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
2015-11-20 12:14:39	ga_s2am_ard_3-2-1_49JGN_2015-11-20_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPK_2015-12-08_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPG_2015-12-21_final.stac-item
2016-04-15 12:05:35	ga_s2am_ard_3-2-1_50JKN_2016-04-15_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_49JGK_2016-05-05_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HQG_2016-05-16_final
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50HMJ_2016-05-22_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HMK_2016-06-18_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JKP_2016-08-23_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHP_2016-08-26_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HQK_2017-01-24_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HLJ_2017-02-26_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JGN_2017-06-02_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_50HPK_2017-06-20_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HPJ_2017-11-07_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HQH_2017-11-07_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HNJ_2017-12-10_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGR_2017-12-19_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50JKM_2017-12-23_final.stac-item
2018-01-15 12:04:34	ga_s2am_ard_3-2-1_49JHM_2018-01-15_final.stac-item
2018-02-07 12:14:38	ga_s2am_ard_3-2-1_49JGL_2018-02-07_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50JKP_2018-02-21_final.stac-item
2018-03-07 11:36:09	ga_s2am_ard_3-2-1_50HPK_2018-03-07_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50HQK_2018-03-17_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HMJ_2018-03-20_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50HPH_2018-04-26_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JGJ_2018-07-04_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HNH_2018-07-08_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JGL_2018-09-02_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-25_final.stac-item
2019-01-14 11:47:10	ga_s2am_ard_3-2-1_50HLH_2019-01-14_final.stac-item
2019-02-26 11:56:36	ga_s2am_ard_3-2-1_50HLK_2019-02-26_final.stac-item
2019-03-12 11:36:29	ga_s2am_ard_3-2-1_50HQK_2019-03-12_final.stac-item
2019-03-18 11:57:03	ga_s2am_ard_3-2-1_50HMH_2019-03-18_final.stac-item
2019-04-10 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2019-04-10_final.stac-item
2019-05-20 12:05:15	ga_s2am_ard_3-2-1_50JKR_2019-05-20_final.stac-item
2019-05-24 11:47:13	ga_s2am_ard_3-2-1_50HMH_2019-05-24_final.stac-item
2019-05-27 11:55:49	ga_s2am_ard_3-2-1_50JKP_2019-05-27_final.stac-item
2019-08-25 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2019-08-25_final.stac-item
2019-08-28 12:04:47	ga_s2am_ard_3-2-1_49JGN_2019-08-28_final.stac-item
2019-09-10 12:15:09	ga_s2am_ard_3-2-1_49JGL_2019-09-10_final.stac-item
2019-09-14 11:55:45	ga_s2am_ard_3-2-1_50JKP_2019-09-14_final.stac-item
2019-11-06 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-11-06_final.stac-item
2019-11-06 12:06:12	ga_s2am_ard_3-2-1_50JKM_2019-11-06_final.stac-item
2019-12-09 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-12-09_final.stac-item
2019-12-10 11:47:06	ga_s2am_ard_3-2-1_50HMH_2019-12-10_final.stac-item
2019-12-27 11:37:05	ga_s2am_ard_3-2-1_50HPH_2019-12-27_final.stac-item
2020-01-12 11:57:00	ga_s2am_ard_3-2-1_50HMH_2020-01-12_final.stac-item
2020-03-05 12:04:42	ga_s2am_ard_3-2-1_49JGN_2020-03-05_final.stac-item
2020-03-09 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2020-03-09_final.stac-item
2020-05-14 12:04:51	ga_s2am_ard_3-2-1_49JGN_2020-05-14_final.stac-item
2020-07-10 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2020-07-10_final.stac-item
2020-07-24 11:36:39	ga_s2am_ard_3-2-1_50HQK_2020-07-24_final.stac-item
2020-07-30 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-07-30_final.stac-item
2020-11-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2020-11-30_final.stac-item
2021-03-03 12:15:07	ga_s2am_ard_3-2-1_49JGL_2021-03-03_final.stac-item
2021-05-26 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-05-26_final.stac-item
2021-05-26 11:57:07	ga_s2am_ard_3-2-1_50HLH_2021-05-26_final.stac-item
2021-07-31 12:15:03	ga_s2am_ard_3-2-1_49JFM_2021-07-31_final.stac-item
2021-08-04 11:56:02	ga_s2am_ard_3-2-1_50JKN_2021-08-04_final.stac-item
2021-08-10 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2021-08-10_final.stac-item
2021-09-16 12:04:44	ga_s2am_ard_3-2-1_50JKT_2021-09-16_final.stac-item
2021-10-16 12:05:02	ga_s2am_ard_3-2-1_49JHM_2021-10-16_final.stac-item
2021-12-05 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-12-05_final.stac-item
2021-12-29 11:46:42	ga_s2am_ard_3-2-1_50HMK_2021-12-29_final.stac-item
2022-01-04 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-01-04_final.stac-item
2022-01-07 12:14:10	ga_s2am_ard_3-2-1_49KHQ_2022-01-07_final.stac-item
2022-01-18 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2022-01-18_final.stac-item
2022-01-28 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-01-28_final.stac-item
2022-02-16 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-02-16_final.stac-item
2022-03-08 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-03-08_final.stac-item
2022-10-08 11:55:53	ga_s2am_ard_3-2-1_50JKP_2022-10-08_final.stac-item
2022-11-07 11:56:40	ga_s2am_ard_3-2-1_50HMK_2022-11-07_final.stac-item
2022-12-14 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-12-14_final.stac-item
2023-01-23 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2023-01-23_final.stac-item
2023-02-02 11:47:07	ga_s2am_ard_3-2-1_50HMH_2023-02-02_final
2023-03-27 11:55:44	ga_s2am_ard_3-2-1_50JKP_2023-03-27_final
2023-04-19 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2023-04-19_final
2023-04-30 11:37:26	ga_s2am_ard_3-2-1_50HNG_2023-04-30_final
2023-05-09 12:03:44	ga_s2am_ard_3-2-1_49KHS_2023-05-09_final
2023-05-19 12:04:48	ga_s2am_ard_3-2-1_49JGN_2023-05-19_final
2023-07-08 12:05:20	ga_s2am_ard_3-2-1_49JGL_2023-07-08_final
2023-07-22 11:46:34	ga_s2am_ard_3-2-1_50HQK_2023-07-22_final
2023-10-06 12:04:58	ga_s2am_ard_3-2-1_50JKS_2023-10-06_final
2023-12-12 11:56:32	ga_s2am_ard_3-2-1_50HMK_2023-12-12_final
2023-12-12 11:56:35	ga_s2am_ard_3-2-1_50HLK_2023-12-12_final
2023-12-15 12:04:24	ga_s2am_ard_3-2-1_49KHP_2023-12-15_final
2023-12-22 11:56:36	ga_s2am_ard_3-2-1_50HLK_2023-12-22_final
2024-01-18 11:46:46	ga_s2am_ard_3-2-1_50HMJ_2024-01-18_final
2024-01-31 11:57:01	ga_s2am_ard_3-2-1_50HMH_2024-01-31_final
2024-02-13 12:05:23	ga_s2am_ard_3-2-1_50JKQ_2024-02-13_final
2024-02-17 11:47:12	ga_s2am_ard_3-2-1_50HLH_2024-02-17_final
2024-03-24 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2024-03-24_final
2024-03-24 12:05:30	ga_s2am_ard_3-2-1_49JGK_2024-03-24_final
2024-03-25 11:36:35	ga_s2am_ard_3-2-1_50HQK_2024-03-25_final
2024-03-25 11:37:00	ga_s2am_ard_3-2-1_50HPJ_2024-03-25_final
2024-03-28 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2024-03-28_final
2024-04-17 11:47:09	ga_s2am_ard_3-2-1_50HNH_2024-04-17_final
2024-05-06 12:14:59	ga_s2am_ard_3-2-1_49JGM_2024-05-06_final
2024-05-17 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2024-05-17_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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