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
2016-09-18 10:43:03	ga_s2am_ard_3-2-1_53JMN_2016-09-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53JML_2016-10-18_final.stac-item
2017-03-27 10:43:01	ga_s2am_ard_3-2-1_53JML_2017-03-27_final.stac-item
2018-08-19 10:37:26	ga_s2am_ard_3-2-1_53JML_2018-08-19_final
2018-08-29 10:37:26	ga_s2am_ard_3-2-1_53JML_2018-08-29_final
2018-09-08 10:37:24	ga_s2am_ard_3-2-1_53JML_2018-09-08_final
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53JML_2018-09-18_final
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53JML_2018-09-28_final
2018-10-08 10:37:24	ga_s2am_ard_3-2-1_53JML_2018-10-08_final
2018-10-18 10:37:24	ga_s2am_ard_3-2-1_53JML_2018-10-18_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JML_2018-10-28_final
2018-11-07 10:44:34	ga_s2am_ard_3-2-1_53JML_2018-11-07_final
2018-11-17 10:44:33	ga_s2am_ard_3-2-1_53JML_2018-11-17_final
2018-11-27 10:44:31	ga_s2am_ard_3-2-1_53JML_2018-11-27_final
2018-12-07 10:44:30	ga_s2am_ard_3-2-1_53JML_2018-12-07_final
2018-12-17 10:44:30	ga_s2am_ard_3-2-1_53JML_2018-12-17_final
2018-12-27 10:44:32	ga_s2am_ard_3-2-1_53JML_2018-12-27_final
2019-01-06 10:44:34	ga_s2am_ard_3-2-1_53JML_2019-01-06_final
2019-01-16 10:44:35	ga_s2am_ard_3-2-1_53JML_2019-01-16_final
2019-01-26 10:44:35	ga_s2am_ard_3-2-1_53JML_2019-01-26_final
2019-02-05 10:44:36	ga_s2am_ard_3-2-1_53JML_2019-02-05_final
2019-02-15 10:44:35	ga_s2am_ard_3-2-1_53JML_2019-02-15_final
2019-02-25 10:44:34	ga_s2am_ard_3-2-1_53JML_2019-02-25_final
2019-03-07 10:44:33	ga_s2am_ard_3-2-1_53JML_2019-03-07_final
2019-03-17 10:44:36	ga_s2am_ard_3-2-1_53JML_2019-03-17_final
2019-03-27 10:44:38	ga_s2am_ard_3-2-1_53JML_2019-03-27_final
2019-04-06 10:44:40	ga_s2am_ard_3-2-1_53JML_2019-04-06_final
2019-04-16 10:44:41	ga_s2am_ard_3-2-1_53JML_2019-04-16_final
2019-04-26 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-04-26_final
2019-05-06 10:44:43	ga_s2am_ard_3-2-1_53JML_2019-05-06_final
2019-05-16 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-05-16_final
2019-05-26 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-05-26_final
2019-06-05 10:44:41	ga_s2am_ard_3-2-1_53JML_2019-06-05_final
2019-06-15 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-06-15_final
2019-06-25 10:44:43	ga_s2am_ard_3-2-1_53JML_2019-06-25_final
2019-07-05 10:44:44	ga_s2am_ard_3-2-1_53JML_2019-07-05_final
2019-07-15 10:44:44	ga_s2am_ard_3-2-1_53JML_2019-07-15_final
2019-07-25 10:44:44	ga_s2am_ard_3-2-1_53JML_2019-07-25_final
2019-08-04 10:44:43	ga_s2am_ard_3-2-1_53JML_2019-08-04_final
2019-08-14 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-08-14_final
2019-08-24 10:44:41	ga_s2am_ard_3-2-1_53JML_2019-08-24_final
2019-09-03 10:44:39	ga_s2am_ard_3-2-1_53JML_2019-09-03_final
2019-09-13 10:44:37	ga_s2am_ard_3-2-1_53JML_2019-09-13_final
2019-09-23 10:44:39	ga_s2am_ard_3-2-1_53JML_2019-09-23_final
2019-10-03 10:44:41	ga_s2am_ard_3-2-1_53JML_2019-10-03_final
2019-10-13 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-10-13_final
2019-10-23 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-10-23_final
2019-11-02 10:44:42	ga_s2am_ard_3-2-1_53JML_2019-11-02_final
2019-11-12 10:44:41	ga_s2am_ard_3-2-1_53JML_2019-11-12_final
2019-11-22 10:44:40	ga_s2am_ard_3-2-1_53JML_2019-11-22_final
2019-12-02 10:44:37	ga_s2am_ard_3-2-1_53JML_2019-12-02_final
2019-12-12 10:44:35	ga_s2am_ard_3-2-1_53JML_2019-12-12_final
2022-09-20 10:51:42	ga_s2am_ard_3-2-1_53LMC_2022-09-20_final.stac-item
2022-10-17 10:42:55	ga_s2am_ard_3-2-1_53KMT_2022-10-17_final.stac-item
2023-02-27 10:51:32	ga_s2am_ard_3-2-1_53LMC_2023-02-27_final.stac-item
2023-04-05 10:42:51	ga_s2am_ard_3-2-1_53KMT_2023-04-05_final.stac-item
2023-04-08 10:51:34	ga_s2am_ard_3-2-1_53LMC_2023-04-08_final.stac-item
2023-04-18 10:51:34	ga_s2am_ard_3-2-1_53LMC_2023-04-18_final.stac-item
2023-06-24 10:42:56	ga_s2am_ard_3-2-1_53KMT_2023-06-24_final.stac-item
2023-06-24 10:44:42	ga_s2am_ard_3-2-1_53JML_2023-06-24_final.stac-item
2023-07-04 10:42:57	ga_s2am_ard_3-2-1_53KMT_2023-07-04_final.stac-item
2023-07-04 10:44:44	ga_s2am_ard_3-2-1_53JML_2023-07-04_final.stac-item
2023-07-14 10:44:44	ga_s2am_ard_3-2-1_53JML_2023-07-14_final.stac-item
2023-07-24 10:44:43	ga_s2am_ard_3-2-1_53JML_2023-07-24_final.stac-item
2023-08-03 10:44:44	ga_s2am_ard_3-2-1_53JML_2023-08-03_final.stac-item
2023-08-13 10:44:44	ga_s2am_ard_3-2-1_53JML_2023-08-13_final.stac-item
2023-08-23 10:44:45	ga_s2am_ard_3-2-1_53JML_2023-08-23_final.stac-item
2023-09-02 10:44:44	ga_s2am_ard_3-2-1_53JML_2023-09-02_final.stac-item
2023-09-12 10:44:44	ga_s2am_ard_3-2-1_53JML_2023-09-12_final.stac-item
2023-09-22 10:42:52	ga_s2am_ard_3-2-1_53KMT_2023-09-22_final.stac-item
2023-09-22 10:44:40	ga_s2am_ard_3-2-1_53JML_2023-09-22_final.stac-item
2023-10-02 10:44:41	ga_s2am_ard_3-2-1_53JML_2023-10-02_final.stac-item
2023-10-12 10:44:37	ga_s2am_ard_3-2-1_53JML_2023-10-12_final.stac-item
2023-10-22 10:44:39	ga_s2am_ard_3-2-1_53JML_2023-10-22_final.stac-item
2023-11-01 10:44:38	ga_s2am_ard_3-2-1_53JML_2023-11-01_final.stac-item
2023-11-11 10:44:38	ga_s2am_ard_3-2-1_53JML_2023-11-11_final.stac-item
2023-11-21 10:44:35	ga_s2am_ard_3-2-1_53JML_2023-11-21_final.stac-item
2023-11-21 10:44:41	ga_s2am_ard_3-2-1_53JML_2023-11-21_final.stac-item
2023-12-01 10:44:30	ga_s2am_ard_3-2-1_53JML_2023-12-01_final.stac-item
2023-12-11 10:44:34	ga_s2am_ard_3-2-1_53JML_2023-12-11_final.stac-item
2023-12-21 10:44:35	ga_s2am_ard_3-2-1_53JML_2023-12-21_final.stac-item
2023-12-31 10:44:36	ga_s2am_ard_3-2-1_53JML_2023-12-31_final.stac-item
2024-01-10 10:44:34	ga_s2am_ard_3-2-1_53JML_2024-01-10_final.stac-item
2024-01-20 10:44:30	ga_s2am_ard_3-2-1_53JML_2024-01-20_final.stac-item
2024-01-30 10:44:34	ga_s2am_ard_3-2-1_53JML_2024-01-30_final.stac-item
2024-02-09 10:44:35	ga_s2am_ard_3-2-1_53JML_2024-02-09_final.stac-item
2024-02-19 10:42:51	ga_s2am_ard_3-2-1_53KMT_2024-02-19_final.stac-item
2024-02-19 10:44:37	ga_s2am_ard_3-2-1_53JML_2024-02-19_final.stac-item
2024-02-29 10:44:39	ga_s2am_ard_3-2-1_53JML_2024-02-29_final.stac-item
2024-03-10 10:44:39	ga_s2am_ard_3-2-1_53JML_2024-03-10_final.stac-item
2024-03-13 10:51:35	ga_s2am_ard_3-2-1_53LMC_2024-03-13_final.stac-item
2024-03-20 10:44:40	ga_s2am_ard_3-2-1_53JML_2024-03-20_final.stac-item
2024-03-30 10:44:38	ga_s2am_ard_3-2-1_53JML_2024-03-30_final.stac-item
2024-04-09 10:44:38	ga_s2am_ard_3-2-1_53JML_2024-04-09_final.stac-item
2024-04-19 10:42:54	ga_s2am_ard_3-2-1_53KMT_2024-04-19_final.stac-item
2024-04-19 10:44:42	ga_s2am_ard_3-2-1_53JML_2024-04-19_final.stac-item
2024-04-29 10:44:41	ga_s2am_ard_3-2-1_53JML_2024-04-29_final.stac-item
2024-05-09 10:44:41	ga_s2am_ard_3-2-1_53JML_2024-05-09_final.stac-item
2024-05-19 10:42:51	ga_s2am_ard_3-2-1_53KMT_2024-05-19_final.stac-item
2024-05-19 10:44:40	ga_s2am_ard_3-2-1_53JML_2024-05-19_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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