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
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JFN_2018-09-05_final
2018-09-15 12:14:38	ga_s2am_ard_3-2-1_49JFN_2018-09-15_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JFN_2018-09-25_final
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49JFN_2018-10-05_final
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49JFN_2018-10-15_final
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49JFN_2018-10-25_final
2018-10-25 12:14:37	ga_s2am_ard_3-2-1_49JFN_2018-10-25_final
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49JFN_2018-11-04_final
2018-11-14 12:14:40	ga_s2am_ard_3-2-1_49JFN_2018-11-14_final
2018-11-24 12:14:38	ga_s2am_ard_3-2-1_49JFN_2018-11-24_final
2018-12-04 12:14:37	ga_s2am_ard_3-2-1_49JFN_2018-12-04_final
2018-12-14 12:14:37	ga_s2am_ard_3-2-1_49JFN_2018-12-14_final
2018-12-24 12:14:38	ga_s2am_ard_3-2-1_49JFN_2018-12-24_final
2019-01-03 12:14:40	ga_s2am_ard_3-2-1_49JFN_2019-01-03_final
2019-01-13 12:14:41	ga_s2am_ard_3-2-1_49JFN_2019-01-13_final
2019-01-23 12:14:42	ga_s2am_ard_3-2-1_49JFN_2019-01-23_final
2019-02-02 12:14:42	ga_s2am_ard_3-2-1_49JFN_2019-02-02_final
2019-02-12 12:14:42	ga_s2am_ard_3-2-1_49JFN_2019-02-12_final
2019-02-22 12:14:41	ga_s2am_ard_3-2-1_49JFN_2019-02-22_final
2019-03-04 12:14:40	ga_s2am_ard_3-2-1_49JFN_2019-03-04_final
2019-03-14 12:14:41	ga_s2am_ard_3-2-1_49JFN_2019-03-14_final
2019-03-24 12:14:44	ga_s2am_ard_3-2-1_49JFN_2019-03-24_final
2019-04-03 12:14:46	ga_s2am_ard_3-2-1_49JFN_2019-04-03_final
2019-04-13 12:14:47	ga_s2am_ard_3-2-1_49JFN_2019-04-13_final
2019-04-23 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-04-23_final
2019-05-03 12:14:49	ga_s2am_ard_3-2-1_49JFN_2019-05-03_final
2019-05-13 12:14:49	ga_s2am_ard_3-2-1_49JFN_2019-05-13_final
2019-05-23 12:14:49	ga_s2am_ard_3-2-1_49JFN_2019-05-23_final
2019-06-02 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-06-02_final
2019-06-12 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-06-12_final
2019-06-22 12:14:49	ga_s2am_ard_3-2-1_49JFN_2019-06-22_final
2019-07-02 12:14:50	ga_s2am_ard_3-2-1_49JFN_2019-07-02_final
2019-07-12 12:14:50	ga_s2am_ard_3-2-1_49JFN_2019-07-12_final
2019-07-22 12:14:50	ga_s2am_ard_3-2-1_49JFN_2019-07-22_final
2019-08-01 12:14:50	ga_s2am_ard_3-2-1_49JFN_2019-08-01_final
2019-08-11 12:14:49	ga_s2am_ard_3-2-1_49JFN_2019-08-11_final
2019-08-21 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-08-21_final
2019-08-31 12:14:46	ga_s2am_ard_3-2-1_49JFN_2019-08-31_final
2019-09-10 12:14:44	ga_s2am_ard_3-2-1_49JFN_2019-09-10_final
2019-09-20 12:14:45	ga_s2am_ard_3-2-1_49JFN_2019-09-20_final
2019-09-30 12:14:47	ga_s2am_ard_3-2-1_49JFN_2019-09-30_final
2019-10-10 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-10-10_final
2019-10-20 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-10-20_final
2019-10-30 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-10-30_final
2019-11-09 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-11-09_final
2019-11-19 12:14:47	ga_s2am_ard_3-2-1_49JFN_2019-11-19_final
2019-11-29 12:14:45	ga_s2am_ard_3-2-1_49JFN_2019-11-29_final
2019-12-09 12:14:42	ga_s2am_ard_3-2-1_49JFN_2019-12-09_final
2019-12-19 12:14:39	ga_s2am_ard_3-2-1_49JFN_2019-12-19_final
2022-12-13 12:15:14	ga_s2am_ard_3-2-1_49JFL_2022-12-13_nrt.stac-item
2022-12-23 12:15:12	ga_s2am_ard_3-2-1_49JFL_2022-12-23_nrt.stac-item
2023-01-02 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-01-02_nrt.stac-item
2023-01-12 12:15:12	ga_s2am_ard_3-2-1_49JFL_2023-01-12_nrt.stac-item
2023-01-22 12:15:10	ga_s2am_ard_3-2-1_49JFL_2023-01-22_nrt.stac-item
2023-02-01 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-02-01_nrt.stac-item
2023-02-11 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-02-11_nrt.stac-item
2023-02-21 12:15:12	ga_s2am_ard_3-2-1_49JFL_2023-02-21_nrt.stac-item
2023-03-03 12:15:11	ga_s2am_ard_3-2-1_49JFL_2023-03-03_nrt.stac-item
2023-03-13 12:15:11	ga_s2am_ard_3-2-1_49JFL_2023-03-13_nrt.stac-item
2023-03-23 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-03-23_nrt.stac-item
2023-04-02 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-04-02_nrt.stac-item
2023-08-20 12:15:20	ga_s2am_ard_3-2-1_49JFL_2023-08-20_nrt.stac-item
2023-08-27 12:05:25	ga_s2am_ard_3-2-1_49JFL_2023-08-27_final.stac-item
2023-08-30 12:15:19	ga_s2am_ard_3-2-1_49JFL_2023-08-30_nrt.stac-item
2023-09-06 12:05:24	ga_s2am_ard_3-2-1_49JFL_2023-09-06_final.stac-item
2023-09-09 12:15:19	ga_s2am_ard_3-2-1_49JFL_2023-09-09_nrt.stac-item
2023-09-16 12:05:23	ga_s2am_ard_3-2-1_49JFL_2023-09-16_final.stac-item
2023-09-19 12:15:16	ga_s2am_ard_3-2-1_49JFL_2023-09-19_nrt.stac-item
2023-09-26 12:05:21	ga_s2am_ard_3-2-1_49JFL_2023-09-26_final.stac-item
2023-09-29 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-09-29_nrt.stac-item
2023-09-29 12:15:19	ga_s2am_ard_3-2-1_49JFL_2023-09-29_nrt.stac-item
2023-10-09 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-10-09_nrt.stac-item
2023-10-19 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-10-19_nrt.stac-item
2023-10-29 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-10-29_nrt.stac-item
2023-11-08 12:15:13	ga_s2am_ard_3-2-1_49JFL_2023-11-08_nrt.stac-item
2023-11-18 12:15:12	ga_s2am_ard_3-2-1_49JFL_2023-11-18_nrt.stac-item
2023-11-28 12:15:06	ga_s2am_ard_3-2-1_49JFL_2023-11-28_final.stac-item
2023-12-08 12:15:08	ga_s2am_ard_3-2-1_49JFL_2023-12-08_final.stac-item
2023-12-28 12:15:11	ga_s2am_ard_3-2-1_49JFL_2023-12-28_final.stac-item
2024-01-07 12:15:10	ga_s2am_ard_3-2-1_49JFL_2024-01-07_final.stac-item
2024-01-17 12:15:06	ga_s2am_ard_3-2-1_49JFL_2024-01-17_final.stac-item
2024-01-27 12:15:08	ga_s2am_ard_3-2-1_49JFL_2024-01-27_final.stac-item
2024-02-06 12:15:10	ga_s2am_ard_3-2-1_49JFL_2024-02-06_final.stac-item
2024-02-16 12:15:12	ga_s2am_ard_3-2-1_49JFL_2024-02-16_final.stac-item
2024-02-26 12:15:13	ga_s2am_ard_3-2-1_49JFL_2024-02-26_final.stac-item
2024-03-07 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-03-07_final.stac-item
2024-03-17 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-03-17_final.stac-item
2024-03-24 12:05:20	ga_s2am_ard_3-2-1_49JFL_2024-03-24_final.stac-item
2024-03-27 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-03-27_final.stac-item
2024-04-06 12:15:12	ga_s2am_ard_3-2-1_49JFL_2024-04-06_nrt.stac-item
2024-04-13 12:05:21	ga_s2am_ard_3-2-1_49JFL_2024-04-13_nrt.stac-item
2024-04-16 12:15:17	ga_s2am_ard_3-2-1_49JFL_2024-04-16_nrt.stac-item
2024-04-23 12:05:22	ga_s2am_ard_3-2-1_49JFL_2024-04-23_nrt.stac-item
2024-04-26 12:15:16	ga_s2am_ard_3-2-1_49JFL_2024-04-26_nrt.stac-item
2024-05-03 12:05:22	ga_s2am_ard_3-2-1_49JFL_2024-05-03_nrt.stac-item
2024-05-06 12:15:16	ga_s2am_ard_3-2-1_49JFL_2024-05-06_nrt.stac-item
2024-05-13 12:05:22	ga_s2am_ard_3-2-1_49JFL_2024-05-13_nrt.stac-item
2024-05-16 12:15:16	ga_s2am_ard_3-2-1_49JFL_2024-05-16_nrt.stac-item
2024-05-26 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-05-26_nrt.stac-item
2024-06-02 12:05:23	ga_s2am_ard_3-2-1_49JFL_2024-06-02_nrt.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

All years