Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

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_49JHN_2015-10-08_final.stac-item
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HLG_2015-10-22_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHS_2015-10-28_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JHN_2016-01-26_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGR_2016-06-27_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHP_2016-06-27_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHP_2016-09-12_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KHQ_2016-11-01_final.stac-item
2017-03-24 12:13:37	ga_s2am_ard_3-2-1_49KGR_2017-03-24_final
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HLH_2017-04-14_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JGN_2017-06-02_final
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49KGQ_2017-06-02_final
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JHN_2017-06-19_final
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KHP_2017-07-29_final
2017-09-10 12:13:33	ga_s2am_ard_3-2-1_49KGQ_2017-09-10_final
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JGN_2017-10-27_final
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-02-24_final
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2018-03-16_final
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-04-08_final
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-04-18_final
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HLH_2018-05-12_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2018-09-25_final
2018-11-24 12:14:14	ga_s2am_ard_3-2-1_49KHP_2018-11-24_final
2019-01-10 12:04:52	ga_s2am_ard_3-2-1_49JHM_2019-01-10_final
2019-01-30 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2019-01-30_final
2019-02-02 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2019-02-02_final
2019-03-01 12:04:41	ga_s2am_ard_3-2-1_49JGN_2019-03-01_final
2019-03-11 12:04:26	ga_s2am_ard_3-2-1_49KGP_2019-03-11_final
2019-03-15 11:47:24	ga_s2am_ard_3-2-1_50HLG_2019-03-15_final.stac-item
2019-03-21 12:04:26	ga_s2am_ard_3-2-1_49KHP_2019-03-21_final
2019-03-31 12:04:57	ga_s2am_ard_3-2-1_49JHM_2019-03-31_final
2019-05-10 12:04:50	ga_s2am_ard_3-2-1_49JGN_2019-05-10_final
2019-05-27 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-05-27_final
2019-06-09 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-06-09_final
2019-06-09 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-06-09_final
2019-07-16 11:56:45	ga_s2am_ard_3-2-1_50HLK_2019-07-16_final
2019-08-08 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-08-08_final
2019-08-25 11:56:42	ga_s2am_ard_3-2-1_50HLK_2019-08-25_final
2019-09-17 12:04:45	ga_s2am_ard_3-2-1_49JGN_2019-09-17_final
2019-10-17 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-10-17_final
2019-10-17 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-10-17_final
2019-10-27 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-10-27_final
2019-12-09 12:13:55	ga_s2am_ard_3-2-1_49KGR_2019-12-09_final
2019-12-09 12:14:24	ga_s2am_ard_3-2-1_49KGP_2019-12-09_final
2019-12-13 11:56:36	ga_s2am_ard_3-2-1_50HLK_2019-12-13_final
2019-12-29 12:14:16	ga_s2am_ard_3-2-1_49KHP_2019-12-29_final
2020-01-25 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2020-01-25_final
2020-03-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2020-03-25_final
2020-05-04 12:04:46	ga_s2am_ard_3-2-1_49JHN_2020-05-04_final
2020-05-04 12:05:12	ga_s2am_ard_3-2-1_49JFM_2020-05-04_final
2020-07-13 12:04:32	ga_s2am_ard_3-2-1_49KHP_2020-07-13_final
2020-07-30 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-07-30_final
2020-08-05 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2020-08-05_final
2020-09-01 12:03:49	ga_s2am_ard_3-2-1_49KHS_2020-09-01_final.stac-item
2020-10-11 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2020-10-11_final
2021-04-22 12:14:17	ga_s2am_ard_3-2-1_49KHP_2021-04-22_final
2021-11-05 12:04:50	ga_s2am_ard_3-2-1_49JGN_2021-11-05_final
2021-11-15 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-11-15_final
2021-11-25 12:04:28	ga_s2am_ard_3-2-1_49KHP_2021-11-25_final
2021-12-09 11:47:25	ga_s2am_ard_3-2-1_50HLG_2021-12-09_final.stac-item
2022-01-24 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2022-01-24_final
2022-01-24 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-01-24_final
2022-01-27 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-01-27_final
2022-02-13 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-02-13_final
2022-04-21 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2022-04-21_final
2022-06-07 11:47:35	ga_s2am_ard_3-2-1_50HLG_2022-06-07_final.stac-item
2022-07-13 12:04:55	ga_s2am_ard_3-2-1_49JHN_2022-07-13_final
2022-09-21 12:04:40	ga_s2am_ard_3-2-1_49JHN_2022-09-21_final.stac-item
2022-11-10 12:04:31	ga_s2am_ard_3-2-1_49KHP_2022-11-10_final.stac-item
2022-11-20 12:04:47	ga_s2am_ard_3-2-1_49JGN_2022-11-20_final.stac-item
2022-12-20 12:04:55	ga_s2am_ard_3-2-1_49JHM_2022-12-20_final.stac-item
2022-12-30 12:04:56	ga_s2am_ard_3-2-1_49JHM_2022-12-30_final.stac-item
2023-01-19 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-01-19_final.stac-item
2023-01-19 12:04:37	ga_s2am_ard_3-2-1_49JHN_2023-01-19_final.stac-item
2023-01-29 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2023-01-29_final.stac-item
2023-02-08 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-02-08_final.stac-item
2023-02-08 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-02-08_final.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_final.stac-item
2023-03-13 12:13:55	ga_s2am_ard_3-2-1_49KGR_2023-03-13_final.stac-item
2023-04-09 12:04:34	ga_s2am_ard_3-2-1_49KHP_2023-04-09_final.stac-item
2023-04-09 12:04:42	ga_s2am_ard_3-2-1_49JHN_2023-04-09_final.stac-item
2023-04-19 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-04-19_final.stac-item
2023-05-29 12:04:46	ga_s2am_ard_3-2-1_49JHN_2023-05-29_final.stac-item
2023-06-28 12:04:54	ga_s2am_ard_3-2-1_49JGN_2023-06-28_final.stac-item
2023-07-15 11:57:27	ga_s2am_ard_3-2-1_50HLG_2023-07-15_final.stac-item
2023-07-18 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-07-18_final.stac-item
2023-08-27 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2023-08-27_final.stac-item
2023-08-27 12:04:34	ga_s2am_ard_3-2-1_49KHP_2023-08-27_final.stac-item
2023-09-16 12:04:50	ga_s2am_ard_3-2-1_49JGN_2023-09-16_final.stac-item
2023-09-19 12:14:24	ga_s2am_ard_3-2-1_49KHP_2023-09-19_final.stac-item
2023-09-26 12:04:30	ga_s2am_ard_3-2-1_49KHP_2023-09-26_final.stac-item
2023-10-06 12:04:58	ga_s2am_ard_3-2-1_49JHM_2023-10-06_final.stac-item
2023-11-05 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-11-05_final.stac-item
2023-11-25 12:04:41	ga_s2am_ard_3-2-1_49JGN_2023-11-25_final.stac-item
2023-12-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-12-25_final.stac-item
2024-01-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2024-01-04_final.stac-item
2024-01-14 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2024-01-14_final.stac-item
2024-02-07 11:47:22	ga_s2am_ard_3-2-1_50HLG_2024-02-07_final.stac-item
2024-02-13 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2024-02-13_final.stac-item
2024-02-13 12:04:43	ga_s2am_ard_3-2-1_49JGN_2024-02-13_final.stac-item

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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