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
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_50JKT_2015-12-27_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_50JKQ_2016-01-26_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_50JLQ_2016-05-05_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JLR_2016-06-14_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49KHS_2016-08-23_final
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JKQ_2016-09-02_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLQ_2016-09-12_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HLG_2016-11-05_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HLG_2016-11-15_final
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMH_2016-12-05_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HLG_2016-12-25_final
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50JLQ_2017-01-07_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50JKR_2017-01-20_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50HMJ_2017-03-08_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JLQ_2017-04-07_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGK_2017-06-29_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2017-07-09_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JLR_2017-07-09_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KHQ_2017-07-12_final.stac-item
2017-07-19 12:03:48	ga_s2am_ard_3-2-1_49KHQ_2017-07-19_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_50JLR_2017-10-27_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-11-19_final.stac-item
2017-12-09 12:14:36	ga_s2am_ard_3-2-1_49JFN_2017-12-09_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49JGK_2018-04-15_final.stac-item
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JKR_2018-04-15_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JLR_2018-05-05_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKR_2018-06-24_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KHP_2018-09-25_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JLR_2018-10-29_final.stac-item
2018-12-08 11:55:04	ga_s2am_ard_3-2-1_50JLR_2018-12-08_final.stac-item
2019-01-17 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2019-01-17_final.stac-item
2019-01-27 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-01-27_final.stac-item
2019-02-09 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2019-02-09_final.stac-item
2019-02-16 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-02-16_final.stac-item
2019-03-01 12:05:02	ga_s2am_ard_3-2-1_50JKR_2019-03-01_final.stac-item
2019-03-18 11:55:10	ga_s2am_ard_3-2-1_50JLR_2019-03-18_final.stac-item
2019-03-31 12:05:05	ga_s2am_ard_3-2-1_50JLR_2019-03-31_final.stac-item
2019-03-31 12:05:12	ga_s2am_ard_3-2-1_50JLR_2019-03-31_final.stac-item
2019-05-30 12:05:11	ga_s2am_ard_3-2-1_50JLR_2019-05-30_final.stac-item
2019-06-19 12:05:12	ga_s2am_ard_3-2-1_50JLR_2019-06-19_final.stac-item
2019-07-13 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-07-13_final.stac-item
2019-09-14 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2019-09-14_final.stac-item
2019-10-27 12:05:08	ga_s2am_ard_3-2-1_50JLR_2019-10-27_final.stac-item
2019-11-03 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2019-11-03_final.stac-item
2020-01-22 11:55:06	ga_s2am_ard_3-2-1_50JLR_2020-01-22_final.stac-item
2020-05-14 12:05:17	ga_s2am_ard_3-2-1_50JKR_2020-05-14_final.stac-item
2020-08-26 11:47:19	ga_s2am_ard_3-2-1_50HLH_2020-08-26_final.stac-item
2020-09-05 11:46:58	ga_s2am_ard_3-2-1_50HQH_2020-09-05_final.stac-item
2020-10-04 12:14:22	ga_s2am_ard_3-2-1_49KHP_2020-10-04_final.stac-item
2020-11-20 12:05:11	ga_s2am_ard_3-2-1_50JLR_2020-11-20_final.stac-item
2020-11-24 11:46:55	ga_s2am_ard_3-2-1_50HQH_2020-11-24_final.stac-item
2020-12-27 11:55:12	ga_s2am_ard_3-2-1_50JLR_2020-12-27_final.stac-item
2021-01-22 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-01-22_final
2021-04-19 12:05:01	ga_s2am_ard_3-2-1_50JLR_2021-04-19_final.stac-item
2021-05-23 11:46:54	ga_s2am_ard_3-2-1_50HQH_2021-05-23_final.stac-item
2021-08-11 11:47:17	ga_s2am_ard_3-2-1_50HLH_2021-08-11_final.stac-item
2021-08-24 11:55:00	ga_s2am_ard_3-2-1_50JLS_2021-08-24_final.stac-item
2021-08-24 11:57:25	ga_s2am_ard_3-2-1_50HLG_2021-08-24_final
2021-09-13 11:54:59	ga_s2am_ard_3-2-1_50JLS_2021-09-13_final.stac-item
2021-10-23 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2021-10-23_final.stac-item
2021-11-18 12:14:21	ga_s2am_ard_3-2-1_49KHP_2021-11-18_final.stac-item
2021-11-22 11:57:23	ga_s2am_ard_3-2-1_50HLG_2021-11-22_final
2021-12-08 12:14:20	ga_s2am_ard_3-2-1_49KHP_2021-12-08_final.stac-item
2021-12-18 12:14:21	ga_s2am_ard_3-2-1_49KHP_2021-12-18_final.stac-item
2022-01-17 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-01-17_final.stac-item
2022-01-21 11:54:58	ga_s2am_ard_3-2-1_50JLS_2022-01-21_final.stac-item
2022-02-20 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2022-02-20_final.stac-item
2022-02-23 12:04:25	ga_s2am_ard_3-2-1_49KGP_2022-02-23_final.stac-item
2022-03-05 12:05:07	ga_s2am_ard_3-2-1_50JLR_2022-03-05_final.stac-item
2022-03-12 11:55:17	ga_s2am_ard_3-2-1_50JLR_2022-03-12_final.stac-item
2022-03-22 11:55:01	ga_s2am_ard_3-2-1_50JLS_2022-03-22_final.stac-item
2022-06-06 12:14:29	ga_s2am_ard_3-2-1_49KHP_2022-06-06_final.stac-item
2022-06-30 11:56:27	ga_s2am_ard_3-2-1_50JKM_2022-06-30_final.stac-item
2022-08-22 12:05:21	ga_s2am_ard_3-2-1_49JFM_2022-08-22_final.stac-item
2022-09-01 12:05:06	ga_s2am_ard_3-2-1_50JLS_2022-09-01_final.stac-item
2022-09-11 12:05:19	ga_s2am_ard_3-2-1_50JLR_2022-09-11_final.stac-item
2022-09-24 12:14:28	ga_s2am_ard_3-2-1_49KHP_2022-09-24_final.stac-item
2022-10-28 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-10-28_final.stac-item
2022-10-31 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-10-31_final.stac-item
2022-12-24 11:46:51	ga_s2am_ard_3-2-1_50HQH_2022-12-24_final.stac-item
2023-01-16 11:55:09	ga_s2am_ard_3-2-1_50JLR_2023-01-16_final.stac-item
2023-02-18 12:04:50	ga_s2am_ard_3-2-1_50JLS_2023-02-18_nrt.stac-item
2023-02-19 11:37:23	ga_s2am_ard_3-2-1_50HNG_2023-02-19_final
2023-04-12 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-04-12_final
2023-05-12 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-05-12_final
2023-07-11 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-07-11_final
2023-08-10 12:14:25	ga_s2am_ard_3-2-1_49KHP_2023-08-10_final
2023-10-26 12:05:08	ga_s2am_ard_3-2-1_50JLR_2023-10-26_final
2023-11-05 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-11-05_final
2023-11-12 11:55:12	ga_s2am_ard_3-2-1_50JLR_2023-11-12_final
2023-11-25 12:05:03	ga_s2am_ard_3-2-1_50JLR_2023-11-25_final
2023-12-02 11:55:05	ga_s2am_ard_3-2-1_50JLR_2023-12-02_final
2023-12-05 12:05:01	ga_s2am_ard_3-2-1_50JLR_2023-12-05_final
2023-12-12 11:55:08	ga_s2am_ard_3-2-1_50JLR_2023-12-12_final
2023-12-19 11:46:49	ga_s2am_ard_3-2-1_50HQH_2023-12-19_final
2023-12-22 11:55:09	ga_s2am_ard_3-2-1_50JLR_2023-12-22_final
2024-01-28 11:46:48	ga_s2am_ard_3-2-1_50HQH_2024-01-28_final
2024-02-07 11:46:49	ga_s2am_ard_3-2-1_50HQH_2024-02-07_final
2024-02-20 11:55:11	ga_s2am_ard_3-2-1_50JLR_2024-02-20_final
2024-03-01 11:55:13	ga_s2am_ard_3-2-1_50JLR_2024-03-01_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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