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
2021-03-15 09:34:58	ga_s2am_ard_3-2-1_56JKN_2021-03-15_final
2021-03-25 09:34:57	ga_s2am_ard_3-2-1_56JKN_2021-03-25_final
2021-04-04 09:34:55	ga_s2am_ard_3-2-1_56JKN_2021-04-04_final
2021-05-17 09:44:54	ga_s2am_ard_3-2-1_56JKN_2021-05-17_final
2021-05-27 09:44:55	ga_s2am_ard_3-2-1_56JKN_2021-05-27_final
2021-06-06 09:44:55	ga_s2am_ard_3-2-1_56JKN_2021-06-06_final
2021-06-16 09:44:54	ga_s2am_ard_3-2-1_56JKN_2021-06-16_final
2021-06-26 09:44:55	ga_s2am_ard_3-2-1_56JKN_2021-06-26_final
2021-07-06 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-07-06_final
2021-07-16 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-07-16_final
2021-07-26 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-07-26_final
2021-08-05 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-08-05_final
2021-08-15 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-08-15_final
2021-08-25 09:44:56	ga_s2am_ard_3-2-1_56JKN_2021-08-25_final
2021-09-04 09:44:55	ga_s2am_ard_3-2-1_56JKN_2021-09-04_final
2021-09-14 09:44:55	ga_s2am_ard_3-2-1_56JKN_2021-09-14_final
2021-09-24 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-09-24_final
2021-10-04 09:44:59	ga_s2am_ard_3-2-1_56JKN_2021-10-04_final
2021-10-14 09:44:59	ga_s2am_ard_3-2-1_56JKN_2021-10-14_final
2021-10-24 09:44:59	ga_s2am_ard_3-2-1_56JKN_2021-10-24_final
2021-11-03 09:44:58	ga_s2am_ard_3-2-1_56JKN_2021-11-03_final
2021-11-03 09:45:07	ga_s2am_ard_3-2-1_55JGH_2021-11-03_final
2021-11-13 09:44:56	ga_s2am_ard_3-2-1_56JKN_2021-11-13_final
2021-11-23 09:44:54	ga_s2am_ard_3-2-1_56JKN_2021-11-23_final
2021-12-03 09:44:53	ga_s2am_ard_3-2-1_56JKN_2021-12-03_final
2021-12-13 09:44:50	ga_s2am_ard_3-2-1_56JKN_2021-12-13_final
2021-12-13 09:44:57	ga_s2am_ard_3-2-1_56JKN_2021-12-13_final
2021-12-23 09:44:55	ga_s2am_ard_3-2-1_56JKN_2021-12-23_final
2022-01-02 09:44:56	ga_s2am_ard_3-2-1_56JKN_2022-01-02_final
2022-01-12 09:44:55	ga_s2am_ard_3-2-1_56JKN_2022-01-12_final
2022-01-22 09:44:54	ga_s2am_ard_3-2-1_56JKN_2022-01-22_final
2022-02-01 09:44:54	ga_s2am_ard_3-2-1_56JKN_2022-02-01_final
2022-02-11 09:44:53	ga_s2am_ard_3-2-1_56JKN_2022-02-11_final
2022-02-21 09:44:56	ga_s2am_ard_3-2-1_56JKN_2022-02-21_final
2022-03-03 09:44:58	ga_s2am_ard_3-2-1_56JKN_2022-03-03_final
2022-03-13 09:44:58	ga_s2am_ard_3-2-1_56JKN_2022-03-13_final
2022-03-23 09:44:57	ga_s2am_ard_3-2-1_56JKN_2022-03-23_final
2022-04-02 09:44:56	ga_s2am_ard_3-2-1_56JKN_2022-04-02_final
2022-04-12 09:44:56	ga_s2am_ard_3-2-1_56JKN_2022-04-12_final
2022-04-22 09:44:59	ga_s2am_ard_3-2-1_56JKN_2022-04-22_final
2022-05-02 09:44:59	ga_s2am_ard_3-2-1_56JKN_2022-05-02_final
2022-05-12 09:44:57	ga_s2am_ard_3-2-1_56JKN_2022-05-12_final
2022-05-22 09:45:01	ga_s2am_ard_3-2-1_56JKN_2022-05-22_final
2022-06-01 09:45:02	ga_s2am_ard_3-2-1_56JKN_2022-06-01_final
2022-06-11 09:45:03	ga_s2am_ard_3-2-1_56JKN_2022-06-11_final
2022-06-21 09:45:06	ga_s2am_ard_3-2-1_56JKN_2022-06-21_final
2022-07-01 09:45:07	ga_s2am_ard_3-2-1_56JKN_2022-07-01_final
2022-07-11 09:45:07	ga_s2am_ard_3-2-1_56JKN_2022-07-11_final
2022-07-21 09:45:05	ga_s2am_ard_3-2-1_56JKN_2022-07-21_final
2022-07-31 09:45:04	ga_s2am_ard_3-2-1_56JKN_2022-07-31_final
2022-08-20 09:45:07	ga_s2am_ard_3-2-1_56JKN_2022-08-20_final
2022-08-30 09:45:06	ga_s2am_ard_3-2-1_56JKN_2022-08-30_final
2022-09-09 09:45:05	ga_s2am_ard_3-2-1_56JKN_2022-09-09_final.stac-item
2022-09-19 09:45:02	ga_s2am_ard_3-2-1_56JKN_2022-09-19_final.stac-item
2022-09-29 09:45:01	ga_s2am_ard_3-2-1_56JKN_2022-09-29_final.stac-item
2022-10-09 09:45:00	ga_s2am_ard_3-2-1_56JKN_2022-10-09_final.stac-item
2022-10-19 09:44:56	ga_s2am_ard_3-2-1_56JKN_2022-10-19_final.stac-item
2022-10-29 09:44:58	ga_s2am_ard_3-2-1_56JKN_2022-10-29_final.stac-item
2022-11-18 09:44:56	ga_s2am_ard_3-2-1_56JKN_2022-11-18_final.stac-item
2022-11-28 09:44:54	ga_s2am_ard_3-2-1_56JKN_2022-11-28_final.stac-item
2022-12-08 09:44:55	ga_s2am_ard_3-2-1_56JKN_2022-12-08_final.stac-item
2022-12-18 09:44:53	ga_s2am_ard_3-2-1_56JKN_2022-12-18_final.stac-item
2022-12-28 09:44:53	ga_s2am_ard_3-2-1_56JKN_2022-12-28_final.stac-item
2023-01-07 09:44:53	ga_s2am_ard_3-2-1_56JKN_2023-01-07_final.stac-item
2023-01-27 09:44:51	ga_s2am_ard_3-2-1_56JKN_2023-01-27_final.stac-item
2023-02-06 09:44:53	ga_s2am_ard_3-2-1_56JKN_2023-02-06_final.stac-item
2023-02-26 09:44:52	ga_s2am_ard_3-2-1_56JKN_2023-02-26_final.stac-item
2023-03-18 09:44:52	ga_s2am_ard_3-2-1_56JKN_2023-03-18_final.stac-item
2023-04-07 09:44:54	ga_s2am_ard_3-2-1_56JKN_2023-04-07_final.stac-item
2023-04-17 09:44:53	ga_s2am_ard_3-2-1_56JKN_2023-04-17_final.stac-item
2023-04-27 09:44:54	ga_s2am_ard_3-2-1_56JKN_2023-04-27_final.stac-item
2023-05-07 09:44:54	ga_s2am_ard_3-2-1_56JKN_2023-05-07_final.stac-item
2023-05-27 09:44:58	ga_s2am_ard_3-2-1_56JKN_2023-05-27_final.stac-item
2023-06-16 09:44:58	ga_s2am_ard_3-2-1_56JKN_2023-06-16_final.stac-item
2023-06-23 09:35:02	ga_s2am_ard_3-2-1_56JKN_2023-06-23_final.stac-item
2023-07-03 09:35:03	ga_s2am_ard_3-2-1_56JKN_2023-07-03_final.stac-item
2023-07-13 09:35:03	ga_s2am_ard_3-2-1_56JKN_2023-07-13_final.stac-item
2023-07-23 09:35:03	ga_s2am_ard_3-2-1_56JKN_2023-07-23_final.stac-item
2023-08-02 09:35:04	ga_s2am_ard_3-2-1_56JKN_2023-08-02_final.stac-item
2023-08-05 09:44:59	ga_s2am_ard_3-2-1_56JKN_2023-08-05_final.stac-item
2023-08-12 09:35:03	ga_s2am_ard_3-2-1_56JKN_2023-08-12_final.stac-item
2023-08-22 09:35:04	ga_s2am_ard_3-2-1_56JKN_2023-08-22_final.stac-item
2023-09-01 09:35:03	ga_s2am_ard_3-2-1_56JKN_2023-09-01_final.stac-item
2023-09-11 09:35:03	ga_s2am_ard_3-2-1_56JKN_2023-09-11_final.stac-item
2023-09-21 09:35:00	ga_s2am_ard_3-2-1_56JKN_2023-09-21_final.stac-item
2023-10-01 09:35:00	ga_s2am_ard_3-2-1_56JKN_2023-10-01_final.stac-item
2023-10-11 09:34:57	ga_s2am_ard_3-2-1_56JKN_2023-10-11_final.stac-item
2023-10-21 09:34:58	ga_s2am_ard_3-2-1_56JKN_2023-10-21_final.stac-item
2023-10-31 09:34:58	ga_s2am_ard_3-2-1_56JKN_2023-10-31_final.stac-item
2023-11-10 09:34:58	ga_s2am_ard_3-2-1_56JKN_2023-11-10_final.stac-item
2023-11-20 09:34:55	ga_s2am_ard_3-2-1_56JKN_2023-11-20_final.stac-item
2023-12-10 09:34:53	ga_s2am_ard_3-2-1_56JKN_2023-12-10_final.stac-item
2023-12-20 09:34:54	ga_s2am_ard_3-2-1_56JKN_2023-12-20_final.stac-item
2023-12-30 09:34:55	ga_s2am_ard_3-2-1_56JKN_2023-12-30_final.stac-item
2024-01-09 09:34:54	ga_s2am_ard_3-2-1_56JKN_2024-01-09_final.stac-item
2024-01-19 09:34:49	ga_s2am_ard_3-2-1_56JKN_2024-01-19_final.stac-item
2024-01-29 09:34:53	ga_s2am_ard_3-2-1_56JKN_2024-01-29_final.stac-item
2024-02-08 09:34:54	ga_s2am_ard_3-2-1_56JKN_2024-02-08_final.stac-item
2024-02-18 09:34:56	ga_s2am_ard_3-2-1_56JKN_2024-02-18_final.stac-item
2024-02-28 09:34:58	ga_s2am_ard_3-2-1_56JKN_2024-02-28_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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