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_50JLR_2015-10-28_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_50JLT_2015-11-27_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49KHP_2015-11-30_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JKT_2015-12-07_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_50JLT_2015-12-27_final.stac-item
2015-12-27 12:05:25	ga_s2am_ard_3-2-1_50JLR_2015-12-27_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_50JKQ_2016-02-05_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JLS_2016-06-11_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JLT_2016-06-11_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JLS_2016-08-10_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JLT_2016-08-10_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKQ_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JLR_2016-08-13_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JLS_2016-08-30_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JLS_2016-09-02_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KHS_2016-09-15_final.stac-item
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_50JLT_2016-09-22_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JHN_2016-10-25_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JLR_2016-11-18_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JLR_2016-11-28_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JLR_2016-12-01_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HMG_2016-12-05_final
2016-12-08 11:44:46	ga_s2am_ard_3-2-1_50JLR_2016-12-08_final.stac-item
2016-12-08 11:44:46	ga_s2am_ard_3-2-1_50JLT_2016-12-08_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JLR_2016-12-21_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50JLR_2016-12-28_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JHN_2017-03-01_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_50JKQ_2017-03-01_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JLS_2017-04-07_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HQH_2017-04-14_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_50JKQ_2017-04-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JLR_2017-05-30_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JLS_2017-06-06_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_50JLT_2017-06-26_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JLS_2017-07-16_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLS_2017-08-05_final.stac-item
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_50JKQ_2017-10-27_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JLS_2018-06-01_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JLS_2018-07-21_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JLS_2018-07-31_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JLT_2018-08-10_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLT_2018-09-19_final.stac-item
2018-12-28 11:54:37	ga_s2am_ard_3-2-1_50JLT_2018-12-28_final.stac-item
2019-01-17 11:55:09	ga_s2am_ard_3-2-1_50JLR_2019-01-17_final.stac-item
2019-05-03 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-05-03_final.stac-item
2019-06-06 11:55:47	ga_s2am_ard_3-2-1_50JMN_2019-06-06_final.stac-item
2019-06-16 11:54:48	ga_s2am_ard_3-2-1_50JLT_2019-06-16_final.stac-item
2019-07-16 11:55:03	ga_s2am_ard_3-2-1_50JLS_2019-07-16_final.stac-item
2019-07-22 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-07-22_final.stac-item
2019-08-01 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-08-01_final.stac-item
2019-08-15 11:54:48	ga_s2am_ard_3-2-1_50JLT_2019-08-15_final.stac-item
2019-11-13 11:56:18	ga_s2am_ard_3-2-1_50JMM_2019-11-13_final.stac-item
2019-12-23 11:55:18	ga_s2am_ard_3-2-1_50JMQ_2019-12-23_final.stac-item
2020-04-11 11:54:43	ga_s2am_ard_3-2-1_50JLT_2020-04-11_final.stac-item
2020-04-24 12:05:10	ga_s2am_ard_3-2-1_49JFM_2020-04-24_final.stac-item
2020-05-11 11:54:49	ga_s2am_ard_3-2-1_50JLT_2020-05-11_final.stac-item
2020-05-31 11:55:30	ga_s2am_ard_3-2-1_50JMQ_2020-05-31_final.stac-item
2020-06-30 11:54:49	ga_s2am_ard_3-2-1_50JLT_2020-06-30_final.stac-item
2020-09-08 11:54:48	ga_s2am_ard_3-2-1_50JLT_2020-09-08_final.stac-item
2021-03-17 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2021-03-17_final.stac-item
2021-04-26 11:54:41	ga_s2am_ard_3-2-1_50JLT_2021-04-26_final.stac-item
2021-09-13 11:55:25	ga_s2am_ard_3-2-1_50JMQ_2021-09-13_final.stac-item
2021-10-13 11:54:50	ga_s2am_ard_3-2-1_50JLT_2021-10-13_final.stac-item
2021-12-02 11:54:44	ga_s2am_ard_3-2-1_50JLT_2021-12-02_final.stac-item
2021-12-12 11:54:43	ga_s2am_ard_3-2-1_50JLT_2021-12-12_final.stac-item
2021-12-22 11:54:45	ga_s2am_ard_3-2-1_50JLT_2021-12-22_final.stac-item
2022-01-01 11:54:46	ga_s2am_ard_3-2-1_50JLT_2022-01-01_final.stac-item
2022-01-11 11:54:45	ga_s2am_ard_3-2-1_50JLT_2022-01-11_final.stac-item
2022-01-21 11:54:44	ga_s2am_ard_3-2-1_50JLT_2022-01-21_final.stac-item
2022-06-30 11:55:11	ga_s2am_ard_3-2-1_50JLS_2022-06-30_final.stac-item
2022-10-28 11:54:56	ga_s2am_ard_3-2-1_50JLS_2022-10-28_final.stac-item
2022-10-28 11:55:27	ga_s2am_ard_3-2-1_50JMQ_2022-10-28_final.stac-item
2022-12-17 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2022-12-17_final.stac-item
2023-02-05 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2023-02-05_final
2023-02-08 12:05:07	ga_s2am_ard_3-2-1_49JFM_2023-02-08_final
2023-02-15 11:54:50	ga_s2am_ard_3-2-1_50JLS_2023-02-15_nrt.stac-item
2023-02-15 11:54:50	ga_s2am_ard_3-2-1_50JLS_2023-02-15_final
2023-02-15 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-15_nrt.stac-item
2023-02-15 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-15_final
2023-02-18 12:05:05	ga_s2am_ard_3-2-1_50JLR_2023-02-18_nrt.stac-item
2023-02-18 12:05:05	ga_s2am_ard_3-2-1_50JLR_2023-02-18_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
2023-02-25 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-02-25_final
2023-03-07 11:55:09	ga_s2am_ard_3-2-1_50JLR_2023-03-07_final
2023-03-10 12:05:03	ga_s2am_ard_3-2-1_50JLR_2023-03-10_final
2023-06-15 11:55:02	ga_s2am_ard_3-2-1_50JLS_2023-06-15_final
2023-06-28 12:04:51	ga_s2am_ard_3-2-1_50JLS_2023-06-28_final
2023-07-08 12:05:13	ga_s2am_ard_3-2-1_50JLR_2023-07-08_final
2023-07-18 12:05:13	ga_s2am_ard_3-2-1_50JLR_2023-07-18_final
2023-08-17 12:05:14	ga_s2am_ard_3-2-1_50JLR_2023-08-17_final
2023-08-27 12:05:14	ga_s2am_ard_3-2-1_50JLR_2023-08-27_final
2023-11-12 11:54:37	ga_s2am_ard_3-2-1_50JLT_2023-11-12_final
2023-12-12 11:54:40	ga_s2am_ard_3-2-1_50JLT_2023-12-12_final
2024-01-31 11:54:40	ga_s2am_ard_3-2-1_50JLT_2024-01-31_final
2024-04-04 11:36:23	ga_s2am_ard_3-2-1_50HQK_2024-04-04_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
2024-04-30 11:54:47	ga_s2am_ard_3-2-1_50JLT_2024-04-30_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

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