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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HLG_2015-11-21_final
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JMR_2016-07-24_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKQ_2016-08-13_final.stac-item
2016-08-14 11:36:06	ga_s2am_ard_3-2-1_50HQK_2016-08-14_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JLR_2016-08-23_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JMR_2016-08-23_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50JMQ_2016-12-28_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JMQ_2017-03-18_final.stac-item
2017-04-11 11:36:02	ga_s2am_ard_3-2-1_50HQK_2017-04-11_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JLS_2017-06-26_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JMR_2017-06-26_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50JMQ_2018-03-03_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JMQ_2018-03-13_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JMR_2018-06-01_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLS_2018-07-11_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JMQ_2018-07-31_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50JMR_2018-08-03_final.stac-item
2018-11-18 11:55:18	ga_s2am_ard_3-2-1_50JMQ_2018-11-18_final.stac-item
2018-11-28 11:55:15	ga_s2am_ard_3-2-1_50JMQ_2018-11-28_final.stac-item
2018-12-11 12:04:50	ga_s2am_ard_3-2-1_50JMR_2018-12-11_final.stac-item
2018-12-18 11:55:01	ga_s2am_ard_3-2-1_50JMR_2018-12-18_final.stac-item
2018-12-28 11:55:03	ga_s2am_ard_3-2-1_50JMR_2018-12-28_final.stac-item
2019-02-16 11:54:37	ga_s2am_ard_3-2-1_50JLT_2019-02-16_final.stac-item
2019-02-23 11:46:49	ga_s2am_ard_3-2-1_50HQH_2019-02-23_final.stac-item
2019-02-26 11:55:08	ga_s2am_ard_3-2-1_50JLR_2019-02-26_final.stac-item
2019-02-26 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2019-02-26_final.stac-item
2019-03-01 12:04:54	ga_s2am_ard_3-2-1_50JMR_2019-03-01_final.stac-item
2019-03-18 11:54:41	ga_s2am_ard_3-2-1_50JLT_2019-03-18_final.stac-item
2019-03-18 11:55:10	ga_s2am_ard_3-2-1_50JLR_2019-03-18_final.stac-item
2019-03-18 11:55:21	ga_s2am_ard_3-2-1_50JMQ_2019-03-18_final.stac-item
2019-03-18 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-03-18_final.stac-item
2019-06-06 11:54:46	ga_s2am_ard_3-2-1_50JLT_2019-06-06_final.stac-item
2019-06-06 11:55:26	ga_s2am_ard_3-2-1_50JMQ_2019-06-06_final.stac-item
2019-07-16 11:55:03	ga_s2am_ard_3-2-1_50JLS_2019-07-16_final.stac-item
2019-11-13 11:55:26	ga_s2am_ard_3-2-1_50JMQ_2019-11-13_final.stac-item
2020-01-02 11:55:18	ga_s2am_ard_3-2-1_50JMQ_2020-01-02_final.stac-item
2020-02-17 12:14:24	ga_s2am_ard_3-2-1_49KHP_2020-02-17_final.stac-item
2020-03-02 11:55:19	ga_s2am_ard_3-2-1_50JMQ_2020-03-02_final.stac-item
2020-03-12 11:55:20	ga_s2am_ard_3-2-1_50JMQ_2020-03-12_final.stac-item
2020-03-28 12:14:27	ga_s2am_ard_3-2-1_49JHN_2020-03-28_final.stac-item
2020-04-11 11:54:43	ga_s2am_ard_3-2-1_50JLT_2020-04-11_final.stac-item
2020-05-31 11:55:16	ga_s2am_ard_3-2-1_50JMR_2020-05-31_final.stac-item
2020-05-31 11:55:30	ga_s2am_ard_3-2-1_50JMQ_2020-05-31_final.stac-item
2020-07-13 12:05:12	ga_s2am_ard_3-2-1_50JLR_2020-07-13_final.stac-item
2020-11-07 11:55:28	ga_s2am_ard_3-2-1_50JMQ_2020-11-07_final.stac-item
2020-11-27 11:55:25	ga_s2am_ard_3-2-1_50JMQ_2020-11-27_final.stac-item
2020-12-17 11:55:22	ga_s2am_ard_3-2-1_50JMQ_2020-12-17_final.stac-item
2020-12-30 12:04:58	ga_s2am_ard_3-2-1_50JMR_2020-12-30_final.stac-item
2021-01-16 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-01-16_final
2021-04-16 11:55:18	ga_s2am_ard_3-2-1_50JMQ_2021-04-16_final.stac-item
2021-05-09 12:04:58	ga_s2am_ard_3-2-1_50JMR_2021-05-09_final.stac-item
2021-07-08 12:05:01	ga_s2am_ard_3-2-1_50JMR_2021-07-08_final.stac-item
2021-11-05 12:05:02	ga_s2am_ard_3-2-1_50JMR_2021-11-05_final.stac-item
2021-11-12 11:55:26	ga_s2am_ard_3-2-1_50JMQ_2021-11-12_final.stac-item
2021-11-22 11:55:24	ga_s2am_ard_3-2-1_50JMQ_2021-11-22_final.stac-item
2021-12-15 12:04:58	ga_s2am_ard_3-2-1_50JMR_2021-12-15_final.stac-item
2022-01-04 12:05:00	ga_s2am_ard_3-2-1_50JMR_2022-01-04_final.stac-item
2022-01-14 12:04:59	ga_s2am_ard_3-2-1_50JMR_2022-01-14_final.stac-item
2022-03-05 12:05:02	ga_s2am_ard_3-2-1_50JMR_2022-03-05_final.stac-item
2022-03-12 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-03-12_final.stac-item
2022-04-05 11:36:33	ga_s2am_ard_3-2-1_50HPK_2022-04-05_final.stac-item
2022-05-04 12:05:09	ga_s2am_ard_3-2-1_50JKR_2022-05-04_final.stac-item
2022-05-04 12:05:14	ga_s2am_ard_3-2-1_50JLR_2022-05-04_final.stac-item
2022-06-03 12:05:16	ga_s2am_ard_3-2-1_50JLR_2022-06-03_final.stac-item
2022-06-30 11:55:11	ga_s2am_ard_3-2-1_50JLS_2022-06-30_final.stac-item
2022-08-12 12:05:11	ga_s2am_ard_3-2-1_50JMR_2022-08-12_final.stac-item
2022-11-20 12:05:00	ga_s2am_ard_3-2-1_50JMR_2022-11-20_final.stac-item
2022-11-27 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2022-11-27_final.stac-item
2022-12-10 12:04:59	ga_s2am_ard_3-2-1_50JMR_2022-12-10_final.stac-item
2022-12-30 12:04:57	ga_s2am_ard_3-2-1_50JMR_2022-12-30_final.stac-item
2023-01-06 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2023-01-06_final.stac-item
2023-02-15 11:55:21	ga_s2am_ard_3-2-1_50JMQ_2023-02-15_nrt.stac-item
2023-02-15 11:55:21	ga_s2am_ard_3-2-1_50JMQ_2023-02-15_final
2023-02-18 12:05:12	ga_s2am_ard_3-2-1_50JLQ_2023-02-18_nrt.stac-item
2023-02-18 12:05:12	ga_s2am_ard_3-2-1_50JLQ_2023-02-18_final
2023-03-07 11:55:05	ga_s2am_ard_3-2-1_50JMR_2023-03-07_final
2023-03-07 11:55:09	ga_s2am_ard_3-2-1_50JLR_2023-03-07_final
2023-03-27 11:54:42	ga_s2am_ard_3-2-1_50JLT_2023-03-27_final
2023-04-16 11:54:44	ga_s2am_ard_3-2-1_50JLT_2023-04-16_final
2023-04-19 12:04:57	ga_s2am_ard_3-2-1_50JMR_2023-04-19_final
2023-05-03 11:47:27	ga_s2am_ard_3-2-1_50HLG_2023-05-03_final
2023-06-05 11:54:48	ga_s2am_ard_3-2-1_50JLT_2023-06-05_final
2023-06-28 12:04:51	ga_s2am_ard_3-2-1_50JLS_2023-06-28_final
2023-07-25 11:55:03	ga_s2am_ard_3-2-1_50JLS_2023-07-25_final
2023-08-01 11:47:32	ga_s2am_ard_3-2-1_50HLG_2023-08-01_final
2023-08-14 11:55:29	ga_s2am_ard_3-2-1_50JMQ_2023-08-14_final
2023-08-24 11:54:50	ga_s2am_ard_3-2-1_50JLT_2023-08-24_final
2023-08-24 11:55:30	ga_s2am_ard_3-2-1_50JMQ_2023-08-24_final
2023-09-13 11:54:49	ga_s2am_ard_3-2-1_50JLT_2023-09-13_final
2023-12-02 11:55:16	ga_s2am_ard_3-2-1_50JMQ_2023-12-02_final
2023-12-22 11:55:20	ga_s2am_ard_3-2-1_50JMQ_2023-12-22_final
2024-01-31 11:55:19	ga_s2am_ard_3-2-1_50JMQ_2024-01-31_final
2024-02-23 12:04:57	ga_s2am_ard_3-2-1_50JMR_2024-02-23_final
2024-03-21 11:55:11	ga_s2am_ard_3-2-1_50JMR_2024-03-21_final
2024-04-13 12:05:00	ga_s2am_ard_3-2-1_50JMR_2024-04-13_final
2024-04-13 12:05:10	ga_s2am_ard_3-2-1_49JFM_2024-04-13_final
2024-04-20 11:54:48	ga_s2am_ard_3-2-1_50JLT_2024-04-20_final
2024-04-20 11:55:13	ga_s2am_ard_3-2-1_50JMR_2024-04-20_final
2024-05-10 11:54:47	ga_s2am_ard_3-2-1_50JLT_2024-05-10_final
2024-05-20 11:55:25	ga_s2am_ard_3-2-1_50JMQ_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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