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 12:09:42	ga_s2am_ard_3-2-1_49KHQ_2015-10-21_final.stac-item
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HQH_2015-10-22_final.stac-item
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KGP_2015-11-30_final.stac-item
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPH_2015-12-08_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGQ_2016-03-09_final.stac-item
2016-05-12 11:56:32	ga_s2am_ard_3-2-1_50HLK_2016-05-12_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHP_2016-08-26_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KHR_2016-09-25_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KGQ_2016-11-21_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KGQ_2016-11-24_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHR_2016-12-21_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49KHR_2017-01-20_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49KHR_2017-01-30_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49KHQ_2017-02-19_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KGR_2017-08-01_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KGP_2017-09-30_final.stac-item
2019-01-13 12:14:52	ga_s2am_ard_3-2-1_49JGM_2019-01-13_final.stac-item
2019-01-27 11:56:11	ga_s2am_ard_3-2-1_50JKM_2019-01-27_final.stac-item
2019-01-30 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2019-01-30_final.stac-item
2019-01-30 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2019-01-30_final.stac-item
2019-02-19 12:06:00	ga_s2am_ard_3-2-1_50JLM_2019-02-19_final.stac-item
2019-02-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2019-02-22_final.stac-item
2019-03-21 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2019-03-21_final.stac-item
2019-04-03 12:14:42	ga_s2am_ard_3-2-1_49JGN_2019-04-03_final.stac-item
2019-05-14 11:47:06	ga_s2am_ard_3-2-1_50HPH_2019-05-14_final.stac-item
2019-05-17 11:57:13	ga_s2am_ard_3-2-1_50HLH_2019-05-17_final.stac-item
2019-08-01 12:14:46	ga_s2am_ard_3-2-1_49JGN_2019-08-01_final.stac-item
2019-12-16 12:05:59	ga_s2am_ard_3-2-1_50JLM_2019-12-16_final.stac-item
2020-02-04 12:05:36	ga_s2am_ard_3-2-1_49JGJ_2020-02-04_final.stac-item
2020-03-06 11:37:02	ga_s2am_ard_3-2-1_50HPH_2020-03-06_final.stac-item
2020-03-19 11:46:50	ga_s2am_ard_3-2-1_50HQH_2020-03-19_final.stac-item
2020-04-17 12:13:54	ga_s2am_ard_3-2-1_49KHR_2020-04-17_final.stac-item
2020-07-20 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-07-20_final.stac-item
2020-07-26 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-07-26_final.stac-item
2020-08-15 12:14:02	ga_s2am_ard_3-2-1_49KHR_2020-08-15_final.stac-item
2020-09-04 12:15:15	ga_s2am_ard_3-2-1_49JGL_2020-09-04_final.stac-item
2020-09-12 11:37:10	ga_s2am_ard_3-2-1_50HPH_2020-09-12_final.stac-item
2020-09-18 11:56:30	ga_s2am_ard_3-2-1_50JLL_2020-09-18_final.stac-item
2020-09-18 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2020-09-18_final.stac-item
2020-09-22 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2020-09-22_final.stac-item
2020-09-22 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-09-22_final.stac-item
2020-10-01 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2020-10-01_final.stac-item
2020-11-13 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2020-11-13_final.stac-item
2020-12-03 12:13:57	ga_s2am_ard_3-2-1_49KGR_2020-12-03_final.stac-item
2021-08-24 11:56:42	ga_s2am_ard_3-2-1_50HLK_2021-08-24_final.stac-item
2021-08-24 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-24_final.stac-item
2021-12-06 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2021-12-06_final.stac-item
2021-12-12 11:57:08	ga_s2am_ard_3-2-1_50HLH_2021-12-12_final.stac-item
2021-12-18 12:14:46	ga_s2am_ard_3-2-1_49JFN_2021-12-18_final.stac-item
2022-01-01 11:56:42	ga_s2am_ard_3-2-1_50HLK_2022-01-01_final.stac-item
2022-01-11 11:56:12	ga_s2am_ard_3-2-1_50JLM_2022-01-11_final.stac-item
2022-01-11 11:56:27	ga_s2am_ard_3-2-1_50JLL_2022-01-11_final.stac-item
2022-01-28 11:47:02	ga_s2am_ard_3-2-1_50HPH_2022-01-28_final.stac-item
2022-02-03 12:06:04	ga_s2am_ard_3-2-1_50JLM_2022-02-03_final.stac-item
2022-02-10 11:56:10	ga_s2am_ard_3-2-1_50JLM_2022-02-10_final.stac-item
2022-03-06 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-03-06_final.stac-item
2022-03-12 11:56:30	ga_s2am_ard_3-2-1_50JLL_2022-03-12_final.stac-item
2022-03-22 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-03-22_final.stac-item
2022-03-22 11:56:29	ga_s2am_ard_3-2-1_50JLL_2022-03-22_final.stac-item
2022-04-24 12:06:09	ga_s2am_ard_3-2-1_50JLM_2022-04-24_final.stac-item
2022-04-25 11:37:12	ga_s2am_ard_3-2-1_50HPH_2022-04-25_final.stac-item
2022-06-04 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-06-04_final.stac-item
2022-06-13 12:04:28	ga_s2am_ard_3-2-1_49KGQ_2022-06-13_final.stac-item
2022-06-27 11:47:15	ga_s2am_ard_3-2-1_50HPH_2022-06-27_final.stac-item
2022-06-30 11:56:38	ga_s2am_ard_3-2-1_50JLL_2022-06-30_final.stac-item
2022-06-30 11:57:19	ga_s2am_ard_3-2-1_50HMH_2022-06-30_final.stac-item
2022-07-10 11:57:08	ga_s2am_ard_3-2-1_50HLJ_2022-07-10_final.stac-item
2022-07-23 12:04:29	ga_s2am_ard_3-2-1_49KGQ_2022-07-23_final.stac-item
2022-08-19 11:56:42	ga_s2am_ard_3-2-1_50HNK_2022-08-19_final.stac-item
2022-08-26 11:47:01	ga_s2am_ard_3-2-1_50HPJ_2022-08-26_final
2022-09-18 11:56:34	ga_s2am_ard_3-2-1_50JLL_2022-09-18_final.stac-item
2022-10-11 12:04:40	ga_s2am_ard_3-2-1_50JKT_2022-10-11_final.stac-item
2022-12-14 11:47:02	ga_s2am_ard_3-2-1_50HPH_2022-12-14_final.stac-item
2023-03-07 11:57:05	ga_s2am_ard_3-2-1_50HLH_2023-03-07_final
2023-03-25 12:50:59	ga_s2am_ard_3-2-1_48LWP_2023-03-25_final
2023-05-16 11:56:12	ga_s2am_ard_3-2-1_50JLM_2023-05-16_final
2023-05-16 11:56:31	ga_s2am_ard_3-2-1_50HNK_2023-05-16_final
2023-05-16 11:57:23	ga_s2am_ard_3-2-1_50HLG_2023-05-16_final
2023-07-02 11:46:58	ga_s2am_ard_3-2-1_50HQH_2023-07-02_final
2023-07-02 11:47:07	ga_s2am_ard_3-2-1_50HPH_2023-07-02_final
2023-07-22 11:47:14	ga_s2am_ard_3-2-1_50HMH_2023-07-22_final
2023-08-11 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-08-11_final
2023-08-14 11:56:42	ga_s2am_ard_3-2-1_50HMK_2023-08-14_final
2023-08-14 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-08-14_final
2023-08-24 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2023-08-24_final
2023-09-09 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2023-09-09_final
2023-11-02 11:56:24	ga_s2am_ard_3-2-1_50JLL_2023-11-02_final
2023-11-09 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2023-11-09_final
2023-11-12 11:56:25	ga_s2am_ard_3-2-1_50JLL_2023-11-12_final
2023-12-08 12:14:21	ga_s2am_ard_3-2-1_49KGP_2023-12-08_final
2024-01-11 11:56:35	ga_s2am_ard_3-2-1_50HLK_2024-01-11_final
2024-01-31 11:56:21	ga_s2am_ard_3-2-1_50JLL_2024-01-31_final
2024-02-07 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2024-02-07_final
2024-02-10 11:56:22	ga_s2am_ard_3-2-1_50JLL_2024-02-10_final
2024-02-27 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2024-02-27_final
2024-03-11 11:56:26	ga_s2am_ard_3-2-1_50JLL_2024-03-11_final
2024-03-17 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2024-03-17_final
2024-03-31 11:56:25	ga_s2am_ard_3-2-1_50JLL_2024-03-31_final
2024-05-14 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2024-05-14_nrt
2024-05-20 11:56:31	ga_s2am_ard_3-2-1_50HNK_2024-05-20_nrt

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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