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
2021-03-18 11:24:25	ga_s2am_ard_3-2-1_51JXN_2021-03-18_final
2021-04-30 11:34:13	ga_s2am_ard_3-2-1_51JXN_2021-04-30_final
2021-05-17 11:24:26	ga_s2am_ard_3-2-1_51JXN_2021-05-17_final
2021-06-09 11:34:16	ga_s2am_ard_3-2-1_51JXN_2021-06-09_final
2021-09-27 11:34:19	ga_s2am_ard_3-2-1_51JXN_2021-09-27_final
2021-10-24 11:24:31	ga_s2am_ard_3-2-1_51JXN_2021-10-24_final
2021-10-27 11:34:20	ga_s2am_ard_3-2-1_51JXN_2021-10-27_final
2021-11-03 11:24:30	ga_s2am_ard_3-2-1_51JXN_2021-11-03_final
2021-11-06 11:34:19	ga_s2am_ard_3-2-1_51JXN_2021-11-06_final
2021-11-13 11:24:28	ga_s2am_ard_3-2-1_51JXN_2021-11-13_final
2021-11-16 11:34:16	ga_s2am_ard_3-2-1_51JXN_2021-11-16_final
2021-11-23 11:24:26	ga_s2am_ard_3-2-1_51JXN_2021-11-23_final
2021-11-26 11:34:15	ga_s2am_ard_3-2-1_51JXN_2021-11-26_final
2021-12-03 11:24:26	ga_s2am_ard_3-2-1_51JXN_2021-12-03_final
2021-12-06 11:34:14	ga_s2am_ard_3-2-1_51JXN_2021-12-06_final
2021-12-13 11:24:18	ga_s2am_ard_3-2-1_51JXN_2021-12-13_final
2021-12-13 11:24:26	ga_s2am_ard_3-2-1_51JXN_2021-12-13_final
2021-12-16 11:34:15	ga_s2am_ard_3-2-1_51JXN_2021-12-16_final
2021-12-23 11:24:27	ga_s2am_ard_3-2-1_51JXN_2021-12-23_final
2021-12-26 11:34:17	ga_s2am_ard_3-2-1_51JXN_2021-12-26_final
2022-01-02 11:24:28	ga_s2am_ard_3-2-1_51JXN_2022-01-02_final
2022-01-05 11:34:17	ga_s2am_ard_3-2-1_51JXN_2022-01-05_final
2022-01-12 11:24:27	ga_s2am_ard_3-2-1_51JXN_2022-01-12_final
2022-01-15 11:34:16	ga_s2am_ard_3-2-1_51JXN_2022-01-15_final
2022-01-22 11:24:26	ga_s2am_ard_3-2-1_51JXN_2022-01-22_final
2022-01-25 11:34:15	ga_s2am_ard_3-2-1_51JXN_2022-01-25_final
2022-02-01 11:24:26	ga_s2am_ard_3-2-1_51JXN_2022-02-01_final
2022-02-04 11:34:15	ga_s2am_ard_3-2-1_51JXN_2022-02-04_final
2022-02-11 11:24:25	ga_s2am_ard_3-2-1_51JXN_2022-02-11_final
2022-02-14 11:34:15	ga_s2am_ard_3-2-1_51JXN_2022-02-14_final
2022-02-21 11:24:28	ga_s2am_ard_3-2-1_51JXN_2022-02-21_final
2022-02-24 11:34:18	ga_s2am_ard_3-2-1_51JXN_2022-02-24_final
2022-03-03 11:24:30	ga_s2am_ard_3-2-1_51JXN_2022-03-03_final
2022-03-06 11:34:19	ga_s2am_ard_3-2-1_51JXN_2022-03-06_final
2022-03-13 11:24:30	ga_s2am_ard_3-2-1_51JXN_2022-03-13_final
2022-03-16 11:34:19	ga_s2am_ard_3-2-1_51JXN_2022-03-16_final
2022-03-23 11:24:29	ga_s2am_ard_3-2-1_51JXN_2022-03-23_final
2022-03-26 11:34:18	ga_s2am_ard_3-2-1_51JXN_2022-03-26_final
2022-04-02 11:24:28	ga_s2am_ard_3-2-1_51JXN_2022-04-02_final
2022-04-05 11:34:17	ga_s2am_ard_3-2-1_51JXN_2022-04-05_final
2022-04-12 11:24:28	ga_s2am_ard_3-2-1_51JXN_2022-04-12_final
2022-04-15 11:34:18	ga_s2am_ard_3-2-1_51JXN_2022-04-15_final
2022-04-22 11:24:31	ga_s2am_ard_3-2-1_51JXN_2022-04-22_final
2022-04-25 11:34:20	ga_s2am_ard_3-2-1_51JXN_2022-04-25_final
2022-05-02 11:24:31	ga_s2am_ard_3-2-1_51JXN_2022-05-02_final
2022-05-05 11:34:20	ga_s2am_ard_3-2-1_51JXN_2022-05-05_final
2022-05-12 11:24:30	ga_s2am_ard_3-2-1_51JXN_2022-05-12_final
2022-05-15 11:34:20	ga_s2am_ard_3-2-1_51JXN_2022-05-15_final
2022-05-22 11:24:33	ga_s2am_ard_3-2-1_51JXN_2022-05-22_final
2022-05-25 11:34:22	ga_s2am_ard_3-2-1_51JXN_2022-05-25_final
2022-06-01 11:24:34	ga_s2am_ard_3-2-1_51JXN_2022-06-01_final
2022-06-04 11:34:23	ga_s2am_ard_3-2-1_51JXN_2022-06-04_final
2022-06-11 11:24:36	ga_s2am_ard_3-2-1_51JXN_2022-06-11_final
2022-06-14 11:34:25	ga_s2am_ard_3-2-1_51JXN_2022-06-14_final
2022-06-21 11:24:38	ga_s2am_ard_3-2-1_51JXN_2022-06-21_final
2022-06-24 11:34:27	ga_s2am_ard_3-2-1_51JXN_2022-06-24_final
2022-07-01 11:24:39	ga_s2am_ard_3-2-1_51JXN_2022-07-01_final
2022-07-04 11:34:28	ga_s2am_ard_3-2-1_51JXN_2022-07-04_final
2022-07-11 11:24:39	ga_s2am_ard_3-2-1_51JXN_2022-07-11_final
2022-07-14 11:34:28	ga_s2am_ard_3-2-1_51JXN_2022-07-14_final
2022-07-21 11:24:38	ga_s2am_ard_3-2-1_51JXN_2022-07-21_final
2022-07-24 11:34:26	ga_s2am_ard_3-2-1_51JXN_2022-07-24_final
2022-07-31 11:24:36	ga_s2am_ard_3-2-1_51JXN_2022-07-31_final
2022-08-03 11:34:26	ga_s2am_ard_3-2-1_51JXN_2022-08-03_final
2022-08-10 11:24:38	ga_s2am_ard_3-2-1_51JXN_2022-08-10_final
2022-08-13 11:34:27	ga_s2am_ard_3-2-1_51JXN_2022-08-13_final
2022-08-20 11:24:35	ga_s2am_ard_3-2-1_51JXN_2022-08-20_final
2022-08-20 11:24:42	ga_s2am_ard_3-2-1_51JXN_2022-08-20_final
2023-02-06 11:24:25	ga_s2am_ard_3-2-1_51JXN_2023-02-06_final.stac-item
2023-02-16 11:24:23	ga_s2am_ard_3-2-1_51JXN_2023-02-16_final.stac-item
2023-02-19 11:34:12	ga_s2am_ard_3-2-1_51JXN_2023-02-19_final.stac-item
2023-02-26 11:24:24	ga_s2am_ard_3-2-1_51JXN_2023-02-26_final.stac-item
2023-03-01 11:34:13	ga_s2am_ard_3-2-1_51JXN_2023-03-01_final.stac-item
2023-03-08 11:24:22	ga_s2am_ard_3-2-1_51JXN_2023-03-08_final.stac-item
2023-03-11 11:34:11	ga_s2am_ard_3-2-1_51JXN_2023-03-11_final.stac-item
2023-03-18 11:24:24	ga_s2am_ard_3-2-1_51JXN_2023-03-18_final.stac-item
2023-03-21 11:34:14	ga_s2am_ard_3-2-1_51JXN_2023-03-21_final.stac-item
2023-03-28 11:24:24	ga_s2am_ard_3-2-1_51JXN_2023-03-28_final.stac-item
2023-03-31 11:34:14	ga_s2am_ard_3-2-1_51JXN_2023-03-31_final.stac-item
2023-04-07 11:24:26	ga_s2am_ard_3-2-1_51JXN_2023-04-07_final.stac-item
2023-04-10 11:34:15	ga_s2am_ard_3-2-1_51JXN_2023-04-10_final.stac-item
2023-04-20 11:34:14	ga_s2am_ard_3-2-1_51JXN_2023-04-20_final.stac-item
2023-04-27 11:24:26	ga_s2am_ard_3-2-1_51JXN_2023-04-27_final.stac-item
2023-04-30 11:34:15	ga_s2am_ard_3-2-1_51JXN_2023-04-30_final.stac-item
2023-05-07 11:24:26	ga_s2am_ard_3-2-1_51JXN_2023-05-07_final.stac-item
2023-05-10 11:34:15	ga_s2am_ard_3-2-1_51JXN_2023-05-10_final.stac-item
2023-05-17 11:24:28	ga_s2am_ard_3-2-1_51JXN_2023-05-17_final.stac-item
2023-05-20 11:34:17	ga_s2am_ard_3-2-1_51JXN_2023-05-20_final.stac-item
2023-05-27 11:24:30	ga_s2am_ard_3-2-1_51JXN_2023-05-27_final.stac-item
2023-05-30 11:34:19	ga_s2am_ard_3-2-1_51JXN_2023-05-30_final.stac-item
2023-06-06 11:24:30	ga_s2am_ard_3-2-1_51JXN_2023-06-06_final.stac-item
2023-06-09 11:34:19	ga_s2am_ard_3-2-1_51JXN_2023-06-09_final.stac-item
2023-10-14 11:24:24	ga_s2am_ard_3-2-1_51JXN_2023-10-14_final.stac-item
2023-10-17 11:34:15	ga_s2am_ard_3-2-1_51JXN_2023-10-17_final.stac-item
2023-10-24 11:24:26	ga_s2am_ard_3-2-1_51JXN_2023-10-24_final.stac-item
2023-10-27 11:34:15	ga_s2am_ard_3-2-1_51JXN_2023-10-27_final.stac-item
2023-11-03 11:24:25	ga_s2am_ard_3-2-1_51JXN_2023-11-03_final.stac-item
2023-11-16 11:34:14	ga_s2am_ard_3-2-1_51JXN_2023-11-16_final.stac-item
2023-11-16 11:34:14	ga_s2am_ard_3-2-1_51JXN_2023-11-16_final.stac-item
2023-11-23 11:24:22	ga_s2am_ard_3-2-1_51JXN_2023-11-23_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

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