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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KGQ_2015-10-28_final.stac-item
2016-01-13 11:56:42	ga_s2am_ard_3-2-1_50HNK_2016-01-13_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50HLG_2016-04-02_final
2016-04-22 11:56:28	ga_s2am_ard_3-2-1_50HNK_2016-04-22_final.stac-item
2016-05-28 12:13:49	ga_s2am_ard_3-2-1_49KGR_2016-05-28_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KGQ_2016-07-14_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HNG_2016-08-17_final
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HQH_2016-09-26_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KGQ_2016-11-14_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KGR_2016-11-14_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KHP_2016-11-21_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KGR_2016-12-14_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49JGN_2016-12-21_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KGP_2016-12-24_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49KHP_2017-01-30_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2017-03-31_final.stac-item
2017-04-10 12:03:46	ga_s2am_ard_3-2-1_49KHQ_2017-04-10_final.stac-item
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49KHP_2017-06-22_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGN_2017-06-29_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49KHQ_2017-08-18_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JHN_2017-10-27_final.stac-item
2018-01-25 12:02:44	ga_s2am_ard_3-2-1_49KGQ_2018-01-25_final.stac-item
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_49KHQ_2018-09-15_final.stac-item
2018-12-14 12:14:33	ga_s2am_ard_3-2-1_49JGN_2018-12-14_final.stac-item
2019-01-20 12:04:24	ga_s2am_ard_3-2-1_49KHP_2019-01-20_final.stac-item
2019-01-20 12:04:42	ga_s2am_ard_3-2-1_49JGN_2019-01-20_final.stac-item
2019-01-31 11:36:31	ga_s2am_ard_3-2-1_50HQK_2019-01-31_final.stac-item
2019-02-12 12:14:24	ga_s2am_ard_3-2-1_49KGP_2019-02-12_final.stac-item
2019-02-22 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-02-22_final.stac-item
2019-03-01 12:04:52	ga_s2am_ard_3-2-1_49JHM_2019-03-01_final.stac-item
2019-05-10 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-05-10_final.stac-item
2019-08-02 11:46:58	ga_s2am_ard_3-2-1_50HQH_2019-08-02_final.stac-item
2019-08-11 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-08-11_final.stac-item
2019-09-10 12:14:20	ga_s2am_ard_3-2-1_49KHP_2019-09-10_final.stac-item
2019-11-19 12:14:22	ga_s2am_ard_3-2-1_49KHP_2019-11-19_final.stac-item
2019-11-26 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2019-11-26_final.stac-item
2019-11-26 12:04:31	ga_s2am_ard_3-2-1_49KGP_2019-11-26_final.stac-item
2019-11-26 12:04:57	ga_s2am_ard_3-2-1_49JHM_2019-11-26_final.stac-item
2019-12-09 12:14:24	ga_s2am_ard_3-2-1_49KGP_2019-12-09_final.stac-item
2019-12-19 12:14:15	ga_s2am_ard_3-2-1_49KHP_2019-12-19_final.stac-item
2020-01-28 12:14:02	ga_s2am_ard_3-2-1_49KHQ_2020-01-28_final.stac-item
2020-05-07 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2020-05-07_final.stac-item
2020-07-16 12:14:26	ga_s2am_ard_3-2-1_49KHP_2020-07-16_final.stac-item
2020-08-02 12:04:34	ga_s2am_ard_3-2-1_49KHP_2020-08-02_final.stac-item
2020-08-02 12:05:03	ga_s2am_ard_3-2-1_49JHM_2020-08-02_final.stac-item
2020-08-19 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-08-19_final.stac-item
2020-08-22 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-08-22_final.stac-item
2020-10-01 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-10-01_final.stac-item
2020-11-03 12:14:26	ga_s2am_ard_3-2-1_49KHP_2020-11-03_final.stac-item
2021-01-19 12:05:09	ga_s2am_ard_3-2-1_49JFM_2021-01-19_final.stac-item
2021-02-02 11:46:53	ga_s2am_ard_3-2-1_50HQH_2021-02-02_final.stac-item
2021-08-24 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2021-08-24_final.stac-item
2021-11-05 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2021-11-05_final.stac-item
2021-11-15 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2021-11-15_final.stac-item
2021-11-18 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-11-18_final.stac-item
2021-12-02 11:56:40	ga_s2am_ard_3-2-1_50HLK_2021-12-02_final.stac-item
2021-12-08 12:14:20	ga_s2am_ard_3-2-1_49KHP_2021-12-08_final.stac-item
2021-12-22 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-12-22_final.stac-item
2022-01-11 11:56:41	ga_s2am_ard_3-2-1_50HLK_2022-01-11_final.stac-item
2022-01-27 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2022-01-27_final.stac-item
2022-02-16 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2022-02-16_final.stac-item
2022-03-19 11:46:33	ga_s2am_ard_3-2-1_50HQK_2022-03-19_final.stac-item
2022-04-14 12:04:31	ga_s2am_ard_3-2-1_49KHP_2022-04-14_final.stac-item
2022-05-07 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2022-05-07_final.stac-item
2022-06-07 11:46:49	ga_s2am_ard_3-2-1_50HMK_2022-06-07_final.stac-item
2022-06-13 12:05:18	ga_s2am_ard_3-2-1_49JFM_2022-06-13_final.stac-item
2022-06-26 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-06-26_final.stac-item
2022-07-16 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-07-16_final.stac-item
2022-08-25 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-08-25_final
2022-10-11 12:04:38	ga_s2am_ard_3-2-1_49JHN_2022-10-11_final.stac-item
2022-11-21 11:36:34	ga_s2am_ard_3-2-1_50HQK_2022-11-21_final.stac-item
2022-12-04 11:46:30	ga_s2am_ard_3-2-1_50HQK_2022-12-04_final.stac-item
2023-01-03 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-01-03_final
2023-02-11 12:14:19	ga_s2am_ard_3-2-1_49KHP_2023-02-11_nrt.stac-item
2023-02-11 12:14:19	ga_s2am_ard_3-2-1_49KHP_2023-02-11_final
2023-03-10 12:04:41	ga_s2am_ard_3-2-1_49JGN_2023-03-10_final
2023-03-10 12:04:51	ga_s2am_ard_3-2-1_49JHM_2023-03-10_final
2023-04-19 12:04:56	ga_s2am_ard_3-2-1_49JHM_2023-04-19_final
2023-04-22 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-04-22_final
2023-04-23 11:47:20	ga_s2am_ard_3-2-1_50HNG_2023-04-23_final
2023-05-09 12:04:23	ga_s2am_ard_3-2-1_49KHP_2023-05-09_final
2023-06-02 11:47:18	ga_s2am_ard_3-2-1_50HLH_2023-06-02_final
2023-06-12 11:46:57	ga_s2am_ard_3-2-1_50HQH_2023-06-12_final
2023-07-02 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2023-07-02_final
2023-07-15 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2023-07-15_final
2023-08-11 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-11_final
2023-10-20 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-10-20_final
2023-10-23 11:56:26	ga_s2am_ard_3-2-1_50HMK_2023-10-23_final
2023-10-29 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-10-29_final
2023-11-08 12:14:20	ga_s2am_ard_3-2-1_49KHP_2023-11-08_final
2024-01-15 11:36:45	ga_s2am_ard_3-2-1_50HPJ_2024-01-15_final
2024-01-17 12:14:13	ga_s2am_ard_3-2-1_49KHP_2024-01-17_final
2024-01-21 11:56:32	ga_s2am_ard_3-2-1_50HLK_2024-01-21_final
2024-01-27 12:14:16	ga_s2am_ard_3-2-1_49KHP_2024-01-27_final
2024-02-06 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2024-02-06_final
2024-02-20 11:56:38	ga_s2am_ard_3-2-1_50HLK_2024-02-20_final
2024-03-21 11:56:38	ga_s2am_ard_3-2-1_50HLK_2024-03-21_final
2024-04-10 11:57:22	ga_s2am_ard_3-2-1_50HLG_2024-04-10_final
2024-04-27 11:47:29	ga_s2am_ard_3-2-1_50HLG_2024-04-27_final
2024-05-06 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2024-05-06_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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