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
2018-07-19 09:32:41	ga_s2am_ard_3-2-1_56JLP_2018-07-19_final
2018-07-29 09:32:41	ga_s2am_ard_3-2-1_56JLP_2018-07-29_final
2018-08-08 09:32:40	ga_s2am_ard_3-2-1_56JLP_2018-08-08_final
2018-08-28 09:32:38	ga_s2am_ard_3-2-1_56JLP_2018-08-28_final
2018-09-07 09:32:37	ga_s2am_ard_3-2-1_56JLP_2018-09-07_final
2018-09-17 09:32:36	ga_s2am_ard_3-2-1_56JLP_2018-09-17_final
2018-09-27 09:32:36	ga_s2am_ard_3-2-1_56JLP_2018-09-27_final
2018-10-07 09:32:37	ga_s2am_ard_3-2-1_56JLP_2018-10-07_final
2018-10-17 09:32:37	ga_s2am_ard_3-2-1_56JLP_2018-10-17_final
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_56JLP_2018-10-27_final
2018-11-06 09:32:36	ga_s2am_ard_3-2-1_56JLP_2018-11-06_final
2018-11-16 09:34:35	ga_s2am_ard_3-2-1_56JLP_2018-11-16_final
2018-11-26 09:34:32	ga_s2am_ard_3-2-1_56JLP_2018-11-26_final
2018-12-06 09:34:32	ga_s2am_ard_3-2-1_56JLP_2018-12-06_final
2018-12-16 09:34:32	ga_s2am_ard_3-2-1_56JLP_2018-12-16_final
2018-12-26 09:34:33	ga_s2am_ard_3-2-1_56JLP_2018-12-26_final
2019-01-05 09:34:35	ga_s2am_ard_3-2-1_56JLP_2019-01-05_final
2019-01-15 09:34:36	ga_s2am_ard_3-2-1_56JLP_2019-01-15_final
2019-01-25 09:34:37	ga_s2am_ard_3-2-1_56JLP_2019-01-25_final
2019-02-14 09:34:37	ga_s2am_ard_3-2-1_56JLP_2019-02-14_final
2019-03-06 09:34:35	ga_s2am_ard_3-2-1_56JLP_2019-03-06_final
2019-03-16 09:34:37	ga_s2am_ard_3-2-1_56JLP_2019-03-16_final
2019-04-05 09:34:41	ga_s2am_ard_3-2-1_56JLP_2019-04-05_final
2019-04-15 09:34:43	ga_s2am_ard_3-2-1_56JLP_2019-04-15_final
2019-04-25 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-04-25_final
2019-05-05 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-05-05_final
2019-05-15 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-05-15_final
2019-05-25 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-05-25_final
2019-06-04 09:34:43	ga_s2am_ard_3-2-1_56JLP_2019-06-04_final
2019-06-14 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-06-14_final
2019-06-24 09:34:45	ga_s2am_ard_3-2-1_56JLP_2019-06-24_final
2019-07-04 09:34:45	ga_s2am_ard_3-2-1_56JLP_2019-07-04_final
2019-07-14 09:34:46	ga_s2am_ard_3-2-1_56JLP_2019-07-14_final
2019-07-24 09:34:45	ga_s2am_ard_3-2-1_56JLP_2019-07-24_final
2019-08-03 09:34:45	ga_s2am_ard_3-2-1_56JLP_2019-08-03_final
2019-08-13 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-08-13_final
2019-08-23 09:34:43	ga_s2am_ard_3-2-1_56JLP_2019-08-23_final
2019-09-02 09:34:41	ga_s2am_ard_3-2-1_56JLP_2019-09-02_final
2019-09-12 09:34:39	ga_s2am_ard_3-2-1_56JLP_2019-09-12_final
2019-09-22 09:34:41	ga_s2am_ard_3-2-1_56JLP_2019-09-22_final
2019-10-12 09:34:43	ga_s2am_ard_3-2-1_56JLP_2019-10-12_final
2019-10-22 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-10-22_final
2019-11-01 09:34:44	ga_s2am_ard_3-2-1_56JLP_2019-11-01_final
2019-11-11 09:34:43	ga_s2am_ard_3-2-1_56JLP_2019-11-11_final
2019-11-21 09:34:41	ga_s2am_ard_3-2-1_56JLP_2019-11-21_final
2021-04-24 09:34:37	ga_s2am_ard_3-2-1_56JLP_2021-04-24_final
2021-05-04 09:34:39	ga_s2am_ard_3-2-1_56JLP_2021-05-04_final
2021-05-14 09:34:40	ga_s2am_ard_3-2-1_56JLP_2021-05-14_final
2021-05-24 09:34:41	ga_s2am_ard_3-2-1_56JLP_2021-05-24_final
2021-06-03 09:34:36	ga_s2am_ard_3-2-1_56JLP_2021-06-03_final
2021-06-03 09:34:43	ga_s2am_ard_3-2-1_56JLP_2021-06-03_final
2021-06-13 09:34:41	ga_s2am_ard_3-2-1_56JLP_2021-06-13_final
2021-06-23 09:34:41	ga_s2am_ard_3-2-1_56JLP_2021-06-23_final
2021-07-03 09:34:43	ga_s2am_ard_3-2-1_56JLP_2021-07-03_final
2021-07-13 09:34:44	ga_s2am_ard_3-2-1_56JLP_2021-07-13_final
2021-07-23 09:34:44	ga_s2am_ard_3-2-1_56JLP_2021-07-23_final
2021-08-02 09:34:44	ga_s2am_ard_3-2-1_56JLP_2021-08-02_final
2021-08-12 09:34:43	ga_s2am_ard_3-2-1_56JLP_2021-08-12_final
2021-08-22 09:34:43	ga_s2am_ard_3-2-1_56JLP_2021-08-22_final
2021-09-01 09:34:42	ga_s2am_ard_3-2-1_56JLP_2021-09-01_final
2021-09-11 09:34:41	ga_s2am_ard_3-2-1_56JLP_2021-09-11_final
2021-09-21 09:34:43	ga_s2am_ard_3-2-1_56JLP_2021-09-21_final
2021-10-01 09:34:45	ga_s2am_ard_3-2-1_56JLP_2021-10-01_final
2021-10-11 09:34:46	ga_s2am_ard_3-2-1_56JLP_2021-10-11_final
2021-10-21 09:34:46	ga_s2am_ard_3-2-1_56JLP_2021-10-21_final
2021-10-31 09:34:45	ga_s2am_ard_3-2-1_56JLP_2021-10-31_final
2021-11-20 09:34:41	ga_s2am_ard_3-2-1_56JLP_2021-11-20_final
2021-11-30 09:34:40	ga_s2am_ard_3-2-1_56JLP_2021-11-30_final
2021-12-10 09:34:39	ga_s2am_ard_3-2-1_56JLP_2021-12-10_final
2021-12-20 09:34:41	ga_s2am_ard_3-2-1_56JLP_2021-12-20_final
2021-12-30 09:34:42	ga_s2am_ard_3-2-1_56JLP_2021-12-30_final
2022-01-09 09:34:42	ga_s2am_ard_3-2-1_56JLP_2022-01-09_final
2022-01-29 09:34:41	ga_s2am_ard_3-2-1_56JLP_2022-01-29_final
2022-02-08 09:34:40	ga_s2am_ard_3-2-1_56JLP_2022-02-08_final
2022-02-18 09:34:42	ga_s2am_ard_3-2-1_56JLP_2022-02-18_final
2022-02-28 09:34:44	ga_s2am_ard_3-2-1_56JLP_2022-02-28_final
2022-03-10 09:34:45	ga_s2am_ard_3-2-1_56JLP_2022-03-10_final
2022-03-20 09:34:44	ga_s2am_ard_3-2-1_56JLP_2022-03-20_final
2022-03-30 09:34:43	ga_s2am_ard_3-2-1_56JLP_2022-03-30_final
2022-04-09 09:34:42	ga_s2am_ard_3-2-1_56JLP_2022-04-09_final
2022-04-19 09:34:45	ga_s2am_ard_3-2-1_56JLP_2022-04-19_final
2022-04-29 09:34:46	ga_s2am_ard_3-2-1_56JLP_2022-04-29_final
2022-05-09 09:34:45	ga_s2am_ard_3-2-1_56JLP_2022-05-09_final
2022-05-19 09:34:46	ga_s2am_ard_3-2-1_56JLP_2022-05-19_final
2022-05-29 09:34:48	ga_s2am_ard_3-2-1_56JLP_2022-05-29_final
2022-06-08 09:34:49	ga_s2am_ard_3-2-1_56JLP_2022-06-08_final
2022-06-18 09:34:52	ga_s2am_ard_3-2-1_56JLP_2022-06-18_final
2022-06-28 09:34:53	ga_s2am_ard_3-2-1_56JLP_2022-06-28_final
2022-07-08 09:34:53	ga_s2am_ard_3-2-1_56JLP_2022-07-08_final
2022-07-18 09:34:52	ga_s2am_ard_3-2-1_56JLP_2022-07-18_final
2022-07-28 09:34:50	ga_s2am_ard_3-2-1_56JLP_2022-07-28_final
2022-08-07 09:34:52	ga_s2am_ard_3-2-1_56JLP_2022-08-07_final
2022-08-17 09:34:53	ga_s2am_ard_3-2-1_56JLP_2022-08-17_final
2022-08-27 09:34:53	ga_s2am_ard_3-2-1_56JLP_2022-08-27_final
2022-09-06 09:34:50	ga_s2am_ard_3-2-1_56JLP_2022-09-06_final.stac-item
2022-09-16 09:34:50	ga_s2am_ard_3-2-1_56JLP_2022-09-16_final.stac-item
2022-09-26 09:34:48	ga_s2am_ard_3-2-1_56JLP_2022-09-26_final.stac-item
2022-10-06 09:34:47	ga_s2am_ard_3-2-1_56JLP_2022-10-06_final.stac-item
2022-10-16 09:34:44	ga_s2am_ard_3-2-1_56JLP_2022-10-16_final.stac-item
2022-10-26 09:34:43	ga_s2am_ard_3-2-1_56JLP_2022-10-26_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