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
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JFM_2015-10-21_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49JGK_2016-01-16_final.stac-item
2016-01-19 12:15:17	ga_s2am_ard_3-2-1_49JGM_2016-01-19_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KGP_2016-08-26_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KGP_2016-12-21_final
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KGR_2016-12-24_final
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KGP_2017-03-14_final
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KGQ_2017-03-14_final
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KHP_2017-03-14_final
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49JFM_2017-10-20_final
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2017-10-20_final
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KHQ_2017-11-09_final
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JHN_2018-01-08_final
2018-01-18 12:14:35	ga_s2am_ard_3-2-1_49JGN_2018-01-18_final
2018-12-04 12:14:00	ga_s2am_ard_3-2-1_49KHQ_2018-12-04_final
2018-12-14 12:13:46	ga_s2am_ard_3-2-1_49KHR_2018-12-14_final
2019-01-13 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-01-13_final
2019-01-20 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-20_final
2019-01-30 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2019-01-30_final
2019-01-30 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-30_final
2019-02-02 12:14:24	ga_s2am_ard_3-2-1_49KGP_2019-02-02_final
2019-03-11 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2019-03-11_final
2019-03-21 12:04:29	ga_s2am_ard_3-2-1_49KGP_2019-03-21_final
2019-07-02 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2019-07-02_final
2019-08-18 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-08-18_final
2019-10-30 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-10-30_final
2019-11-09 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2019-11-09_final
2020-01-25 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2020-01-25_final
2020-01-25 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2020-01-25_final
2020-02-27 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2020-02-27_final
2020-04-17 12:14:27	ga_s2am_ard_3-2-1_49KGP_2020-04-17_final
2020-07-16 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-07-16_final
2020-08-15 12:14:02	ga_s2am_ard_3-2-1_49KHR_2020-08-15_final
2020-10-01 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-10-01_final
2020-10-01 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-10-01_final
2020-12-10 12:03:56	ga_s2am_ard_3-2-1_49KHR_2020-12-10_final
2021-01-29 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-01-29_final
2021-08-30 12:14:00	ga_s2am_ard_3-2-1_49KGR_2021-08-30_final
2021-08-30 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2021-08-30_final
2021-11-18 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-11-18_final
2021-11-22 11:57:23	ga_s2am_ard_3-2-1_50HLG_2021-11-22_final.stac-item
2021-11-25 12:05:29	ga_s2am_ard_3-2-1_49JGK_2021-11-25_final
2021-11-28 12:13:54	ga_s2am_ard_3-2-1_49KHR_2021-11-28_final
2022-01-01 11:57:25	ga_s2am_ard_3-2-1_50HLG_2022-01-01_final.stac-item
2022-02-13 12:05:29	ga_s2am_ard_3-2-1_49JGK_2022-02-13_final
2022-02-23 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-02-23_final
2022-03-15 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-03-15_final
2022-04-14 12:04:34	ga_s2am_ard_3-2-1_49KGP_2022-04-14_final
2022-04-14 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-04-14_final
2022-04-21 11:57:14	ga_s2am_ard_3-2-1_50HLH_2022-04-21_final
2022-04-27 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-04-27_final
2022-05-07 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2022-05-07_final
2022-05-08 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-05-08_final
2022-05-24 12:04:25	ga_s2am_ard_3-2-1_49KGQ_2022-05-24_final
2022-06-06 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-06-06_final
2022-06-23 12:04:41	ga_s2am_ard_3-2-1_49KGP_2022-06-23_final
2022-07-13 12:04:46	ga_s2am_ard_3-2-1_49KHP_2022-07-13_final
2022-08-05 12:14:24	ga_s2am_ard_3-2-1_49KGQ_2022-08-05_final
2022-08-12 12:04:43	ga_s2am_ard_3-2-1_49KGP_2022-08-12_final
2022-08-15 12:14:07	ga_s2am_ard_3-2-1_49KHR_2022-08-15_final
2022-08-22 12:05:42	ga_s2am_ard_3-2-1_49JGK_2022-08-22_final
2022-09-04 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-09-04_final.stac-item
2022-10-01 12:04:41	ga_s2am_ard_3-2-1_49KHP_2022-10-01_final.stac-item
2022-10-14 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-10-14_final.stac-item
2022-10-14 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-10-14_final.stac-item
2022-11-10 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2022-11-10_final.stac-item
2022-11-10 12:05:18	ga_s2am_ard_3-2-1_49JGL_2022-11-10_final.stac-item
2022-11-13 12:14:01	ga_s2am_ard_3-2-1_49KGR_2022-11-13_final.stac-item
2022-11-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-11-13_final.stac-item
2022-11-20 12:04:32	ga_s2am_ard_3-2-1_49KGP_2022-11-20_final.stac-item
2022-12-13 12:13:58	ga_s2am_ard_3-2-1_49KGR_2022-12-13_final.stac-item
2023-02-28 12:04:26	ga_s2am_ard_3-2-1_49KGP_2023-02-28_final.stac-item
2023-02-28 12:04:31	ga_s2am_ard_3-2-1_49KHP_2023-02-28_final.stac-item
2023-02-28 12:04:32	ga_s2am_ard_3-2-1_49KGP_2023-02-28_final.stac-item
2023-03-10 12:04:28	ga_s2am_ard_3-2-1_49KHP_2023-03-10_final.stac-item
2023-04-19 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-04-19_final.stac-item
2023-04-19 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-04-19_final.stac-item
2023-06-08 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2023-06-08_final.stac-item
2023-07-18 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2023-07-18_final.stac-item
2023-07-28 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2023-07-28_final.stac-item
2023-08-11 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-08-11_final.stac-item
2023-08-20 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2023-08-20_final.stac-item
2023-10-06 12:05:30	ga_s2am_ard_3-2-1_49JGK_2023-10-06_final.stac-item
2023-10-29 12:13:58	ga_s2am_ard_3-2-1_49KGR_2023-10-29_final.stac-item
2023-11-08 12:13:58	ga_s2am_ard_3-2-1_49KGR_2023-11-08_final.stac-item
2023-11-08 12:14:59	ga_s2am_ard_3-2-1_49JFM_2023-11-08_final.stac-item
2023-11-15 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-11-15_final.stac-item
2023-11-18 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-11-18_final.stac-item
2023-12-05 12:03:52	ga_s2am_ard_3-2-1_49KHR_2023-12-05_final.stac-item
2024-01-07 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-01-07_final.stac-item
2024-01-17 12:14:19	ga_s2am_ard_3-2-1_49KGP_2024-01-17_final.stac-item
2024-01-24 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2024-01-24_final.stac-item
2024-02-06 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-02-06_final.stac-item
2024-02-10 11:57:18	ga_s2am_ard_3-2-1_50HLG_2024-02-10_final.stac-item
2024-02-16 12:14:54	ga_s2am_ard_3-2-1_49JGM_2024-02-16_final.stac-item
2024-02-23 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2024-02-23_final.stac-item
2024-03-17 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2024-03-17_final.stac-item
2024-03-21 11:57:23	ga_s2am_ard_3-2-1_50HLG_2024-03-21_final.stac-item
2024-03-24 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2024-03-24_final.stac-item
2024-04-16 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2024-04-16_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

All years