-07-27_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JGL_2016-08-23_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HMH_2016-12-15_final.stac-item
2017-03-28 11:56:02	ga_s2am_ard_3-2-1_50HNK_2017-03-28_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49JGN_2017-04-23_final.stac-item
2017-05-17 11:56:36	ga_s2am_ard_3-2-1_50HMH_2017-05-17_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HQK_2017-05-24_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JGL_2017-06-02_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50HLK_2017-06-06_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_49JHM_2017-07-19_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KGQ_2017-08-01_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JGL_2017-08-18_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50HMJ_2018-01-12_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49JGK_2018-01-25_final.stac-item
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-04-08_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KGR_2018-04-28_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HNH_2018-06-28_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50HNK_2018-07-01_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGL_2018-07-17_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGR_2018-09-05_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHR_2018-09-05_final.stac-item
2018-09-15 12:14:38	ga_s2am_ard_3-2-1_49JGM_2018-09-15_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HMJ_2018-09-19_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49JGK_2018-11-04_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HMK_2018-11-05_final.stac-item
2018-11-14 12:13:53	ga_s2am_ard_3-2-1_49KGR_2018-11-14_final.stac-item
2018-12-01 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-01_final.stac-item
2018-12-02 11:36:29	ga_s2am_ard_3-2-1_50HPK_2018-12-02_final.stac-item
2018-12-25 11:46:55	ga_s2am_ard_3-2-1_50HPH_2018-12-25_final.stac-item
2019-01-07 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-01-07_final.stac-item
2019-01-21 11:36:34	ga_s2am_ard_3-2-1_50HPK_2019-01-21_final.stac-item
2019-01-31 11:37:03	ga_s2am_ard_3-2-1_50HPH_2019-01-31_final.stac-item
2019-02-10 11:36:31	ga_s2am_ard_3-2-1_50HQK_2019-02-10_final.stac-item
2019-03-04 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2019-03-04_final.stac-item
2019-03-25 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2019-03-25_final.stac-item
2019-04-03 12:14:57	ga_s2am_ard_3-2-1_49JGM_2019-04-03_final.stac-item
2019-04-21 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-04-21_final.stac-item
2019-08-28 12:05:16	ga_s2am_ard_3-2-1_49JGL_2019-08-28_final.stac-item
2019-09-27 12:05:16	ga_s2am_ard_3-2-1_49JGL_2019-09-27_final.stac-item
2019-10-21 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2019-10-21_final.stac-item
2019-10-24 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2019-10-24_final.stac-item
2019-11-06 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-11-06_final.stac-item
2019-11-29 12:13:58	ga_s2am_ard_3-2-1_49KGR_2019-11-29_final.stac-item
2019-12-29 12:14:36	ga_s2am_ard_3-2-1_49JGN_2019-12-29_final.stac-item
2020-03-15 12:04:39	ga_s2am_ard_3-2-1_49JHN_2020-03-15_final.stac-item
2020-03-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2020-03-25_final.stac-item
2020-04-07 12:14:53	ga_s2am_ard_3-2-1_49JGM_2020-04-07_final.stac-item
2020-06-06 12:15:06	ga_s2am_ard_3-2-1_49JFM_2020-06-06_final.stac-item
2020-07-13 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2020-07-13_final.stac-item
2020-08-02 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-08-02_final.stac-item
2020-08-22 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-08-22_final.stac-item
2020-10-18 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-10-18_final.stac-item
2021-03-10 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-03-10_final.stac-item
2021-03-30 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2021-03-30_final.stac-item
2021-03-30 12:05:12	ga_s2am_ard_3-2-1_49JGL_2021-03-30_final.stac-item
2021-04-22 12:14:37	ga_s2am_ard_3-2-1_49JGN_2021-04-22_final.stac-item
2021-05-19 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-05-19_final.stac-item
2021-07-15 11:57:09	ga_s2am_ard_3-2-1_50HMH_2021-07-15_final.stac-item
2021-08-11 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2021-08-11_final.stac-item
2021-11-16 11:37:04	ga_s2am_ard_3-2-1_50HQH_2021-11-16_final.stac-item
2021-11-29 11:46:30	ga_s2am_ard_3-2-1_50HQK_2021-11-29_final.stac-item
2021-12-09 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2021-12-09_final.stac-item
2021-12-16 11:37:11	ga_s2am_ard_3-2-1_50HQG_2021-12-16_final
2022-01-07 12:15:12	ga_s2am_ard_3-2-1_49JGL_2022-01-07_final.stac-item
2022-01-27 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-01-27_final.stac-item
2022-02-27 11:46:33	ga_s2am_ard_3-2-1_50HQK_2022-02-27_final.stac-item
2022-03-05 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-03-05_final.stac-item
2022-10-08 11:57:12	ga_s2am_ard_3-2-1_50HMH_2022-10-08_final.stac-item
2022-10-11 12:04:48	ga_s2am_ard_3-2-1_49JHN_2022-10-11_final.stac-item
2022-10-18 11:57:12	ga_s2am_ard_3-2-1_50HLH_2022-10-18_final.stac-item
2022-11-10 12:05:00	ga_s2am_ard_3-2-1_49JHM_2022-11-10_final.stac-item
2022-11-13 12:13:58	ga_s2am_ard_3-2-1_49KHR_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
2022-12-24 11:47:08	ga_s2am_ard_3-2-1_50HMH_2022-12-24_final.stac-item
2023-01-12 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-01-12_final.stac-item
2023-02-22 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2023-02-22_nrt.stac-item
2023-02-22 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2023-02-22_final
2023-04-19 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-04-19_final
2023-05-23 11:47:20	ga_s2am_ard_3-2-1_50HPG_2023-05-23_final
2023-07-01 12:15:15	ga_s2am_ard_3-2-1_49JGL_2023-07-01_final
2023-07-31 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-07-31_final
2023-08-14 11:56:42	ga_s2am_ard_3-2-1_50HMK_2023-08-14_final
2023-08-27 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2023-08-27_final
2023-10-20 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2023-10-20_final
2023-10-20 11:47:10	ga_s2am_ard_3-2-1_50HMH_2023-10-20_final
2023-10-29 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-10-29_final
2023-11-28 12:15:03	ga_s2am_ard_3-2-1_49JGL_2023-11-28_final
2024-01-07 12:14:52	ga_s2am_ard_3-2-1_49JGM_2024-01-07_final
2024-01-08 11:47:05	ga_s2am_ard_3-2-1_50HMH_2024-01-08_final
2024-01-27 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2024-01-27_final
2024-02-13 12:04:25	ga_s2am_ard_3-2-1_49KHP_2024-02-13_final
2024-02-14 11:36:49	ga_s2am_ard_3-2-1_50HPJ_2024-02-14_final
2024-03-01 11:56:44	ga_s2am_ard_3-2-1_50HLK_2024-03-01_final
2024-03-04 12:03:45	ga_s2am_ard_3-2-1_49KHS_2024-03-04_final
2024-03-14 12:04:18	ga_s2am_ard_3-2-1_49KGQ_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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