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
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_50JQM_2016-08-04_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_50JQM_2017-04-21_final
2017-06-30 11:36:02	ga_s2am_ard_3-2-1_50JQM_2017-06-30_final
2017-08-09 11:36:05	ga_s2am_ard_3-2-1_50JQM_2017-08-09_final
2017-08-29 11:36:08	ga_s2am_ard_3-2-1_50JQM_2017-08-29_final
2017-11-17 11:36:01	ga_s2am_ard_3-2-1_50JQM_2017-11-17_final
2019-02-20 11:36:01	ga_s2am_ard_3-2-1_50JQM_2019-02-20_final
2019-03-02 11:36:00	ga_s2am_ard_3-2-1_50JQM_2019-03-02_final
2019-03-12 11:36:01	ga_s2am_ard_3-2-1_50JQM_2019-03-12_final
2019-03-22 11:36:03	ga_s2am_ard_3-2-1_50JQM_2019-03-22_final
2019-04-01 11:36:05	ga_s2am_ard_3-2-1_50JQM_2019-04-01_final
2019-04-11 11:36:07	ga_s2am_ard_3-2-1_50JQM_2019-04-11_final
2019-04-21 11:36:08	ga_s2am_ard_3-2-1_50JQM_2019-04-21_final
2019-05-01 11:36:09	ga_s2am_ard_3-2-1_50JQM_2019-05-01_final
2019-05-11 11:36:09	ga_s2am_ard_3-2-1_50JQM_2019-05-11_final
2019-05-21 11:36:09	ga_s2am_ard_3-2-1_50JQM_2019-05-21_final
2019-05-31 11:36:08	ga_s2am_ard_3-2-1_50JQM_2019-05-31_final
2019-06-10 11:36:08	ga_s2am_ard_3-2-1_50JQM_2019-06-10_final
2019-06-20 11:36:09	ga_s2am_ard_3-2-1_50JQM_2019-06-20_final
2019-06-30 11:36:10	ga_s2am_ard_3-2-1_50JQM_2019-06-30_final
2019-07-10 11:36:10	ga_s2am_ard_3-2-1_50JQM_2019-07-10_final
2019-07-20 11:36:10	ga_s2am_ard_3-2-1_50JQM_2019-07-20_final
2019-07-30 11:36:10	ga_s2am_ard_3-2-1_50JQM_2019-07-30_final
2019-08-09 11:36:09	ga_s2am_ard_3-2-1_50JQM_2019-08-09_final
2020-02-15 11:35:58	ga_s2am_ard_3-2-1_50JQM_2020-02-15_final
2020-03-16 11:36:01	ga_s2am_ard_3-2-1_50JQM_2020-03-16_final
2021-04-30 11:36:03	ga_s2am_ard_3-2-1_50JQM_2021-04-30_final
2022-06-27 11:46:13	ga_s2am_ard_3-2-1_50JQM_2022-06-27_final
2022-07-07 11:46:14	ga_s2am_ard_3-2-1_50JQM_2022-07-07_final
2022-07-17 11:46:13	ga_s2am_ard_3-2-1_50JQM_2022-07-17_final
2022-07-27 11:46:10	ga_s2am_ard_3-2-1_50JQM_2022-07-27_final
2022-08-06 11:46:12	ga_s2am_ard_3-2-1_50JQM_2022-08-06_final
2022-08-16 11:46:13	ga_s2am_ard_3-2-1_50JQM_2022-08-16_final
2022-08-26 11:46:13	ga_s2am_ard_3-2-1_50JQM_2022-08-26_final.stac-item
2022-09-02 11:36:17	ga_s2am_ard_3-2-1_50JQM_2022-09-02_final.stac-item
2022-09-05 11:46:12	ga_s2am_ard_3-2-1_50JQM_2022-09-05_final.stac-item
2022-09-12 11:36:16	ga_s2am_ard_3-2-1_50JQM_2022-09-12_final.stac-item
2022-09-15 11:46:10	ga_s2am_ard_3-2-1_50JQM_2022-09-15_final.stac-item
2022-09-22 11:36:12	ga_s2am_ard_3-2-1_50JQM_2022-09-22_final.stac-item
2022-09-25 11:46:08	ga_s2am_ard_3-2-1_50JQM_2022-09-25_final.stac-item
2022-10-02 11:36:12	ga_s2am_ard_3-2-1_50JQM_2022-10-02_final.stac-item
2022-10-05 11:46:08	ga_s2am_ard_3-2-1_50JQM_2022-10-05_final.stac-item
2022-10-12 11:36:10	ga_s2am_ard_3-2-1_50JQM_2022-10-12_final.stac-item
2022-10-15 11:46:05	ga_s2am_ard_3-2-1_50JQM_2022-10-15_final.stac-item
2022-10-22 11:36:07	ga_s2am_ard_3-2-1_50JQM_2022-10-22_final.stac-item
2022-10-25 11:46:03	ga_s2am_ard_3-2-1_50JQM_2022-10-25_final.stac-item
2022-11-01 11:36:09	ga_s2am_ard_3-2-1_50JQM_2022-11-01_final.stac-item
2022-11-04 11:46:05	ga_s2am_ard_3-2-1_50JQM_2022-11-04_final.stac-item
2022-11-11 11:36:09	ga_s2am_ard_3-2-1_50JQM_2022-11-11_final.stac-item
2022-11-14 11:46:03	ga_s2am_ard_3-2-1_50JQM_2022-11-14_final.stac-item
2022-11-21 11:36:06	ga_s2am_ard_3-2-1_50JQM_2022-11-21_final.stac-item
2022-11-24 11:46:00	ga_s2am_ard_3-2-1_50JQM_2022-11-24_final.stac-item
2022-12-01 11:36:05	ga_s2am_ard_3-2-1_50JQM_2022-12-01_final.stac-item
2022-12-04 11:46:01	ga_s2am_ard_3-2-1_50JQM_2022-12-04_final.stac-item
2022-12-11 11:36:05	ga_s2am_ard_3-2-1_50JQM_2022-12-11_final.stac-item
2022-12-14 11:46:01	ga_s2am_ard_3-2-1_50JQM_2022-12-14_final.stac-item
2022-12-21 11:36:03	ga_s2am_ard_3-2-1_50JQM_2022-12-21_final.stac-item
2022-12-24 11:45:58	ga_s2am_ard_3-2-1_50JQM_2022-12-24_final.stac-item
2022-12-31 11:36:04	ga_s2am_ard_3-2-1_50JQM_2022-12-31_final.stac-item
2023-01-03 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-01-03_final.stac-item
2023-01-10 11:36:03	ga_s2am_ard_3-2-1_50JQM_2023-01-10_final.stac-item
2023-01-13 11:45:58	ga_s2am_ard_3-2-1_50JQM_2023-01-13_final.stac-item
2023-01-20 11:36:00	ga_s2am_ard_3-2-1_50JQM_2023-01-20_final.stac-item
2023-01-23 11:45:57	ga_s2am_ard_3-2-1_50JQM_2023-01-23_final.stac-item
2023-01-30 11:36:03	ga_s2am_ard_3-2-1_50JQM_2023-01-30_final.stac-item
2023-02-02 11:45:59	ga_s2am_ard_3-2-1_50JQM_2023-02-02_final.stac-item
2023-02-09 11:36:04	ga_s2am_ard_3-2-1_50JQM_2023-02-09_final.stac-item
2023-02-12 11:45:59	ga_s2am_ard_3-2-1_50JQM_2023-02-12_final.stac-item
2023-02-19 11:36:02	ga_s2am_ard_3-2-1_50JQM_2023-02-19_final.stac-item
2023-02-22 11:45:58	ga_s2am_ard_3-2-1_50JQM_2023-02-22_final.stac-item
2023-03-01 11:36:02	ga_s2am_ard_3-2-1_50JQM_2023-03-01_final.stac-item
2023-03-04 11:45:57	ga_s2am_ard_3-2-1_50JQM_2023-03-04_final.stac-item
2023-03-11 11:36:00	ga_s2am_ard_3-2-1_50JQM_2023-03-11_final.stac-item
2023-03-14 11:45:57	ga_s2am_ard_3-2-1_50JQM_2023-03-14_final.stac-item
2023-03-21 11:36:04	ga_s2am_ard_3-2-1_50JQM_2023-03-21_final.stac-item
2023-03-24 11:45:59	ga_s2am_ard_3-2-1_50JQM_2023-03-24_final.stac-item
2023-03-31 11:36:03	ga_s2am_ard_3-2-1_50JQM_2023-03-31_final.stac-item
2023-04-03 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-04-03_final.stac-item
2023-04-10 11:36:05	ga_s2am_ard_3-2-1_50JQM_2023-04-10_final.stac-item
2023-04-13 11:46:01	ga_s2am_ard_3-2-1_50JQM_2023-04-13_final.stac-item
2023-04-23 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-04-23_final.stac-item
2023-05-03 11:46:01	ga_s2am_ard_3-2-1_50JQM_2023-05-03_final.stac-item
2023-05-13 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-05-13_final.stac-item
2023-05-23 11:46:04	ga_s2am_ard_3-2-1_50JQM_2023-05-23_final.stac-item
2023-06-02 11:46:04	ga_s2am_ard_3-2-1_50JQM_2023-06-02_final.stac-item
2023-06-12 11:46:05	ga_s2am_ard_3-2-1_50JQM_2023-06-12_final.stac-item
2023-06-22 11:46:04	ga_s2am_ard_3-2-1_50JQM_2023-06-22_final.stac-item
2023-07-02 11:46:05	ga_s2am_ard_3-2-1_50JQM_2023-07-02_final.stac-item
2023-07-12 11:46:06	ga_s2am_ard_3-2-1_50JQM_2023-07-12_final.stac-item
2023-07-22 11:46:05	ga_s2am_ard_3-2-1_50JQM_2023-07-22_final.stac-item
2023-08-01 11:46:06	ga_s2am_ard_3-2-1_50JQM_2023-08-01_final.stac-item
2023-08-11 11:46:05	ga_s2am_ard_3-2-1_50JQM_2023-08-11_final.stac-item
2023-08-21 11:46:07	ga_s2am_ard_3-2-1_50JQM_2023-08-21_final.stac-item
2023-08-31 11:46:06	ga_s2am_ard_3-2-1_50JQM_2023-08-31_final.stac-item
2023-09-10 11:46:06	ga_s2am_ard_3-2-1_50JQM_2023-09-10_final.stac-item
2023-09-20 11:46:03	ga_s2am_ard_3-2-1_50JQM_2023-09-20_final.stac-item
2023-09-30 11:46:03	ga_s2am_ard_3-2-1_50JQM_2023-09-30_final.stac-item
2023-10-10 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-10-10_final.stac-item
2023-10-20 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-10-20_final.stac-item
2023-10-30 11:46:00	ga_s2am_ard_3-2-1_50JQM_2023-10-30_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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