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
2015-11-27 12:04:51	ga_s2am_ard_3-2-1_49JGL_2015-11-27_final.stac-item
2021-11-05 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-11-05_final
2021-11-08 12:15:13	ga_s2am_ard_3-2-1_49JGL_2021-11-08_final
2021-11-15 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-11-15_final
2021-11-18 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-11-18_final
2021-11-25 12:05:15	ga_s2am_ard_3-2-1_49JGL_2021-11-25_final
2021-11-28 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-11-28_final
2021-12-05 12:05:14	ga_s2am_ard_3-2-1_49JGL_2021-12-05_final
2021-12-08 12:15:09	ga_s2am_ard_3-2-1_49JGL_2021-12-08_final
2021-12-18 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-12-18_final
2021-12-25 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-12-25_final
2021-12-28 12:15:12	ga_s2am_ard_3-2-1_49JGL_2021-12-28_final
2022-01-07 12:15:12	ga_s2am_ard_3-2-1_49JGL_2022-01-07_final
2022-01-17 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-01-17_final
2022-01-27 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-01-27_final
2022-02-03 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-03_final
2022-02-06 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-02-06_final
2022-02-16 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-02-16_final
2022-02-23 12:05:17	ga_s2am_ard_3-2-1_49JGL_2022-02-23_final
2022-02-26 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-02-26_final
2022-03-05 12:05:09	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final
2022-03-05 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final
2022-03-18 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-03-18_final
2022-03-25 12:05:18	ga_s2am_ard_3-2-1_49JGL_2022-03-25_final
2022-04-14 12:05:18	ga_s2am_ard_3-2-1_49JGL_2022-04-14_final
2022-04-17 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-04-17_final
2022-04-24 12:05:20	ga_s2am_ard_3-2-1_49JGL_2022-04-24_final
2022-04-27 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-04-27_final
2022-04-27 12:15:17	ga_s2am_ard_3-2-1_49JGL_2022-04-27_final
2022-05-04 12:05:10	ga_s2am_ard_3-2-1_49JGL_2022-05-04_final
2022-05-04 12:05:20	ga_s2am_ard_3-2-1_49JGL_2022-05-04_final
2022-05-07 12:15:15	ga_s2am_ard_3-2-1_49JGL_2022-05-07_final
2022-05-14 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-05-14_final
2022-05-24 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-05-24_final
2022-05-27 12:15:18	ga_s2am_ard_3-2-1_49JGL_2022-05-27_final
2022-06-03 12:05:23	ga_s2am_ard_3-2-1_49JGL_2022-06-03_final
2022-06-06 12:15:18	ga_s2am_ard_3-2-1_49JGL_2022-06-06_final
2022-06-13 12:05:25	ga_s2am_ard_3-2-1_49JGL_2022-06-13_final
2022-06-16 12:15:21	ga_s2am_ard_3-2-1_49JGL_2022-06-16_final
2022-06-23 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-06-23_final
2022-06-26 12:15:23	ga_s2am_ard_3-2-1_49JGL_2022-06-26_final
2022-07-03 12:05:28	ga_s2am_ard_3-2-1_49JGL_2022-07-03_final
2022-07-06 12:15:23	ga_s2am_ard_3-2-1_49JGL_2022-07-06_final
2022-07-13 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-07-13_final
2022-07-16 12:15:23	ga_s2am_ard_3-2-1_49JGL_2022-07-16_final
2022-07-23 12:05:26	ga_s2am_ard_3-2-1_49JGL_2022-07-23_final
2022-07-26 12:15:20	ga_s2am_ard_3-2-1_49JGL_2022-07-26_final
2022-08-02 12:05:25	ga_s2am_ard_3-2-1_49JGL_2022-08-02_final
2022-08-05 12:15:21	ga_s2am_ard_3-2-1_49JGL_2022-08-05_final
2022-08-12 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-08-12_final
2022-08-15 12:15:23	ga_s2am_ard_3-2-1_49JGL_2022-08-15_final
2022-08-22 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-08-22_final
2022-08-25 12:15:23	ga_s2am_ard_3-2-1_49JGL_2022-08-25_final
2023-02-08 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-02-08_final.stac-item
2023-02-11 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-11_final.stac-item
2023-02-18 12:05:09	ga_s2am_ard_3-2-1_49JGL_2023-02-18_final.stac-item
2023-02-18 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-02-18_final.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_final.stac-item
2023-02-28 12:05:12	ga_s2am_ard_3-2-1_49JGL_2023-02-28_final.stac-item
2023-03-03 12:15:07	ga_s2am_ard_3-2-1_49JGL_2023-03-03_final.stac-item
2023-03-10 12:05:10	ga_s2am_ard_3-2-1_49JGL_2023-03-10_final.stac-item
2023-03-13 12:15:07	ga_s2am_ard_3-2-1_49JGL_2023-03-13_final.stac-item
2023-03-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-03-20_final.stac-item
2023-03-23 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-03-23_final.stac-item
2023-03-30 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-03-30_final.stac-item
2023-04-02 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-04-02_final.stac-item
2023-04-09 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-04-09_final.stac-item
2023-04-12 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-04-12_final.stac-item
2023-04-19 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-04-19_final.stac-item
2023-04-22 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-04-22_final.stac-item
2023-04-29 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-04-29_final.stac-item
2023-05-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2023-05-02_final.stac-item
2023-05-09 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-05-09_final.stac-item
2023-05-12 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-05-12_final.stac-item
2023-05-19 12:05:17	ga_s2am_ard_3-2-1_49JGL_2023-05-19_final.stac-item
2023-05-22 12:15:13	ga_s2am_ard_3-2-1_49JGL_2023-05-22_final.stac-item
2023-05-29 12:05:18	ga_s2am_ard_3-2-1_49JGL_2023-05-29_final.stac-item
2023-06-01 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-06-01_final.stac-item
2023-06-08 12:05:18	ga_s2am_ard_3-2-1_49JGL_2023-06-08_final.stac-item
2023-06-11 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-06-11_final.stac-item
2023-06-18 12:05:19	ga_s2am_ard_3-2-1_49JGL_2023-06-18_final.stac-item
2023-06-21 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-06-21_final.stac-item
2023-06-28 12:05:19	ga_s2am_ard_3-2-1_49JGL_2023-06-28_final.stac-item
2023-07-01 12:15:15	ga_s2am_ard_3-2-1_49JGL_2023-07-01_final.stac-item
2023-07-08 12:05:20	ga_s2am_ard_3-2-1_49JGL_2023-07-08_final.stac-item
2023-07-11 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-07-11_final.stac-item
2023-07-18 12:05:19	ga_s2am_ard_3-2-1_49JGL_2023-07-18_final.stac-item
2023-07-21 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-07-21_final.stac-item
2023-07-28 12:05:20	ga_s2am_ard_3-2-1_49JGL_2023-07-28_final.stac-item
2023-07-31 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-07-31_final.stac-item
2023-08-07 12:05:19	ga_s2am_ard_3-2-1_49JGL_2023-08-07_final.stac-item
2023-08-17 12:05:21	ga_s2am_ard_3-2-1_49JGL_2023-08-17_final.stac-item
2023-10-16 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-10-16_final.stac-item
2023-10-19 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-19_final.stac-item
2023-10-26 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-10-26_final.stac-item
2023-10-29 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-29_final.stac-item
2023-11-05 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-11-05_final.stac-item
2023-11-15 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-11-15_final.stac-item
2023-11-18 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-11-18_final.stac-item
2023-11-25 12:05:10	ga_s2am_ard_3-2-1_49JGL_2023-11-25_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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