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
2015-08-25 10:45:29	ga_s2am_ard_3-2-1_52JGM_2015-08-25_final.stac-item
2016-07-03 10:55:16	ga_s2am_ard_3-2-1_53JKG_2016-07-03_final.stac-item
2016-07-23 10:55:18	ga_s2am_ard_3-2-1_53JKG_2016-07-23_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_52JGM_2016-10-18_final.stac-item
2017-03-20 10:53:07	ga_s2am_ard_3-2-1_52JGM_2017-03-20_final
2017-04-09 10:53:13	ga_s2am_ard_3-2-1_52JGM_2017-04-09_final
2017-04-16 10:43:06	ga_s2am_ard_3-2-1_52JGM_2017-04-16_final
2017-04-29 10:53:17	ga_s2am_ard_3-2-1_52JGM_2017-04-29_final
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_52JGM_2017-05-06_final
2017-05-26 10:43:09	ga_s2am_ard_3-2-1_52JGM_2017-05-26_final
2017-06-08 10:53:16	ga_s2am_ard_3-2-1_52JGM_2017-06-08_final
2017-06-28 10:53:13	ga_s2am_ard_3-2-1_52JGM_2017-06-28_final
2017-07-18 10:53:16	ga_s2am_ard_3-2-1_52JGM_2017-07-18_final
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_52JGM_2017-07-25_final
2017-08-07 10:53:16	ga_s2am_ard_3-2-1_52JGM_2017-08-07_final
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_52JGM_2017-08-14_final
2017-08-27 10:53:15	ga_s2am_ard_3-2-1_52JGM_2017-08-27_final
2017-09-03 10:43:06	ga_s2am_ard_3-2-1_52JGM_2017-09-03_final
2017-09-16 10:53:12	ga_s2am_ard_3-2-1_52JGM_2017-09-16_final
2017-09-23 10:43:02	ga_s2am_ard_3-2-1_52JGM_2017-09-23_final
2017-10-06 10:53:13	ga_s2am_ard_3-2-1_52JGM_2017-10-06_final
2017-10-13 10:43:05	ga_s2am_ard_3-2-1_52JGM_2017-10-13_final
2022-09-10 10:55:53	ga_s2am_ard_3-2-1_52JGM_2022-09-10_final.stac-item
2022-09-17 10:45:56	ga_s2am_ard_3-2-1_52JGM_2022-09-17_final.stac-item
2022-09-20 10:55:50	ga_s2am_ard_3-2-1_52JGM_2022-09-20_final.stac-item
2022-09-27 10:45:54	ga_s2am_ard_3-2-1_52JGM_2022-09-27_final.stac-item
2022-09-30 10:55:49	ga_s2am_ard_3-2-1_52JGM_2022-09-30_final.stac-item
2022-10-10 10:55:48	ga_s2am_ard_3-2-1_52JGM_2022-10-10_final.stac-item
2022-10-20 10:55:44	ga_s2am_ard_3-2-1_52JGM_2022-10-20_final.stac-item
2022-11-16 10:45:49	ga_s2am_ard_3-2-1_52JGM_2022-11-16_final.stac-item
2022-12-16 10:45:46	ga_s2am_ard_3-2-1_52JGM_2022-12-16_final.stac-item
2022-12-26 10:45:45	ga_s2am_ard_3-2-1_52JGM_2022-12-26_final.stac-item
2022-12-29 10:55:41	ga_s2am_ard_3-2-1_52JGM_2022-12-29_final.stac-item
2023-01-05 10:45:37	ga_s2am_ard_3-2-1_53JKG_2023-01-05_final.stac-item
2023-01-05 10:45:39	ga_s2am_ard_3-2-1_52JGM_2023-01-05_final.stac-item
2023-01-08 10:55:41	ga_s2am_ard_3-2-1_52JGM_2023-01-08_final.stac-item
2023-01-15 10:45:44	ga_s2am_ard_3-2-1_52JGM_2023-01-15_final.stac-item
2023-01-18 10:55:34	ga_s2am_ard_3-2-1_53JKG_2023-01-18_final.stac-item
2023-01-18 10:55:37	ga_s2am_ard_3-2-1_52JGM_2023-01-18_final.stac-item
2023-01-25 10:45:44	ga_s2am_ard_3-2-1_52JGM_2023-01-25_final.stac-item
2023-01-28 10:55:40	ga_s2am_ard_3-2-1_52JGM_2023-01-28_final.stac-item
2023-01-28 10:55:58	ga_s2am_ard_3-2-1_53JKF_2023-01-28_final.stac-item
2023-01-28 10:55:59	ga_s2am_ard_3-2-1_52JGL_2023-01-28_final.stac-item
2023-02-04 10:45:46	ga_s2am_ard_3-2-1_52JGM_2023-02-04_final.stac-item
2023-02-07 10:55:41	ga_s2am_ard_3-2-1_52JGM_2023-02-07_final.stac-item
2023-02-14 10:45:45	ga_s2am_ard_3-2-1_52JGM_2023-02-14_final.stac-item
2023-02-17 10:55:38	ga_s2am_ard_3-2-1_52JGM_2023-02-17_final.stac-item
2023-02-24 10:45:45	ga_s2am_ard_3-2-1_52JGM_2023-02-24_final.stac-item
2023-02-27 10:55:37	ga_s2am_ard_3-2-1_53JKG_2023-02-27_final.stac-item
2023-02-27 10:55:39	ga_s2am_ard_3-2-1_52JGM_2023-02-27_final.stac-item
2023-03-06 10:45:43	ga_s2am_ard_3-2-1_52JGM_2023-03-06_final.stac-item
2023-03-09 10:55:34	ga_s2am_ard_3-2-1_53JKG_2023-03-09_final.stac-item
2023-03-09 10:55:37	ga_s2am_ard_3-2-1_52JGM_2023-03-09_final.stac-item
2023-03-16 10:45:44	ga_s2am_ard_3-2-1_52JGM_2023-03-16_final.stac-item
2023-03-19 10:55:37	ga_s2am_ard_3-2-1_53JKG_2023-03-19_final.stac-item
2023-03-19 10:55:40	ga_s2am_ard_3-2-1_52JGM_2023-03-19_final.stac-item
2023-03-26 10:45:45	ga_s2am_ard_3-2-1_52JGM_2023-03-26_final.stac-item
2023-03-29 10:55:40	ga_s2am_ard_3-2-1_52JGM_2023-03-29_final.stac-item
2023-04-05 10:45:47	ga_s2am_ard_3-2-1_52JGM_2023-04-05_final.stac-item
2023-04-08 10:55:39	ga_s2am_ard_3-2-1_53JKG_2023-04-08_final.stac-item
2023-04-08 10:55:42	ga_s2am_ard_3-2-1_52JGM_2023-04-08_final.stac-item
2023-04-15 10:45:47	ga_s2am_ard_3-2-1_52JGM_2023-04-15_final.stac-item
2023-04-18 10:55:41	ga_s2am_ard_3-2-1_52JGM_2023-04-18_final.stac-item
2023-04-25 10:45:47	ga_s2am_ard_3-2-1_52JGM_2023-04-25_final.stac-item
2023-04-28 10:55:42	ga_s2am_ard_3-2-1_52JGM_2023-04-28_final.stac-item
2023-05-05 10:45:47	ga_s2am_ard_3-2-1_52JGM_2023-05-05_final.stac-item
2023-05-08 10:55:42	ga_s2am_ard_3-2-1_52JGM_2023-05-08_final.stac-item
2023-05-15 10:45:47	ga_s2am_ard_3-2-1_52JGM_2023-05-15_final.stac-item
2023-05-18 10:55:41	ga_s2am_ard_3-2-1_53JKG_2023-05-18_final.stac-item
2023-05-18 10:55:44	ga_s2am_ard_3-2-1_52JGM_2023-05-18_final.stac-item
2023-05-25 10:45:50	ga_s2am_ard_3-2-1_52JGM_2023-05-25_final.stac-item
2023-05-28 10:55:43	ga_s2am_ard_3-2-1_53JKG_2023-05-28_final.stac-item
2023-05-28 10:55:46	ga_s2am_ard_3-2-1_52JGM_2023-05-28_final.stac-item
2023-06-04 10:45:51	ga_s2am_ard_3-2-1_52JGM_2023-06-04_final.stac-item
2023-06-07 10:55:45	ga_s2am_ard_3-2-1_52JGM_2023-06-07_final.stac-item
2023-06-14 10:45:51	ga_s2am_ard_3-2-1_52JGM_2023-06-14_final.stac-item
2023-06-17 10:55:41	ga_s2am_ard_3-2-1_52JGM_2023-06-17_final.stac-item
2023-06-17 10:55:46	ga_s2am_ard_3-2-1_53JKG_2023-06-17_final.stac-item
2023-06-24 10:45:50	ga_s2am_ard_3-2-1_52JGM_2023-06-24_final.stac-item
2023-06-27 10:55:46	ga_s2am_ard_3-2-1_52JGM_2023-06-27_final.stac-item
2023-07-04 10:45:52	ga_s2am_ard_3-2-1_52JGM_2023-07-04_final.stac-item
2023-07-07 10:55:44	ga_s2am_ard_3-2-1_53JKG_2023-07-07_final.stac-item
2023-07-07 10:55:47	ga_s2am_ard_3-2-1_52JGM_2023-07-07_final.stac-item
2023-07-14 10:45:52	ga_s2am_ard_3-2-1_52JGM_2023-07-14_final.stac-item
2023-07-17 10:55:44	ga_s2am_ard_3-2-1_53JKG_2023-07-17_final.stac-item
2023-07-17 10:55:47	ga_s2am_ard_3-2-1_52JGM_2023-07-17_final.stac-item
2023-07-24 10:45:52	ga_s2am_ard_3-2-1_52JGM_2023-07-24_final.stac-item
2023-07-27 10:55:47	ga_s2am_ard_3-2-1_52JGM_2023-07-27_final.stac-item
2023-08-06 10:55:44	ga_s2am_ard_3-2-1_53JKG_2023-08-06_final.stac-item
2023-08-16 10:55:45	ga_s2am_ard_3-2-1_53JKG_2023-08-16_final.stac-item
2023-09-15 10:55:43	ga_s2am_ard_3-2-1_53JKG_2023-09-15_final.stac-item
2023-10-25 10:55:39	ga_s2am_ard_3-2-1_53JKG_2023-10-25_final.stac-item
2023-11-04 10:55:38	ga_s2am_ard_3-2-1_53JKG_2023-11-04_final.stac-item
2023-11-14 10:55:56	ga_s2am_ard_3-2-1_53JKF_2023-11-14_final.stac-item
2023-11-14 10:55:57	ga_s2am_ard_3-2-1_52JGL_2023-11-14_final.stac-item
2023-11-24 10:55:34	ga_s2am_ard_3-2-1_53JKG_2023-11-24_final.stac-item
2023-12-01 10:45:38	ga_s2am_ard_3-2-1_52JGM_2023-12-01_final.stac-item
2023-12-04 10:55:32	ga_s2am_ard_3-2-1_53JKG_2023-12-04_final.stac-item
2023-12-11 10:45:36	ga_s2am_ard_3-2-1_53JKG_2023-12-11_final.stac-item
2023-12-14 10:55:35	ga_s2am_ard_3-2-1_53JKG_2023-12-14_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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