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 12:09:42	ga_s2am_ard_3-2-1_49KHP_2015-10-21_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHQ_2015-10-28_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_49JGN_2015-11-27_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49JHM_2015-12-17_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHP_2016-08-26_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KGR_2016-09-25_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KHP_2016-11-14_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49KHP_2016-12-01_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-12_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49JGN_2017-02-22_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KGP_2017-02-22_final
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KHP_2017-03-14_final
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KHQ_2017-11-09_final
2018-12-04 12:13:46	ga_s2am_ard_3-2-1_49KHR_2018-12-04_final
2019-01-13 12:14:17	ga_s2am_ard_3-2-1_49KHP_2019-01-13_final
2019-01-20 12:03:41	ga_s2am_ard_3-2-1_49KHS_2019-01-20_final.stac-item
2019-01-20 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-01-20_final
2019-01-30 12:04:43	ga_s2am_ard_3-2-1_49JGN_2019-01-30_final
2019-02-12 12:13:51	ga_s2am_ard_3-2-1_49KHR_2019-02-12_final
2019-02-12 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-12_final
2019-03-11 12:04:26	ga_s2am_ard_3-2-1_49KGP_2019-03-11_final
2019-03-14 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-03-14_final
2019-03-21 12:04:29	ga_s2am_ard_3-2-1_49KGP_2019-03-21_final
2019-04-10 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-04-10_final
2019-05-17 11:57:13	ga_s2am_ard_3-2-1_50HLH_2019-05-17_final
2019-09-20 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-09-20_final
2019-10-30 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-10-30_final
2019-11-06 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2019-11-06_final
2019-11-09 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-11-09_final
2019-12-16 12:04:51	ga_s2am_ard_3-2-1_49JHM_2019-12-16_final
2020-02-27 12:13:50	ga_s2am_ard_3-2-1_49KHR_2020-02-27_final
2020-05-11 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-05-11_final
2020-05-27 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2020-05-27_final
2020-06-03 12:04:13	ga_s2am_ard_3-2-1_49KHR_2020-06-03_final
2020-08-22 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-08-22_final
2020-09-01 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-09-01_final
2020-10-01 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-10-01_final
2020-11-13 12:14:25	ga_s2am_ard_3-2-1_49KHP_2020-11-13_final
2020-12-03 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2020-12-03_final
2020-12-10 12:04:24	ga_s2am_ard_3-2-1_49KHP_2020-12-10_final
2021-10-06 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2021-10-06_final
2021-11-15 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2021-11-15_final
2021-11-18 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-11-18_final
2021-11-25 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-11-25_final
2021-11-28 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-11-28_final
2022-01-14 12:05:16	ga_s2am_ard_3-2-1_49JGL_2022-01-14_final
2022-02-03 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-03_final
2022-02-16 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-02-16_final
2022-02-16 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-02-16_final
2022-02-23 12:04:01	ga_s2am_ard_3-2-1_49KHR_2022-02-23_final
2022-04-11 11:57:10	ga_s2am_ard_3-2-1_50HLH_2022-04-11_final
2022-04-14 12:04:31	ga_s2am_ard_3-2-1_49KHP_2022-04-14_final
2022-04-14 12:04:59	ga_s2am_ard_3-2-1_49JHM_2022-04-14_final
2022-04-14 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-04-14_final
2022-05-08 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-05-08_final
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-05-24_final
2022-06-07 11:47:22	ga_s2am_ard_3-2-1_50HLH_2022-06-07_final
2022-07-03 12:04:41	ga_s2am_ard_3-2-1_49KHP_2022-07-03_final
2022-07-06 12:14:08	ga_s2am_ard_3-2-1_49KHR_2022-07-06_final
2022-07-13 12:04:41	ga_s2am_ard_3-2-1_49KGP_2022-07-13_final
2022-07-13 12:04:46	ga_s2am_ard_3-2-1_49KHP_2022-07-13_final
2022-08-15 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-08-15_final
2022-08-29 11:57:07	ga_s2am_ard_3-2-1_50HLJ_2022-08-29_final
2022-10-01 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-10-01_final.stac-item
2022-10-04 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-10-04_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 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2022-11-20_final.stac-item
2022-11-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2022-11-23_final.stac-item
2022-12-03 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-12-03_final.stac-item
2022-12-30 12:05:28	ga_s2am_ard_3-2-1_49JGK_2022-12-30_final.stac-item
2023-01-02 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-01-02_final.stac-item
2023-01-02 12:14:26	ga_s2am_ard_3-2-1_49KGP_2023-01-02_final.stac-item
2023-02-08 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-02-08_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
2023-03-20 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-03-20_final.stac-item
2023-04-19 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-04-19_final.stac-item
2023-05-09 12:04:32	ga_s2am_ard_3-2-1_49KGP_2023-05-09_final.stac-item
2023-06-11 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2023-06-11_final.stac-item
2023-06-15 11:57:17	ga_s2am_ard_3-2-1_50HLH_2023-06-15_final.stac-item
2023-07-28 12:04:36	ga_s2am_ard_3-2-1_49KGP_2023-07-28_final.stac-item
2023-08-27 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2023-08-27_final.stac-item
2023-09-09 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-09-09_final.stac-item
2023-09-16 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2023-09-16_final.stac-item
2023-09-26 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2023-09-26_final.stac-item
2023-10-19 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-10-19_final.stac-item
2023-10-26 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2023-10-26_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 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-11-15_final.stac-item
2023-11-15 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-11-15_final.stac-item
2023-11-22 11:57:05	ga_s2am_ard_3-2-1_50HLH_2023-11-22_final.stac-item
2024-01-07 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2024-01-07_final.stac-item
2024-01-17 12:14:13	ga_s2am_ard_3-2-1_49KHP_2024-01-17_final.stac-item
2024-02-03 12:05:25	ga_s2am_ard_3-2-1_49JGK_2024-02-03_final.stac-item
2024-02-06 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2024-02-06_final.stac-item
2024-03-04 12:05:15	ga_s2am_ard_3-2-1_49JGL_2024-03-04_final.stac-item
2024-03-17 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-17_final.stac-item
2024-04-03 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2024-04-03_final.stac-item
2024-04-06 12:14:11	ga_s2am_ard_3-2-1_49KGQ_2024-04-06_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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