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
2019-06-25 10:45:45	ga_s2am_ard_3-2-1_53JLG_2019-06-25_final
2019-07-25 10:45:45	ga_s2am_ard_3-2-1_53JLG_2019-07-25_final
2019-08-04 10:45:45	ga_s2am_ard_3-2-1_53JLG_2019-08-04_final
2019-09-03 10:45:40	ga_s2am_ard_3-2-1_53JLG_2019-09-03_final
2019-11-22 10:45:41	ga_s2am_ard_3-2-1_53JLG_2019-11-22_final
2020-01-21 10:45:34	ga_s2am_ard_3-2-1_53JLG_2020-01-21_final
2020-01-31 10:45:33	ga_s2am_ard_3-2-1_53JLG_2020-01-31_final
2020-03-11 10:45:36	ga_s2am_ard_3-2-1_53JLG_2020-03-11_final
2020-03-21 10:45:37	ga_s2am_ard_3-2-1_53JLG_2020-03-21_final
2020-04-20 10:45:41	ga_s2am_ard_3-2-1_53JLG_2020-04-20_final
2020-05-30 10:45:46	ga_s2am_ard_3-2-1_53JLG_2020-05-30_final
2020-07-09 10:45:44	ga_s2am_ard_3-2-1_53JLG_2020-07-09_final
2020-08-18 10:45:46	ga_s2am_ard_3-2-1_53JLG_2020-08-18_final
2020-08-28 10:45:45	ga_s2am_ard_3-2-1_53JLG_2020-08-28_final
2020-09-07 10:45:44	ga_s2am_ard_3-2-1_53JLG_2020-09-07_final
2020-09-17 10:45:45	ga_s2am_ard_3-2-1_53JLG_2020-09-17_final
2020-09-27 10:45:46	ga_s2am_ard_3-2-1_53JLG_2020-09-27_final
2020-10-07 10:45:46	ga_s2am_ard_3-2-1_53JLG_2020-10-07_final
2020-10-17 10:45:46	ga_s2am_ard_3-2-1_53JLG_2020-10-17_final
2020-10-27 10:45:46	ga_s2am_ard_3-2-1_53JLG_2020-10-27_final
2020-11-06 10:45:45	ga_s2am_ard_3-2-1_53JLG_2020-11-06_final
2020-11-16 10:45:44	ga_s2am_ard_3-2-1_53JLG_2020-11-16_final
2020-11-26 10:45:41	ga_s2am_ard_3-2-1_53JLG_2020-11-26_final
2020-12-06 10:45:38	ga_s2am_ard_3-2-1_53JLG_2020-12-06_final
2020-12-16 10:45:38	ga_s2am_ard_3-2-1_53JLG_2020-12-16_final
2020-12-26 10:45:40	ga_s2am_ard_3-2-1_53JLG_2020-12-26_final
2021-01-05 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-01-05_final
2021-01-15 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-01-15_final
2021-01-25 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-01-25_final
2021-02-04 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-02-04_final
2021-02-14 10:45:39	ga_s2am_ard_3-2-1_53JLG_2021-02-14_final
2021-02-24 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-02-24_final
2021-03-06 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-03-06_final
2021-03-16 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-03-16_final
2021-03-26 10:45:38	ga_s2am_ard_3-2-1_53JLG_2021-03-26_final
2021-04-05 10:45:37	ga_s2am_ard_3-2-1_53JLG_2021-04-05_final
2021-04-15 10:45:34	ga_s2am_ard_3-2-1_53JLG_2021-04-15_final
2021-04-25 10:45:37	ga_s2am_ard_3-2-1_53JLG_2021-04-25_final
2021-05-05 10:45:39	ga_s2am_ard_3-2-1_53JLG_2021-05-05_final
2021-05-15 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-05-15_final
2021-05-25 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-05-25_final
2021-06-04 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-06-04_final
2021-06-14 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-06-14_final
2021-06-24 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-06-24_final
2021-07-04 10:45:43	ga_s2am_ard_3-2-1_53JLG_2021-07-04_final
2021-07-14 10:45:43	ga_s2am_ard_3-2-1_53JLG_2021-07-14_final
2021-07-24 10:45:44	ga_s2am_ard_3-2-1_53JLG_2021-07-24_final
2021-08-03 10:45:43	ga_s2am_ard_3-2-1_53JLG_2021-08-03_final
2021-08-13 10:45:43	ga_s2am_ard_3-2-1_53JLG_2021-08-13_final
2021-08-23 10:45:42	ga_s2am_ard_3-2-1_53JLG_2021-08-23_final
2021-09-02 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-09-02_final
2021-09-12 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-09-12_final
2021-09-22 10:45:43	ga_s2am_ard_3-2-1_53JLG_2021-09-22_final
2021-10-02 10:45:45	ga_s2am_ard_3-2-1_53JLG_2021-10-02_final
2021-10-12 10:45:46	ga_s2am_ard_3-2-1_53JLG_2021-10-12_final
2021-10-22 10:45:46	ga_s2am_ard_3-2-1_53JLG_2021-10-22_final
2021-11-01 10:45:45	ga_s2am_ard_3-2-1_53JLG_2021-11-01_final
2021-11-11 10:45:43	ga_s2am_ard_3-2-1_53JLG_2021-11-11_final
2021-11-21 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-11-21_final
2021-12-01 10:45:40	ga_s2am_ard_3-2-1_53JLG_2021-12-01_final
2021-12-11 10:45:39	ga_s2am_ard_3-2-1_53JLG_2021-12-11_final
2021-12-21 10:45:41	ga_s2am_ard_3-2-1_53JLG_2021-12-21_final
2021-12-31 10:45:42	ga_s2am_ard_3-2-1_53JLG_2021-12-31_final
2022-01-10 10:45:42	ga_s2am_ard_3-2-1_53JLG_2022-01-10_final
2022-01-20 10:45:40	ga_s2am_ard_3-2-1_53JLG_2022-01-20_final
2022-01-30 10:45:40	ga_s2am_ard_3-2-1_53JLG_2022-01-30_final
2022-02-09 10:45:39	ga_s2am_ard_3-2-1_53JLG_2022-02-09_final
2022-02-19 10:45:42	ga_s2am_ard_3-2-1_53JLG_2022-02-19_final
2022-03-01 10:45:44	ga_s2am_ard_3-2-1_53JLG_2022-03-01_final
2022-03-11 10:45:44	ga_s2am_ard_3-2-1_53JLG_2022-03-11_final
2022-03-21 10:45:44	ga_s2am_ard_3-2-1_53JLG_2022-03-21_final
2022-03-31 10:45:43	ga_s2am_ard_3-2-1_53JLG_2022-03-31_final
2022-04-10 10:45:42	ga_s2am_ard_3-2-1_53JLG_2022-04-10_final
2022-04-20 10:45:45	ga_s2am_ard_3-2-1_53JLG_2022-04-20_final
2022-04-30 10:45:45	ga_s2am_ard_3-2-1_53JLG_2022-04-30_final
2022-05-10 10:45:44	ga_s2am_ard_3-2-1_53JLG_2022-05-10_final
2022-05-20 10:45:46	ga_s2am_ard_3-2-1_53JLG_2022-05-20_final
2022-05-30 10:45:48	ga_s2am_ard_3-2-1_53JLG_2022-05-30_final
2022-06-09 10:45:49	ga_s2am_ard_3-2-1_53JLG_2022-06-09_final
2022-06-19 10:45:52	ga_s2am_ard_3-2-1_53JLG_2022-06-19_final
2022-06-29 10:45:53	ga_s2am_ard_3-2-1_53JLG_2022-06-29_final
2022-07-09 10:45:53	ga_s2am_ard_3-2-1_53JLG_2022-07-09_final
2022-07-19 10:45:52	ga_s2am_ard_3-2-1_53JLG_2022-07-19_final
2022-07-29 10:45:50	ga_s2am_ard_3-2-1_53JLG_2022-07-29_final
2022-08-08 10:45:52	ga_s2am_ard_3-2-1_53JLG_2022-08-08_final
2022-08-18 10:45:53	ga_s2am_ard_3-2-1_53JLG_2022-08-18_final
2022-08-28 10:45:53	ga_s2am_ard_3-2-1_53JLG_2022-08-28_final
2023-02-14 10:45:38	ga_s2am_ard_3-2-1_53JLG_2023-02-14_final.stac-item
2023-02-24 10:45:38	ga_s2am_ard_3-2-1_53JLG_2023-02-24_final.stac-item
2023-03-06 10:45:37	ga_s2am_ard_3-2-1_53JLG_2023-03-06_final.stac-item
2023-03-16 10:45:38	ga_s2am_ard_3-2-1_53JLG_2023-03-16_final.stac-item
2023-03-26 10:45:39	ga_s2am_ard_3-2-1_53JLG_2023-03-26_final.stac-item
2023-04-05 10:45:40	ga_s2am_ard_3-2-1_53JLG_2023-04-05_final.stac-item
2023-04-15 10:45:40	ga_s2am_ard_3-2-1_53JLG_2023-04-15_final.stac-item
2023-04-25 10:45:40	ga_s2am_ard_3-2-1_53JLG_2023-04-25_final.stac-item
2023-05-05 10:45:40	ga_s2am_ard_3-2-1_53JLG_2023-05-05_final.stac-item
2023-05-15 10:45:41	ga_s2am_ard_3-2-1_53JLG_2023-05-15_final.stac-item
2023-06-04 10:45:44	ga_s2am_ard_3-2-1_53JLG_2023-06-04_final.stac-item
2023-10-22 10:45:40	ga_s2am_ard_3-2-1_53JLG_2023-10-22_final.stac-item
2023-11-01 10:45:39	ga_s2am_ard_3-2-1_53JLG_2023-11-01_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