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
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_49JHM_2015-11-27_final.stac-item
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KHR_2015-11-30_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JHM_2016-01-26_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGR_2016-03-09_final.stac-item
2016-04-18 12:13:45	ga_s2am_ard_3-2-1_49KHQ_2016-04-18_final.stac-item
2016-04-25 12:04:45	ga_s2am_ard_3-2-1_49JHM_2016-04-25_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_49JGN_2016-06-14_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49KHP_2016-08-03_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49KHP_2016-08-23_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KGQ_2016-11-01_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49JGN_2016-12-01_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49JGN_2016-12-14_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_49JHM_2016-12-21_final
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_49KHP_2017-03-11_final
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49KHP_2017-05-10_final
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KGQ_2017-05-13_final
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49KGQ_2017-05-30_final
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HLH_2017-06-26_final
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGN_2017-06-29_final
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KHQ_2017-07-29_final
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49JGN_2017-08-01_final
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2017-11-19_final
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-03-19_final
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2018-03-19_final
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49KHQ_2018-05-08_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2018-09-25_final
2019-01-10 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2019-01-10_final
2019-01-13 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2019-01-13_final
2019-02-19 12:04:27	ga_s2am_ard_3-2-1_49KGP_2019-02-19_final
2019-04-03 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2019-04-03_final
2019-05-20 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-05-20_final
2019-05-30 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-05-30_final
2019-06-09 12:04:59	ga_s2am_ard_3-2-1_49JHM_2019-06-09_final
2019-06-23 11:47:18	ga_s2am_ard_3-2-1_50HLH_2019-06-23_final
2019-07-16 11:57:14	ga_s2am_ard_3-2-1_50HLH_2019-07-16_final
2019-07-19 12:04:33	ga_s2am_ard_3-2-1_49KHP_2019-07-19_final
2019-08-01 12:14:31	ga_s2am_ard_3-2-1_49KGP_2019-08-01_final
2019-08-22 11:47:16	ga_s2am_ard_3-2-1_50HLH_2019-08-22_final
2019-09-10 12:13:38	ga_s2am_ard_3-2-1_49KHS_2019-09-10_final.stac-item
2019-10-10 12:14:01	ga_s2am_ard_3-2-1_49KGR_2019-10-10_final
2019-10-10 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2019-10-10_final
2019-11-06 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-11-06_final
2019-11-26 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-11-26_final
2019-11-26 12:04:46	ga_s2am_ard_3-2-1_49JGN_2019-11-26_final
2020-01-25 12:04:36	ga_s2am_ard_3-2-1_49JHN_2020-01-25_final
2020-02-07 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2020-02-07_final
2020-02-24 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2020-02-24_final
2020-02-24 12:04:37	ga_s2am_ard_3-2-1_49JHN_2020-02-24_final
2020-03-08 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2020-03-08_final
2020-05-04 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2020-05-04_final
2020-05-04 12:05:00	ga_s2am_ard_3-2-1_49JHM_2020-05-04_final
2020-08-22 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-08-22_final
2020-11-23 12:14:10	ga_s2am_ard_3-2-1_49KHQ_2020-11-23_final
2021-04-22 12:14:04	ga_s2am_ard_3-2-1_49KHQ_2021-04-22_final
2021-11-15 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2021-11-15_final
2021-11-15 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-11-15_final
2021-12-05 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-12-05_final
2021-12-15 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2021-12-15_final
2021-12-19 11:47:27	ga_s2am_ard_3-2-1_50HLG_2021-12-19_final.stac-item
2022-01-21 11:56:40	ga_s2am_ard_3-2-1_50HLK_2022-01-21_final
2022-02-23 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2022-02-23_final
2022-02-23 12:04:24	ga_s2am_ard_3-2-1_49KHP_2022-02-23_final
2022-03-18 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-03-18_final
2022-03-28 12:14:21	ga_s2am_ard_3-2-1_49KGP_2022-03-28_final
2022-05-14 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2022-05-14_final
2022-05-14 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2022-05-14_final
2022-05-24 12:04:33	ga_s2am_ard_3-2-1_49KHP_2022-05-24_final
2022-05-28 11:47:22	ga_s2am_ard_3-2-1_50HLH_2022-05-28_final
2022-06-23 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-06-23_final
2022-08-22 12:04:31	ga_s2am_ard_3-2-1_49KGQ_2022-08-22_final
2022-09-11 12:04:24	ga_s2am_ard_3-2-1_49KHQ_2022-09-11_final.stac-item
2022-10-21 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-10-21_final.stac-item
2022-11-30 12:04:57	ga_s2am_ard_3-2-1_49JHM_2022-11-30_final.stac-item
2022-12-10 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-12-10_final.stac-item
2022-12-10 12:04:57	ga_s2am_ard_3-2-1_49JHM_2022-12-10_final.stac-item
2022-12-17 11:56:39	ga_s2am_ard_3-2-1_50HLK_2022-12-17_final.stac-item
2022-12-30 12:04:27	ga_s2am_ard_3-2-1_49KHP_2022-12-30_final.stac-item
2022-12-30 12:04:41	ga_s2am_ard_3-2-1_49JHN_2022-12-30_final.stac-item
2023-01-09 12:04:26	ga_s2am_ard_3-2-1_49KHP_2023-01-09_final.stac-item
2023-01-29 12:04:44	ga_s2am_ard_3-2-1_49JGN_2023-01-29_final.stac-item
2023-02-18 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-02-18_final.stac-item
2023-02-28 12:04:24	ga_s2am_ard_3-2-1_49KHP_2023-02-28_final.stac-item
2023-04-09 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2023-04-09_final.stac-item
2023-04-09 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2023-04-09_final.stac-item
2023-04-09 12:04:33	ga_s2am_ard_3-2-1_49JHN_2023-04-09_final.stac-item
2023-04-29 12:04:28	ga_s2am_ard_3-2-1_49KHP_2023-04-29_final.stac-item
2023-05-19 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2023-05-19_final.stac-item
2023-07-08 12:04:33	ga_s2am_ard_3-2-1_49KHP_2023-07-08_final.stac-item
2023-07-18 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2023-07-18_final.stac-item
2023-09-06 12:04:33	ga_s2am_ard_3-2-1_49KHP_2023-09-06_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
2023-10-06 12:04:29	ga_s2am_ard_3-2-1_49KHP_2023-10-06_final.stac-item
2023-10-09 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-10-09_final.stac-item
2023-10-09 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-10-09_final.stac-item
2023-10-16 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2023-10-16_final.stac-item
2023-12-25 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-12-25_final.stac-item
2024-01-14 12:04:39	ga_s2am_ard_3-2-1_49JGN_2024-01-14_final.stac-item
2024-03-31 11:56:39	ga_s2am_ard_3-2-1_50HLK_2024-03-31_final.stac-item
2024-04-03 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2024-04-03_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

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