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
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_50JLM_2015-10-08_final.stac-item
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_49KGR_2015-10-21_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49KHP_2015-11-30_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPJ_2015-12-21_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JKM_2016-02-15_final.stac-item
2016-03-29 12:13:41	ga_s2am_ard_3-2-1_49KHQ_2016-03-29_final.stac-item
2016-05-08 12:13:49	ga_s2am_ard_3-2-1_49KGR_2016-05-08_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KGR_2016-05-18_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_50HQG_2016-09-13_final
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLK_2016-11-28_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49KHP_2016-12-01_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JLQ_2016-12-21_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HLK_2017-02-26_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_50JKQ_2017-03-01_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KHQ_2017-03-14_final.stac-item
2017-04-03 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2017-04-03_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_50JLQ_2017-04-30_final.stac-item
2017-05-20 12:03:50	ga_s2am_ard_3-2-1_49KHQ_2017-05-20_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JHM_2017-06-29_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_50JKT_2017-06-29_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49KHR_2017-08-01_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLQ_2017-08-05_final.stac-item
2017-08-28 12:03:48	ga_s2am_ard_3-2-1_49KHQ_2017-08-28_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KHP_2018-04-28_final.stac-item
2019-01-20 12:05:19	ga_s2am_ard_3-2-1_50JLQ_2019-01-20_final.stac-item
2019-02-19 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-02-19_final.stac-item
2019-02-19 12:04:39	ga_s2am_ard_3-2-1_50JKT_2019-02-19_final.stac-item
2019-03-01 12:05:02	ga_s2am_ard_3-2-1_50JKR_2019-03-01_final.stac-item
2019-03-11 12:04:23	ga_s2am_ard_3-2-1_49KHP_2019-03-11_final.stac-item
2019-03-11 12:04:41	ga_s2am_ard_3-2-1_49JGN_2019-03-11_final.stac-item
2019-07-02 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-07-02_final.stac-item
2019-08-01 12:14:03	ga_s2am_ard_3-2-1_49KGR_2019-08-01_final.stac-item
2019-08-11 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-08-11_final.stac-item
2019-09-01 11:46:54	ga_s2am_ard_3-2-1_50HQH_2019-09-01_final.stac-item
2019-10-30 12:14:24	ga_s2am_ard_3-2-1_49KHP_2019-10-30_final.stac-item
2019-11-26 12:04:28	ga_s2am_ard_3-2-1_49KHP_2019-11-26_final.stac-item
2019-12-16 12:04:37	ga_s2am_ard_3-2-1_49JHN_2019-12-16_final.stac-item
2019-12-16 12:04:37	ga_s2am_ard_3-2-1_50JKT_2019-12-16_final.stac-item
2020-01-25 12:05:16	ga_s2am_ard_3-2-1_50JLQ_2020-01-25_final.stac-item
2020-02-27 12:14:16	ga_s2am_ard_3-2-1_49KHP_2020-02-27_final.stac-item
2020-07-13 12:05:12	ga_s2am_ard_3-2-1_50JLR_2020-07-13_final.stac-item
2020-07-20 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-07-20_final.stac-item
2020-08-26 11:47:19	ga_s2am_ard_3-2-1_50HLH_2020-08-26_final.stac-item
2020-09-08 11:55:17	ga_s2am_ard_3-2-1_50JLR_2020-09-08_final.stac-item
2020-10-01 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-10-01_final.stac-item
2020-12-03 12:14:20	ga_s2am_ard_3-2-1_49KHP_2020-12-03_final.stac-item
2021-10-13 11:55:18	ga_s2am_ard_3-2-1_50JLR_2021-10-13_final.stac-item
2021-11-28 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-11-28_final.stac-item
2021-12-25 12:06:05	ga_s2am_ard_3-2-1_50JLM_2021-12-25_final.stac-item
2021-12-26 11:36:35	ga_s2am_ard_3-2-1_50HQK_2021-12-26_final.stac-item
2022-01-05 11:36:35	ga_s2am_ard_3-2-1_50HQK_2022-01-05_final.stac-item
2022-01-24 12:06:04	ga_s2am_ard_3-2-1_50JLM_2022-01-24_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 12:05:08	ga_s2am_ard_3-2-1_50JKS_2022-03-05_final.stac-item
2022-03-05 12:05:16	ga_s2am_ard_3-2-1_50JKR_2022-03-05_final.stac-item
2022-05-04 12:05:17	ga_s2am_ard_3-2-1_50JKR_2022-05-04_final.stac-item
2022-05-08 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-05-08_final.stac-item
2022-06-06 12:14:29	ga_s2am_ard_3-2-1_49KHP_2022-06-06_final.stac-item
2022-06-07 11:47:18	ga_s2am_ard_3-2-1_50HMH_2022-06-07_final.stac-item
2022-06-20 11:55:24	ga_s2am_ard_3-2-1_50JLR_2022-06-20_final.stac-item
2022-06-20 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-06-20_final.stac-item
2022-07-20 11:55:24	ga_s2am_ard_3-2-1_50JLR_2022-07-20_final.stac-item
2022-08-22 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-08-22_final.stac-item
2022-08-22 12:05:39	ga_s2am_ard_3-2-1_50JKQ_2022-08-22_final.stac-item
2022-08-26 11:47:22	ga_s2am_ard_3-2-1_50HMH_2022-08-26_final.stac-item
2022-10-11 12:04:40	ga_s2am_ard_3-2-1_50JKT_2022-10-11_final.stac-item
2022-10-14 12:14:17	ga_s2am_ard_3-2-1_49KHQ_2022-10-14_final.stac-item
2022-11-04 11:46:34	ga_s2am_ard_3-2-1_50HQK_2022-11-04_final.stac-item
2022-11-13 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-11-13_final.stac-item
2022-11-24 11:46:53	ga_s2am_ard_3-2-1_50HQH_2022-11-24_final.stac-item
2022-12-13 12:14:07	ga_s2am_ard_3-2-1_49KHQ_2022-12-13_final.stac-item
2023-01-02 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-01-02_final.stac-item
2023-01-02 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-01-02_final.stac-item
2023-01-06 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2023-01-06_final.stac-item
2023-01-12 12:14:19	ga_s2am_ard_3-2-1_49KHP_2023-01-12_final.stac-item
2023-02-08 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-02-08_final
2023-03-03 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-03-03_final
2023-05-12 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-05-12_final
2023-05-20 11:37:29	ga_s2am_ard_3-2-1_50HNG_2023-05-20_final
2023-06-28 12:04:52	ga_s2am_ard_3-2-1_50JKT_2023-06-28_final
2023-07-11 12:14:26	ga_s2am_ard_3-2-1_49KHP_2023-07-11_final
2023-08-01 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2023-08-01_final
2023-08-14 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2023-08-14_final
2023-08-20 12:14:27	ga_s2am_ard_3-2-1_49KHP_2023-08-20_final
2023-08-21 11:47:33	ga_s2am_ard_3-2-1_50HLG_2023-08-21_final
2023-09-27 11:37:28	ga_s2am_ard_3-2-1_50HNG_2023-09-27_final
2023-11-22 11:56:36	ga_s2am_ard_3-2-1_50HLK_2023-11-22_final
2023-12-06 11:36:27	ga_s2am_ard_3-2-1_50HQK_2023-12-06_final
2024-01-01 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2024-01-01_final
2024-01-04 12:06:06	ga_s2am_ard_3-2-1_50JKM_2024-01-04_final
2024-01-11 11:55:22	ga_s2am_ard_3-2-1_50JLQ_2024-01-11_final
2024-01-14 12:05:16	ga_s2am_ard_3-2-1_50JLQ_2024-01-14_final
2024-03-07 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-07_final
2024-03-11 11:57:22	ga_s2am_ard_3-2-1_50HLG_2024-03-11_final
2024-04-04 11:36:23	ga_s2am_ard_3-2-1_50HQK_2024-04-04_final
2024-04-16 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2024-04-16_final
2024-04-30 11:57:25	ga_s2am_ard_3-2-1_50HLG_2024-04-30_final
2024-05-03 12:05:15	ga_s2am_ard_3-2-1_50JKR_2024-05-03_final
2024-05-17 11:47:12	ga_s2am_ard_3-2-1_50HMH_2024-05-17_final
2024-05-17 11:47:16	ga_s2am_ard_3-2-1_50HLH_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

Other products

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