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
2015-10-20 09:23:08	ga_s2am_ard_3-2-1_56JLL_2015-10-19_final.stac-item
2015-12-19 09:29:18	ga_s2am_ard_3-2-1_56JLL_2015-12-18_final.stac-item
2016-01-18 09:29:15	ga_s2am_ard_3-2-1_56JLL_2016-01-17_final.stac-item
2016-02-17 09:25:19	ga_s2am_ard_3-2-1_56JLL_2016-02-16_final.stac-item
2016-07-06 09:22:47	ga_s2am_ard_3-2-1_56JLL_2016-07-05_final.stac-item
2016-07-26 09:23:14	ga_s2am_ard_3-2-1_56JLL_2016-07-25_final.stac-item
2016-10-04 09:22:40	ga_s2am_ard_3-2-1_56JLL_2016-10-03_final.stac-item
2016-10-24 09:22:41	ga_s2am_ard_3-2-1_56JLL_2016-10-23_final.stac-item
2020-12-22 09:25:28	ga_s2am_ard_3-2-1_56JLL_2020-12-21_final
2021-01-01 09:25:30	ga_s2am_ard_3-2-1_56JLL_2020-12-31_final
2021-01-21 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-01-20_final
2021-01-31 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-01-30_final
2021-03-02 09:25:29	ga_s2am_ard_3-2-1_56JLL_2021-03-01_final
2021-03-22 09:25:28	ga_s2am_ard_3-2-1_56JLL_2021-03-21_final
2021-04-01 09:25:27	ga_s2am_ard_3-2-1_56JLL_2021-03-31_final
2021-04-11 09:25:25	ga_s2am_ard_3-2-1_56JLL_2021-04-10_final
2021-04-21 09:25:25	ga_s2am_ard_3-2-1_56JLL_2021-04-20_final
2021-05-01 09:25:27	ga_s2am_ard_3-2-1_56JLL_2021-04-30_final
2021-05-31 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-05-30_final
2021-06-10 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-06-09_final
2021-06-20 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-06-19_final
2021-07-10 09:25:32	ga_s2am_ard_3-2-1_56JLL_2021-07-09_final
2021-07-20 09:25:33	ga_s2am_ard_3-2-1_56JLL_2021-07-19_final
2021-07-30 09:25:33	ga_s2am_ard_3-2-1_56JLL_2021-07-29_final
2021-08-19 09:25:32	ga_s2am_ard_3-2-1_56JLL_2021-08-18_final
2021-08-29 09:25:31	ga_s2am_ard_3-2-1_56JLL_2021-08-28_final
2021-09-08 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-09-07_final
2021-10-18 09:25:35	ga_s2am_ard_3-2-1_56JLL_2021-10-17_final
2021-11-17 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-11-16_final
2021-12-07 09:25:29	ga_s2am_ard_3-2-1_56JLL_2021-12-06_final
2021-12-17 09:25:30	ga_s2am_ard_3-2-1_56JLL_2021-12-16_final
2021-12-27 09:25:31	ga_s2am_ard_3-2-1_56JLL_2021-12-26_final
2022-01-06 09:25:31	ga_s2am_ard_3-2-1_56JLL_2022-01-05_final
2022-01-16 09:25:30	ga_s2am_ard_3-2-1_56JLL_2022-01-15_final
2022-01-26 09:25:30	ga_s2am_ard_3-2-1_56JLL_2022-01-25_final
2022-02-25 09:25:32	ga_s2am_ard_3-2-1_56JLL_2022-02-24_final
2022-03-07 09:25:33	ga_s2am_ard_3-2-1_56JLL_2022-03-06_final
2022-03-17 09:25:33	ga_s2am_ard_3-2-1_56JLL_2022-03-16_final
2022-03-27 09:25:32	ga_s2am_ard_3-2-1_56JLL_2022-03-26_final
2022-04-16 09:25:33	ga_s2am_ard_3-2-1_56JLL_2022-04-15_final
2022-05-06 09:25:34	ga_s2am_ard_3-2-1_56JLL_2022-05-05_final
2022-05-16 09:25:34	ga_s2am_ard_3-2-1_56JLL_2022-05-15_final
2022-05-26 09:25:37	ga_s2am_ard_3-2-1_56JLL_2022-05-25_final
2022-06-15 09:25:40	ga_s2am_ard_3-2-1_56JLL_2022-06-14_final
2022-06-25 09:25:42	ga_s2am_ard_3-2-1_56JLL_2022-06-24_final
2022-07-25 09:25:40	ga_s2am_ard_3-2-1_56JLL_2022-07-24_final
2022-08-17 09:35:42	ga_s2am_ard_3-2-1_56JLL_2022-08-17_final
2022-09-03 09:25:42	ga_s2am_ard_3-2-1_56JLL_2022-09-02_final.stac-item
2022-09-23 09:25:36	ga_s2am_ard_3-2-1_56JLL_2022-09-22_final.stac-item
2022-10-03 09:25:37	ga_s2am_ard_3-2-1_56JLL_2022-10-02_final.stac-item
2022-10-13 09:25:35	ga_s2am_ard_3-2-1_56JLL_2022-10-12_final.stac-item
2022-11-22 09:25:30	ga_s2am_ard_3-2-1_56JLL_2022-11-21_final.stac-item
2022-12-22 09:28:16	ga_s2am_ard_3-2-1_56GMU_2022-12-21_nrt.stac-item
2023-01-01 09:28:17	ga_s2am_ard_3-2-1_56GMU_2022-12-31_nrt.stac-item
2023-01-11 09:28:16	ga_s2am_ard_3-2-1_56GMU_2023-01-10_nrt.stac-item
2023-01-21 09:28:13	ga_s2am_ard_3-2-1_56GMU_2023-01-20_nrt.stac-item
2023-01-31 09:28:16	ga_s2am_ard_3-2-1_56GMU_2023-01-30_nrt.stac-item
2023-02-10 09:28:17	ga_s2am_ard_3-2-1_56GMU_2023-02-09_nrt.stac-item
2023-03-02 09:28:15	ga_s2am_ard_3-2-1_56GMU_2023-03-01_nrt.stac-item
2023-03-12 09:28:14	ga_s2am_ard_3-2-1_56GMU_2023-03-11_nrt.stac-item
2023-03-22 09:28:16	ga_s2am_ard_3-2-1_56GMU_2023-03-21_nrt.stac-item
2023-04-01 09:28:17	ga_s2am_ard_3-2-1_56GMU_2023-03-31_nrt.stac-item
2023-04-11 09:28:18	ga_s2am_ard_3-2-1_56GMU_2023-04-10_nrt.stac-item
2023-04-21 09:28:16	ga_s2am_ard_3-2-1_56GMU_2023-04-20_nrt.stac-item
2023-05-01 09:28:18	ga_s2am_ard_3-2-1_56GMU_2023-04-30_nrt.stac-item
2023-05-11 09:28:17	ga_s2am_ard_3-2-1_56GMU_2023-05-10_nrt.stac-item
2023-05-21 09:28:20	ga_s2am_ard_3-2-1_56GMU_2023-05-20_nrt.stac-item
2023-05-31 09:28:22	ga_s2am_ard_3-2-1_56GMU_2023-05-30_nrt.stac-item
2023-06-10 09:28:22	ga_s2am_ard_3-2-1_56GMU_2023-06-09_nrt.stac-item
2023-06-20 09:28:22	ga_s2am_ard_3-2-1_56GMU_2023-06-19_nrt.stac-item
2023-06-30 09:28:22	ga_s2am_ard_3-2-1_56GMU_2023-06-29_nrt.stac-item
2023-07-10 09:28:23	ga_s2am_ard_3-2-1_56GMU_2023-07-09_nrt.stac-item
2023-07-20 09:28:22	ga_s2am_ard_3-2-1_56GMU_2023-07-19_nrt.stac-item
2023-07-30 09:28:23	ga_s2am_ard_3-2-1_56GMU_2023-07-29_nrt.stac-item
2023-08-09 09:28:22	ga_s2am_ard_3-2-1_56GMU_2023-08-08_nrt.stac-item
2023-08-19 09:28:24	ga_s2am_ard_3-2-1_56GMU_2023-08-18_nrt.stac-item
2023-08-29 09:28:23	ga_s2am_ard_3-2-1_56GMU_2023-08-28_nrt.stac-item
2023-09-08 09:28:23	ga_s2am_ard_3-2-1_56GMU_2023-09-07_nrt.stac-item
2023-09-18 09:28:21	ga_s2am_ard_3-2-1_56GMU_2023-09-17_nrt.stac-item
2023-09-28 09:28:20	ga_s2am_ard_3-2-1_56GMU_2023-09-27_nrt.stac-item
2023-10-08 09:28:18	ga_s2am_ard_3-2-1_56GMU_2023-10-07_nrt.stac-item
2023-10-18 09:28:17	ga_s2am_ard_3-2-1_56GMU_2023-10-17_nrt.stac-item
2023-10-28 09:28:18	ga_s2am_ard_3-2-1_56GMU_2023-10-27_nrt.stac-item
2023-11-17 09:28:16	ga_s2am_ard_3-2-1_56GMU_2023-11-16_nrt.stac-item
2023-11-27 09:28:12	ga_s2am_ard_3-2-1_56GMU_2023-11-26_nrt.stac-item
2023-12-07 09:28:12	ga_s2am_ard_3-2-1_56GMU_2023-12-06_nrt.stac-item
2023-12-17 09:28:14	ga_s2am_ard_3-2-1_56GMU_2023-12-16_nrt.stac-item
2023-12-27 09:28:15	ga_s2am_ard_3-2-1_56GMU_2023-12-26_nrt.stac-item
2024-01-06 09:28:14	ga_s2am_ard_3-2-1_56GMU_2024-01-05_nrt.stac-item
2024-01-16 09:28:11	ga_s2am_ard_3-2-1_56GMU_2024-01-15_nrt.stac-item
2024-01-26 09:28:12	ga_s2am_ard_3-2-1_56GMU_2024-01-25_nrt.stac-item
2024-02-05 09:28:14	ga_s2am_ard_3-2-1_56GMU_2024-02-04_nrt.stac-item
2024-02-15 09:28:16	ga_s2am_ard_3-2-1_56GMU_2024-02-14_nrt.stac-item
2024-02-25 09:28:17	ga_s2am_ard_3-2-1_56GMU_2024-02-24_nrt.stac-item
2024-03-06 09:28:18	ga_s2am_ard_3-2-1_56GMU_2024-03-05_nrt.stac-item
2024-03-16 09:28:18	ga_s2am_ard_3-2-1_56GMU_2024-03-15_nrt.stac-item
2024-03-26 09:28:19	ga_s2am_ard_3-2-1_56GMU_2024-03-25_nrt.stac-item
2024-04-05 09:28:15	ga_s2am_ard_3-2-1_56GMU_2024-04-04_nrt.stac-item
2024-04-15 09:28:20	ga_s2am_ard_3-2-1_56GMU_2024-04-14_nrt.stac-item
2024-04-25 09:28:20	ga_s2am_ard_3-2-1_56GMU_2024-04-24_nrt.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

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