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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HLG_2015-11-21_final.stac-item
2016-03-29 12:13:41	ga_s2am_ard_3-2-1_49KHQ_2016-03-29_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JKR_2016-07-14_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JLQ_2016-08-23_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49KHP_2016-10-25_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KHP_2016-11-14_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JLQ_2016-11-18_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HQH_2016-12-15_final
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HLG_2017-01-24_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JLQ_2017-03-18_final
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_50JLQ_2017-03-21_final
2017-04-11 11:36:02	ga_s2am_ard_3-2-1_50HQK_2017-04-11_final
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KHP_2017-05-13_final
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JLQ_2017-05-17_final
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JLQ_2017-06-26_final
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLQ_2017-08-05_final
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JLQ_2017-08-18_final
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JLR_2017-08-18_final
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGN_2017-09-17_final
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLQ_2017-09-17_final
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JLQ_2017-10-24_final
2017-12-06 12:04:36	ga_s2am_ard_3-2-1_50JLQ_2017-12-06_final
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HLG_2018-02-01_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HMG_2018-02-11_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HLG_2018-02-28_final.stac-item
2018-03-07 11:36:09	ga_s2am_ard_3-2-1_50HQK_2018-03-07_final
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JLQ_2018-04-12_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLR_2018-05-22_final
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKR_2018-06-24_final
2018-11-28 11:55:19	ga_s2am_ard_3-2-1_50JLQ_2018-11-28_final
2019-02-13 11:47:23	ga_s2am_ard_3-2-1_50HLG_2019-02-13_final.stac-item
2019-03-01 12:05:07	ga_s2am_ard_3-2-1_50JLR_2019-03-01_final
2019-06-29 12:05:16	ga_s2am_ard_3-2-1_50JKR_2019-06-29_final
2019-07-12 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-07-12_final
2019-07-22 12:14:26	ga_s2am_ard_3-2-1_49KHP_2019-07-22_final
2019-08-08 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2019-08-08_final
2019-08-11 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-08-11_final
2019-08-18 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2019-08-18_final
2019-11-03 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2019-11-03_final
2020-03-02 11:55:08	ga_s2am_ard_3-2-1_50JLR_2020-03-02_final
2020-03-02 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2020-03-02_final
2020-04-11 11:57:19	ga_s2am_ard_3-2-1_50HMG_2020-04-11_final.stac-item
2020-04-21 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2020-04-21_final
2020-05-11 11:55:17	ga_s2am_ard_3-2-1_50JLR_2020-05-11_final
2020-05-11 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-05-11_final
2020-05-14 12:05:13	ga_s2am_ard_3-2-1_50JLR_2020-05-14_final
2020-05-21 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-05-21_final
2020-05-21 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2020-05-21_final
2020-06-03 12:05:14	ga_s2am_ard_3-2-1_50JLR_2020-06-03_final
2020-07-03 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2020-07-03_final
2020-09-14 12:13:44	ga_s2am_ard_3-2-1_49KHS_2020-09-14_final.stac-item
2020-10-18 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2020-10-18_final
2021-01-23 11:47:28	ga_s2am_ard_3-2-1_50HLG_2021-01-23_final.stac-item
2021-03-10 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2021-03-10_final
2021-10-13 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2021-10-13_final
2021-10-23 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2021-10-23_final
2021-11-22 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2021-11-22_final
2021-11-25 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2021-11-25_final
2021-12-25 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2021-12-25_final
2022-02-10 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2022-02-10_final
2022-03-05 12:05:09	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final
2022-03-05 12:05:13	ga_s2am_ard_3-2-1_50JLR_2022-03-05_final
2022-03-05 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-03-05_final
2022-03-22 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2022-03-22_final
2022-04-14 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2022-04-14_final
2022-05-01 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2022-05-01_final
2022-05-04 12:05:14	ga_s2am_ard_3-2-1_50JLR_2022-05-04_final
2022-05-04 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2022-05-04_final
2022-06-03 12:05:16	ga_s2am_ard_3-2-1_50JLR_2022-06-03_final
2022-06-03 12:05:31	ga_s2am_ard_3-2-1_50JLQ_2022-06-03_final
2022-08-12 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-08-12_final
2022-10-18 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2022-10-18_final.stac-item
2022-10-28 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-10-28_final.stac-item
2023-02-15 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2023-02-15_final.stac-item
2023-02-18 12:05:05	ga_s2am_ard_3-2-1_50JLR_2023-02-18_final.stac-item
2023-02-25 11:55:25	ga_s2am_ard_3-2-1_50JLQ_2023-02-25_final.stac-item
2023-03-07 11:55:09	ga_s2am_ard_3-2-1_50JLR_2023-03-07_final.stac-item
2023-03-10 12:05:03	ga_s2am_ard_3-2-1_50JLR_2023-03-10_final.stac-item
2023-03-10 12:05:18	ga_s2am_ard_3-2-1_50JLQ_2023-03-10_final.stac-item
2023-03-17 11:55:25	ga_s2am_ard_3-2-1_50JLQ_2023-03-17_final.stac-item
2023-03-20 12:05:06	ga_s2am_ard_3-2-1_50JLR_2023-03-20_final.stac-item
2023-03-27 11:55:11	ga_s2am_ard_3-2-1_50JLR_2023-03-27_final.stac-item
2023-04-19 12:05:07	ga_s2am_ard_3-2-1_50JLR_2023-04-19_final.stac-item
2023-04-19 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2023-04-19_final.stac-item
2023-05-16 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2023-05-16_final.stac-item
2023-05-19 12:05:10	ga_s2am_ard_3-2-1_50JLR_2023-05-19_final.stac-item
2023-05-19 12:05:14	ga_s2am_ard_3-2-1_50JKR_2023-05-19_final.stac-item
2023-07-15 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2023-07-15_final.stac-item
2023-08-01 11:47:32	ga_s2am_ard_3-2-1_50HLG_2023-08-01_final.stac-item
2023-08-14 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2023-08-14_final.stac-item
2023-08-24 11:55:19	ga_s2am_ard_3-2-1_50JLR_2023-08-24_final.stac-item
2023-08-24 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2023-08-24_final.stac-item
2023-08-27 12:05:14	ga_s2am_ard_3-2-1_50JLR_2023-08-27_final.stac-item
2023-08-27 12:05:29	ga_s2am_ard_3-2-1_50JLQ_2023-08-27_final.stac-item
2024-03-21 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2024-03-21_final.stac-item
2024-03-24 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2024-03-24_final.stac-item
2024-04-10 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2024-04-10_final.stac-item
2024-04-13 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2024-04-13_final.stac-item
2024-04-20 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2024-04-20_final.stac-item
2024-05-03 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2024-05-03_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