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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50JLM_2015-10-28_final.stac-item
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JLM_2015-11-14_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JLM_2015-12-04_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLM_2015-12-17_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JLM_2016-01-03_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLM_2016-01-16_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JLM_2016-03-03_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLM_2016-04-02_final.stac-item
2016-04-15 12:05:35	ga_s2am_ard_3-2-1_50JLM_2016-04-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JLM_2016-05-15_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLM_2016-05-22_final.stac-item
2016-06-04 12:02:54	ga_s2am_ard_3-2-1_50JLM_2016-06-04_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JLM_2016-06-11_final.stac-item
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50JLM_2016-06-21_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JLM_2016-07-01_final.stac-item
2016-07-11 11:56:11	ga_s2am_ard_3-2-1_50JLM_2016-07-11_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JLM_2016-07-14_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JLM_2016-07-21_final.stac-item
2016-07-31 11:56:12	ga_s2am_ard_3-2-1_50JLM_2016-07-31_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_50JLM_2016-08-03_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JLM_2016-08-10_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JLM_2016-08-20_final.stac-item
2016-08-23 12:05:55	ga_s2am_ard_3-2-1_50JLM_2016-08-23_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JLM_2016-08-30_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JLM_2016-09-09_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JLM_2016-09-19_final.stac-item
2016-09-29 11:56:03	ga_s2am_ard_3-2-1_50JLM_2016-09-29_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JLM_2016-10-09_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JLM_2016-10-19_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JLM_2016-10-22_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JLM_2016-10-29_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JLM_2016-11-01_final.stac-item
2016-11-08 11:56:06	ga_s2am_ard_3-2-1_50JLM_2016-11-08_final.stac-item
2016-11-08 11:56:13	ga_s2am_ard_3-2-1_50JLM_2016-11-08_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLM_2016-11-11_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JLM_2016-11-18_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JLM_2016-11-21_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JLM_2016-11-28_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50JLM_2016-12-08_final
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JLM_2016-12-11_final
2016-12-18 11:56:02	ga_s2am_ard_3-2-1_50JLM_2016-12-18_final
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JLM_2016-12-21_final
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50JLM_2016-12-28_final
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50JLM_2016-12-31_final
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50JLM_2017-01-07_final
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JLM_2017-01-30_final
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50JLM_2017-02-09_final
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JLM_2017-02-16_final
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JLM_2017-02-19_final
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JLM_2017-02-26_final
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50JLM_2017-03-08_final
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JLM_2017-03-11_final
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JLM_2017-03-18_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLM_2018-10-12_final
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLM_2018-10-19_final
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLM_2018-10-22_final
2018-11-01 12:05:28	ga_s2am_ard_3-2-1_50JLM_2018-11-01_final
2018-11-08 11:56:06	ga_s2am_ard_3-2-1_50JLM_2018-11-08_final
2018-11-18 11:56:05	ga_s2am_ard_3-2-1_50JLM_2018-11-18_final
2018-11-21 12:05:57	ga_s2am_ard_3-2-1_50JLM_2018-11-21_final
2018-11-28 11:56:02	ga_s2am_ard_3-2-1_50JLM_2018-11-28_final
2018-12-01 12:05:56	ga_s2am_ard_3-2-1_50JLM_2018-12-01_final
2018-12-08 11:56:03	ga_s2am_ard_3-2-1_50JLM_2018-12-08_final
2018-12-11 12:05:56	ga_s2am_ard_3-2-1_50JLM_2018-12-11_final
2018-12-18 11:56:02	ga_s2am_ard_3-2-1_50JLM_2018-12-18_final
2018-12-21 12:05:52	ga_s2am_ard_3-2-1_50JLM_2018-12-21_final
2018-12-21 12:05:56	ga_s2am_ard_3-2-1_50JLM_2018-12-21_final
2018-12-28 11:55:58	ga_s2am_ard_3-2-1_50JLM_2018-12-28_final
2018-12-28 11:56:05	ga_s2am_ard_3-2-1_50JLM_2018-12-28_final
2018-12-31 12:05:58	ga_s2am_ard_3-2-1_50JLM_2018-12-31_final
2019-01-07 11:56:06	ga_s2am_ard_3-2-1_50JLM_2019-01-07_final
2019-01-10 12:05:59	ga_s2am_ard_3-2-1_50JLM_2019-01-10_final
2019-01-17 11:56:07	ga_s2am_ard_3-2-1_50JLM_2019-01-17_final
2019-01-20 12:06:00	ga_s2am_ard_3-2-1_50JLM_2019-01-20_final
2019-01-27 11:56:08	ga_s2am_ard_3-2-1_50JLM_2019-01-27_final
2019-01-30 12:06:01	ga_s2am_ard_3-2-1_50JLM_2019-01-30_final
2019-02-06 11:56:05	ga_s2am_ard_3-2-1_50JLM_2019-02-06_final
2019-02-06 11:56:12	ga_s2am_ard_3-2-1_50JLM_2019-02-06_final
2019-02-09 12:06:01	ga_s2am_ard_3-2-1_50JLM_2019-02-09_final
2019-02-16 11:56:07	ga_s2am_ard_3-2-1_50JLM_2019-02-16_final
2019-02-19 12:06:00	ga_s2am_ard_3-2-1_50JLM_2019-02-19_final
2019-02-26 11:56:06	ga_s2am_ard_3-2-1_50JLM_2019-02-26_final
2019-03-01 12:05:59	ga_s2am_ard_3-2-1_50JLM_2019-03-01_final
2019-03-08 11:56:05	ga_s2am_ard_3-2-1_50JLM_2019-03-08_final
2019-03-11 12:05:59	ga_s2am_ard_3-2-1_50JLM_2019-03-11_final
2019-03-18 11:56:08	ga_s2am_ard_3-2-1_50JLM_2019-03-18_final
2019-03-21 12:06:02	ga_s2am_ard_3-2-1_50JLM_2019-03-21_final
2019-03-28 11:56:10	ga_s2am_ard_3-2-1_50JLM_2019-03-28_final
2019-03-31 12:06:04	ga_s2am_ard_3-2-1_50JLM_2019-03-31_final
2019-04-07 11:56:12	ga_s2am_ard_3-2-1_50JLM_2019-04-07_final
2019-04-10 12:06:06	ga_s2am_ard_3-2-1_50JLM_2019-04-10_final
2019-04-17 11:56:14	ga_s2am_ard_3-2-1_50JLM_2019-04-17_final
2019-04-20 12:06:07	ga_s2am_ard_3-2-1_50JLM_2019-04-20_final
2019-04-27 11:56:14	ga_s2am_ard_3-2-1_50JLM_2019-04-27_final
2019-04-30 12:06:08	ga_s2am_ard_3-2-1_50JLM_2019-04-30_final
2019-05-07 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-05-07_final
2019-05-10 12:06:08	ga_s2am_ard_3-2-1_50JLM_2019-05-10_final
2019-05-17 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-05-17_final
2019-05-20 12:06:08	ga_s2am_ard_3-2-1_50JLM_2019-05-20_final
2019-05-27 11:56:14	ga_s2am_ard_3-2-1_50JLM_2019-05-27_final

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