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
2021-05-26 10:15:41	ga_s2am_ard_3-2-1_54JWL_2021-05-26_final
2021-06-05 10:15:41	ga_s2am_ard_3-2-1_54JWL_2021-06-05_final
2021-06-12 10:05:45	ga_s2am_ard_3-2-1_54JWL_2021-06-12_final
2021-06-25 10:15:42	ga_s2am_ard_3-2-1_54JWL_2021-06-25_final
2021-07-02 10:05:47	ga_s2am_ard_3-2-1_54JWL_2021-07-02_final
2021-07-05 10:15:43	ga_s2am_ard_3-2-1_54JWL_2021-07-05_final
2021-07-12 10:05:48	ga_s2am_ard_3-2-1_54JWL_2021-07-12_final
2021-07-15 10:15:44	ga_s2am_ard_3-2-1_54JWL_2021-07-15_final
2021-07-25 10:15:44	ga_s2am_ard_3-2-1_54JWL_2021-07-25_final
2021-08-01 10:05:48	ga_s2am_ard_3-2-1_54JWL_2021-08-01_final
2021-08-04 10:15:44	ga_s2am_ard_3-2-1_54JWL_2021-08-04_final
2021-08-14 10:15:43	ga_s2am_ard_3-2-1_54JWL_2021-08-14_final
2021-08-21 10:05:47	ga_s2am_ard_3-2-1_54JWL_2021-08-21_final
2021-08-24 10:15:43	ga_s2am_ard_3-2-1_54JWL_2021-08-24_final
2021-09-13 10:15:41	ga_s2am_ard_3-2-1_54JWL_2021-09-13_final
2021-09-23 10:15:44	ga_s2am_ard_3-2-1_54JWL_2021-09-23_final
2021-09-30 10:05:49	ga_s2am_ard_3-2-1_54JWL_2021-09-30_final
2021-10-03 10:15:45	ga_s2am_ard_3-2-1_54JWL_2021-10-03_final
2021-10-10 10:05:50	ga_s2am_ard_3-2-1_54JWL_2021-10-10_final
2021-10-13 10:15:46	ga_s2am_ard_3-2-1_54JWL_2021-10-13_final
2021-10-20 10:05:50	ga_s2am_ard_3-2-1_54JWL_2021-10-20_final
2021-10-23 10:15:46	ga_s2am_ard_3-2-1_54JWL_2021-10-23_final
2021-10-30 10:05:49	ga_s2am_ard_3-2-1_54JWL_2021-10-30_final
2021-11-02 10:15:45	ga_s2am_ard_3-2-1_54JWL_2021-11-02_final
2021-11-29 10:05:45	ga_s2am_ard_3-2-1_54JWL_2021-11-29_final
2021-12-02 10:15:40	ga_s2am_ard_3-2-1_54JWL_2021-12-02_final
2021-12-12 10:15:40	ga_s2am_ard_3-2-1_54JWL_2021-12-12_final
2021-12-19 10:05:45	ga_s2am_ard_3-2-1_54JWL_2021-12-19_final
2021-12-22 10:15:42	ga_s2am_ard_3-2-1_54JWL_2021-12-22_final
2021-12-29 10:05:46	ga_s2am_ard_3-2-1_54JWL_2021-12-29_final
2022-01-01 10:15:42	ga_s2am_ard_3-2-1_54JWL_2022-01-01_final
2022-01-08 10:05:46	ga_s2am_ard_3-2-1_54JWL_2022-01-08_final
2022-01-11 10:15:42	ga_s2am_ard_3-2-1_54JWL_2022-01-11_final
2022-01-21 10:15:41	ga_s2am_ard_3-2-1_54JWL_2022-01-21_final
2022-01-28 10:05:45	ga_s2am_ard_3-2-1_54JWL_2022-01-28_final
2022-01-31 10:15:41	ga_s2am_ard_3-2-1_54JWL_2022-01-31_final
2022-02-07 10:05:44	ga_s2am_ard_3-2-1_54JWL_2022-02-07_final
2022-02-10 10:15:40	ga_s2am_ard_3-2-1_54JWL_2022-02-10_final
2022-02-17 10:05:46	ga_s2am_ard_3-2-1_54JWL_2022-02-17_final
2022-02-20 10:15:42	ga_s2am_ard_3-2-1_54JWL_2022-02-20_final
2022-02-27 10:05:48	ga_s2am_ard_3-2-1_54JWL_2022-02-27_final
2022-03-02 10:15:44	ga_s2am_ard_3-2-1_54JWL_2022-03-02_final
2022-03-09 10:05:49	ga_s2am_ard_3-2-1_54JWL_2022-03-09_final
2022-03-12 10:15:45	ga_s2am_ard_3-2-1_54JWL_2022-03-12_final
2022-03-19 10:05:48	ga_s2am_ard_3-2-1_54JWL_2022-03-19_final
2022-03-22 10:15:44	ga_s2am_ard_3-2-1_54JWL_2022-03-22_final
2022-03-29 10:05:47	ga_s2am_ard_3-2-1_54JWL_2022-03-29_final
2022-04-01 10:15:43	ga_s2am_ard_3-2-1_54JWL_2022-04-01_final
2022-04-08 10:05:45	ga_s2am_ard_3-2-1_54JWL_2022-04-08_final
2022-04-11 10:15:42	ga_s2am_ard_3-2-1_54JWL_2022-04-11_final
2022-04-18 10:05:49	ga_s2am_ard_3-2-1_54JWL_2022-04-18_final
2022-04-21 10:15:45	ga_s2am_ard_3-2-1_54JWL_2022-04-21_final
2022-04-28 10:05:50	ga_s2am_ard_3-2-1_54JWL_2022-04-28_final
2022-05-01 10:15:46	ga_s2am_ard_3-2-1_54JWL_2022-05-01_final
2022-05-08 10:05:49	ga_s2am_ard_3-2-1_54JWL_2022-05-08_final
2022-05-11 10:15:44	ga_s2am_ard_3-2-1_54JWL_2022-05-11_final
2022-05-18 10:05:50	ga_s2am_ard_3-2-1_54JWL_2022-05-18_final
2022-05-21 10:15:47	ga_s2am_ard_3-2-1_54JWL_2022-05-21_final
2022-05-28 10:05:52	ga_s2am_ard_3-2-1_54JWL_2022-05-28_final
2022-05-31 10:15:48	ga_s2am_ard_3-2-1_54JWL_2022-05-31_final
2022-06-07 10:05:53	ga_s2am_ard_3-2-1_54JWL_2022-06-07_final
2022-06-10 10:15:50	ga_s2am_ard_3-2-1_54JWL_2022-06-10_final
2022-06-17 10:05:56	ga_s2am_ard_3-2-1_54JWL_2022-06-17_final
2022-06-20 10:15:52	ga_s2am_ard_3-2-1_54JWL_2022-06-20_final
2022-06-27 10:05:57	ga_s2am_ard_3-2-1_54JWL_2022-06-27_final
2022-06-30 10:15:54	ga_s2am_ard_3-2-1_54JWL_2022-06-30_final
2022-07-07 10:05:58	ga_s2am_ard_3-2-1_54JWL_2022-07-07_final
2022-07-10 10:15:54	ga_s2am_ard_3-2-1_54JWL_2022-07-10_final
2022-07-17 10:05:49	ga_s2am_ard_3-2-1_54JWL_2022-07-17_final
2022-07-17 10:05:57	ga_s2am_ard_3-2-1_54JWL_2022-07-17_final
2022-07-20 10:15:52	ga_s2am_ard_3-2-1_54JWL_2022-07-20_final
2022-07-27 10:05:55	ga_s2am_ard_3-2-1_54JWL_2022-07-27_final
2022-07-30 10:15:50	ga_s2am_ard_3-2-1_54JWL_2022-07-30_final
2023-02-05 10:15:39	ga_s2am_ard_3-2-1_54JWL_2023-02-05_final.stac-item
2023-02-12 10:05:43	ga_s2am_ard_3-2-1_54JWL_2023-02-12_final.stac-item
2023-02-15 10:15:38	ga_s2am_ard_3-2-1_54JWL_2023-02-15_final.stac-item
2023-02-22 10:05:42	ga_s2am_ard_3-2-1_54JWL_2023-02-22_final.stac-item
2023-02-25 10:15:38	ga_s2am_ard_3-2-1_54JWL_2023-02-25_final.stac-item
2023-03-04 10:05:41	ga_s2am_ard_3-2-1_54JWL_2023-03-04_final.stac-item
2023-03-07 10:15:37	ga_s2am_ard_3-2-1_54JWL_2023-03-07_final.stac-item
2023-03-14 10:05:41	ga_s2am_ard_3-2-1_54JWL_2023-03-14_final.stac-item
2023-03-17 10:15:38	ga_s2am_ard_3-2-1_54JWL_2023-03-17_final.stac-item
2023-03-24 10:05:43	ga_s2am_ard_3-2-1_54JWL_2023-03-24_final.stac-item
2023-03-27 10:15:39	ga_s2am_ard_3-2-1_54JWL_2023-03-27_final.stac-item
2023-04-03 10:05:44	ga_s2am_ard_3-2-1_54JWL_2023-04-03_final.stac-item
2023-04-06 10:15:40	ga_s2am_ard_3-2-1_54JWL_2023-04-06_final.stac-item
2023-04-13 10:05:45	ga_s2am_ard_3-2-1_54JWL_2023-04-13_final.stac-item
2023-04-16 10:15:40	ga_s2am_ard_3-2-1_54JWL_2023-04-16_final.stac-item
2023-04-23 10:05:40	ga_s2am_ard_3-2-1_54JWL_2023-04-23_final.stac-item
2023-04-23 10:05:46	ga_s2am_ard_3-2-1_54JWL_2023-04-23_final.stac-item
2023-04-26 10:15:33	ga_s2am_ard_3-2-1_54JWL_2023-04-26_final.stac-item
2023-04-26 10:15:40	ga_s2am_ard_3-2-1_54JWL_2023-04-26_final.stac-item
2023-05-06 10:15:41	ga_s2am_ard_3-2-1_54JWL_2023-05-06_final.stac-item
2023-05-13 10:05:44	ga_s2am_ard_3-2-1_54JWL_2023-05-13_final.stac-item
2023-05-16 10:15:42	ga_s2am_ard_3-2-1_54JWL_2023-05-16_final.stac-item
2023-10-13 10:15:38	ga_s2am_ard_3-2-1_54JWL_2023-10-13_final.stac-item
2023-10-20 10:05:45	ga_s2am_ard_3-2-1_54JWL_2023-10-20_final.stac-item
2023-10-23 10:15:41	ga_s2am_ard_3-2-1_54JWL_2023-10-23_final.stac-item
2023-10-30 10:05:44	ga_s2am_ard_3-2-1_54JWL_2023-10-30_final.stac-item
2023-11-02 10:15:39	ga_s2am_ard_3-2-1_54JWL_2023-11-02_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