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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLQ_2015-12-17_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQH_2015-12-21_final.stac-item
2016-04-25 12:04:45	ga_s2am_ard_3-2-1_50JKT_2016-04-25_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JKQ_2016-09-02_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHP_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HLG_2016-12-15_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_50JLQ_2017-04-10_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_50JKR_2017-04-30_final
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KHP_2017-05-13_final
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_50JKR_2017-06-09_final
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2017-07-09_final
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2017-11-06_final
2018-01-15 12:04:34	ga_s2am_ard_3-2-1_50JKT_2018-01-15_final
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_50JKR_2018-03-16_final
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49KHP_2018-03-29_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JLQ_2018-04-05_final
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-04-08_final
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_50JKR_2018-04-15_final
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49KHP_2018-04-18_final
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KHP_2018-04-28_final
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JLQ_2018-05-05_final
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49KHP_2018-05-08_final
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49KHP_2018-05-18_final
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKR_2018-06-24_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JLQ_2018-09-09_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLQ_2018-09-19_final
2019-01-20 12:05:04	ga_s2am_ard_3-2-1_50JLR_2019-01-20_final
2019-01-27 11:57:17	ga_s2am_ard_3-2-1_50HMG_2019-01-27_final.stac-item
2019-02-06 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-02-06_final
2019-02-16 11:55:24	ga_s2am_ard_3-2-1_50JLQ_2019-02-16_final
2019-03-28 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2019-03-28_final
2019-04-14 11:47:26	ga_s2am_ard_3-2-1_50HMG_2019-04-14_final.stac-item
2019-05-17 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2019-05-17_final
2019-06-19 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2019-06-19_final
2019-07-29 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2019-07-29_final
2019-08-11 12:13:43	ga_s2am_ard_3-2-1_49KHS_2019-08-11_final.stac-item
2019-08-28 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2019-08-28_final
2019-10-07 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2019-10-07_final
2019-10-14 11:55:16	ga_s2am_ard_3-2-1_50JLR_2019-10-14_final
2019-10-17 12:05:11	ga_s2am_ard_3-2-1_50JLR_2019-10-17_final
2019-11-06 12:05:11	ga_s2am_ard_3-2-1_50JLR_2019-11-06_final
2019-11-26 12:05:08	ga_s2am_ard_3-2-1_50JLR_2019-11-26_final
2019-12-20 11:47:08	ga_s2am_ard_3-2-1_50HLH_2019-12-20_final
2020-03-05 12:05:18	ga_s2am_ard_3-2-1_50JLQ_2020-03-05_final
2020-04-24 12:05:10	ga_s2am_ard_3-2-1_50JLR_2020-04-24_final
2020-05-14 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2020-05-14_final
2020-05-21 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-05-21_final
2020-05-21 11:57:26	ga_s2am_ard_3-2-1_50HMG_2020-05-21_final.stac-item
2020-05-31 11:55:19	ga_s2am_ard_3-2-1_50JLR_2020-05-31_final
2020-06-20 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2020-06-20_final
2020-07-13 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2020-07-13_final
2020-08-12 12:03:50	ga_s2am_ard_3-2-1_49KHS_2020-08-12_final.stac-item
2020-10-18 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-10-18_final
2020-11-03 12:14:26	ga_s2am_ard_3-2-1_49KHP_2020-11-03_final
2020-11-20 12:05:11	ga_s2am_ard_3-2-1_50JLR_2020-11-20_final
2021-04-19 12:05:01	ga_s2am_ard_3-2-1_50JLR_2021-04-19_final
2021-05-19 12:05:08	ga_s2am_ard_3-2-1_50JLR_2021-05-19_final
2021-08-17 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-08-17_final.stac-item
2021-08-21 11:47:30	ga_s2am_ard_3-2-1_50HLG_2021-08-21_final.stac-item
2021-09-19 12:14:23	ga_s2am_ard_3-2-1_49KHP_2021-09-19_final
2021-09-23 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2021-09-23_final
2021-10-03 11:57:28	ga_s2am_ard_3-2-1_50HLG_2021-10-03_final.stac-item
2021-11-15 12:05:09	ga_s2am_ard_3-2-1_50JLR_2021-11-15_final
2021-12-12 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2021-12-12_final
2021-12-19 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-12-19_final.stac-item
2022-01-17 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-01-17_final
2022-01-24 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2022-01-24_final
2022-01-27 12:14:21	ga_s2am_ard_3-2-1_49KHP_2022-01-27_final
2022-02-13 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2022-02-13_final
2022-03-05 12:05:07	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
2022-03-08 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-03-08_final
2022-03-09 11:47:32	ga_s2am_ard_3-2-1_50HLG_2022-03-09_final.stac-item
2022-03-22 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-22_final
2022-05-01 11:55:18	ga_s2am_ard_3-2-1_50JLR_2022-05-01_final
2022-05-28 11:47:28	ga_s2am_ard_3-2-1_50HNG_2022-05-28_final.stac-item
2022-06-13 12:05:18	ga_s2am_ard_3-2-1_50JLR_2022-06-13_final
2022-06-23 12:05:20	ga_s2am_ard_3-2-1_50JLR_2022-06-23_final
2022-10-01 12:05:30	ga_s2am_ard_3-2-1_50JLQ_2022-10-01_final.stac-item
2022-12-07 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2022-12-07_final.stac-item
2023-02-08 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2023-02-08_final.stac-item
2023-03-20 12:05:21	ga_s2am_ard_3-2-1_50JLQ_2023-03-20_final.stac-item
2023-03-27 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2023-03-27_final.stac-item
2023-04-09 12:04:33	ga_s2am_ard_3-2-1_49JHN_2023-04-09_final.stac-item
2023-05-19 12:05:10	ga_s2am_ard_3-2-1_50JLR_2023-05-19_final.stac-item
2023-07-08 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2023-07-08_final.stac-item
2023-08-24 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2023-08-24_final.stac-item
2023-08-31 11:47:32	ga_s2am_ard_3-2-1_50HLG_2023-08-31_final.stac-item
2023-09-16 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2023-09-16_final.stac-item
2023-10-26 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2023-10-26_final.stac-item
2023-11-02 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2023-11-02_final.stac-item
2023-11-05 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2023-11-05_final.stac-item
2023-11-29 11:47:20	ga_s2am_ard_3-2-1_50HLG_2023-11-29_final.stac-item
2023-12-15 12:05:19	ga_s2am_ard_3-2-1_50JLQ_2023-12-15_final.stac-item
2024-02-07 11:46:49	ga_s2am_ard_3-2-1_50HQH_2024-02-07_final.stac-item
2024-02-13 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2024-02-13_final.stac-item
2024-03-24 12:05:13	ga_s2am_ard_3-2-1_50JKR_2024-03-24_final.stac-item
2024-03-28 11:47:27	ga_s2am_ard_3-2-1_50HLG_2024-03-28_final.stac-item
2024-04-10 11:57:22	ga_s2am_ard_3-2-1_50HLG_2024-04-10_final.stac-item
2024-04-26 12:15:02	ga_s2am_ard_3-2-1_49JFM_2024-04-26_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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