Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-02-05 10:20:28	ga_s2am_ard_3-2-1_54LVJ_2016-02-05_final.stac-item
2016-03-06 10:20:55	ga_s2am_ard_3-2-1_54LVJ_2016-03-06_final.stac-item
2016-03-29 10:28:49	ga_s2am_ard_3-2-1_54LVJ_2016-03-29_final.stac-item
2016-04-05 10:17:42	ga_s2am_ard_3-2-1_54LVJ_2016-04-05_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_54LVJ_2016-04-28_final.stac-item
2016-05-08 10:28:07	ga_s2am_ard_3-2-1_54LVJ_2016-05-08_final.stac-item
2016-05-25 10:20:04	ga_s2am_ard_3-2-1_54LVJ_2016-05-25_final.stac-item
2016-05-28 10:28:07	ga_s2am_ard_3-2-1_54LVJ_2016-05-28_final.stac-item
2016-06-14 10:20:02	ga_s2am_ard_3-2-1_54LVJ_2016-06-14_final.stac-item
2016-06-17 10:28:04	ga_s2am_ard_3-2-1_54LVJ_2016-06-17_final.stac-item
2016-07-24 10:20:03	ga_s2am_ard_3-2-1_54LVJ_2016-07-24_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_54LVJ_2016-07-27_final.stac-item
2016-08-13 10:20:02	ga_s2am_ard_3-2-1_54LVJ_2016-08-13_final.stac-item
2016-08-16 10:28:09	ga_s2am_ard_3-2-1_54LVJ_2016-08-16_final.stac-item
2016-09-02 10:19:59	ga_s2am_ard_3-2-1_54LVJ_2016-09-02_final.stac-item
2016-09-05 10:28:01	ga_s2am_ard_3-2-1_54LVJ_2016-09-05_final.stac-item
2016-09-22 10:19:54	ga_s2am_ard_3-2-1_54LVJ_2016-09-22_final.stac-item
2016-10-12 10:19:54	ga_s2am_ard_3-2-1_54LVJ_2016-10-12_final.stac-item
2016-10-15 10:27:57	ga_s2am_ard_3-2-1_54LVJ_2016-10-15_final.stac-item
2016-11-01 10:17:53	ga_s2am_ard_3-2-1_54LVJ_2016-11-01_final.stac-item
2016-11-04 10:27:06	ga_s2am_ard_3-2-1_54LVJ_2016-11-04_final.stac-item
2016-11-21 10:19:32	ga_s2am_ard_3-2-1_54LVJ_2016-11-21_final.stac-item
2016-12-04 10:28:24	ga_s2am_ard_3-2-1_54LVJ_2016-12-04_final.stac-item
2021-01-02 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-01-02_final
2021-01-09 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2021-01-09_final
2021-01-12 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-01-12_final
2021-01-19 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2021-01-19_final
2021-01-22 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-01-22_final
2021-01-29 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2021-01-29_final
2021-02-01 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-02-01_final
2021-02-08 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-02-08_final
2021-02-11 10:31:12	ga_s2am_ard_3-2-1_54LVJ_2021-02-11_final
2021-02-18 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-02-18_final
2021-02-21 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-02-21_final
2021-02-28 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-02-28_final
2021-03-03 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-03-03_final
2021-03-10 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-03-10_final
2021-03-13 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-03-13_final
2021-03-20 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-03-20_final
2021-03-23 10:31:12	ga_s2am_ard_3-2-1_54LVJ_2021-03-23_final
2021-03-30 10:21:18	ga_s2am_ard_3-2-1_54LVJ_2021-03-30_final
2021-04-02 10:31:10	ga_s2am_ard_3-2-1_54LVJ_2021-04-02_final
2021-04-09 10:21:16	ga_s2am_ard_3-2-1_54LVJ_2021-04-09_final
2021-04-12 10:31:08	ga_s2am_ard_3-2-1_54LVJ_2021-04-12_final
2021-04-19 10:21:16	ga_s2am_ard_3-2-1_54LVJ_2021-04-19_final
2021-04-22 10:31:09	ga_s2am_ard_3-2-1_54LVJ_2021-04-22_final
2021-04-22 10:31:09	ga_s2am_ard_3-2-1_54LVJ_2021-04-22_final
2021-04-29 10:21:18	ga_s2am_ard_3-2-1_54LVJ_2021-04-29_final
2021-05-02 10:31:11	ga_s2am_ard_3-2-1_54LVJ_2021-05-02_final
2021-05-09 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-05-09_final
2021-05-12 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-05-12_final
2021-05-19 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2021-05-19_final
2021-05-22 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-05-22_final
2021-05-29 10:21:22	ga_s2am_ard_3-2-1_54LVJ_2021-05-29_final
2021-06-01 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-06-01_final
2021-06-08 10:21:22	ga_s2am_ard_3-2-1_54LVJ_2021-06-08_final
2021-06-11 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-06-11_final
2021-06-18 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2021-06-18_final
2021-06-21 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-06-21_final
2021-06-28 10:21:22	ga_s2am_ard_3-2-1_54LVJ_2021-06-28_final
2021-07-01 10:31:15	ga_s2am_ard_3-2-1_54LVJ_2021-07-01_final
2021-07-08 10:21:24	ga_s2am_ard_3-2-1_54LVJ_2021-07-08_final
2021-07-11 10:31:16	ga_s2am_ard_3-2-1_54LVJ_2021-07-11_final
2021-07-18 10:21:24	ga_s2am_ard_3-2-1_54LVJ_2021-07-18_final
2021-07-21 10:31:17	ga_s2am_ard_3-2-1_54LVJ_2021-07-21_final
2021-07-28 10:21:24	ga_s2am_ard_3-2-1_54LVJ_2021-07-28_final
2021-07-31 10:31:17	ga_s2am_ard_3-2-1_54LVJ_2021-07-31_final
2021-08-07 10:21:24	ga_s2am_ard_3-2-1_54LVJ_2021-08-07_final
2021-08-10 10:31:16	ga_s2am_ard_3-2-1_54LVJ_2021-08-10_final
2021-08-17 10:21:23	ga_s2am_ard_3-2-1_54LVJ_2021-08-17_final
2021-08-20 10:31:16	ga_s2am_ard_3-2-1_54LVJ_2021-08-20_final
2021-08-27 10:21:23	ga_s2am_ard_3-2-1_54LVJ_2021-08-27_final
2021-08-30 10:31:15	ga_s2am_ard_3-2-1_54LVJ_2021-08-30_final
2021-09-06 10:21:21	ga_s2am_ard_3-2-1_54LVJ_2021-09-06_final
2021-09-09 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-09-09_final
2021-09-16 10:21:22	ga_s2am_ard_3-2-1_54LVJ_2021-09-16_final
2021-09-19 10:31:16	ga_s2am_ard_3-2-1_54LVJ_2021-09-19_final
2021-09-26 10:21:24	ga_s2am_ard_3-2-1_54LVJ_2021-09-26_final
2021-09-29 10:31:17	ga_s2am_ard_3-2-1_54LVJ_2021-09-29_final
2021-10-06 10:21:26	ga_s2am_ard_3-2-1_54LVJ_2021-10-06_final
2021-10-09 10:31:19	ga_s2am_ard_3-2-1_54LVJ_2021-10-09_final
2021-10-16 10:21:26	ga_s2am_ard_3-2-1_54LVJ_2021-10-16_final
2021-10-19 10:31:19	ga_s2am_ard_3-2-1_54LVJ_2021-10-19_final
2021-10-26 10:21:26	ga_s2am_ard_3-2-1_54LVJ_2021-10-26_final
2021-10-29 10:31:18	ga_s2am_ard_3-2-1_54LVJ_2021-10-29_final
2021-11-05 10:21:24	ga_s2am_ard_3-2-1_54LVJ_2021-11-05_final
2021-11-08 10:31:16	ga_s2am_ard_3-2-1_54LVJ_2021-11-08_final
2021-11-15 10:21:22	ga_s2am_ard_3-2-1_54LVJ_2021-11-15_final
2021-11-18 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-11-18_final
2021-11-28 10:31:13	ga_s2am_ard_3-2-1_54LVJ_2021-11-28_final
2021-12-05 10:21:20	ga_s2am_ard_3-2-1_54LVJ_2021-12-05_final
2021-12-08 10:31:12	ga_s2am_ard_3-2-1_54LVJ_2021-12-08_final
2021-12-18 10:31:14	ga_s2am_ard_3-2-1_54LVJ_2021-12-18_final
2021-12-25 10:21:22	ga_s2am_ard_3-2-1_54LVJ_2021-12-25_final
2021-12-28 10:31:15	ga_s2am_ard_3-2-1_54LVJ_2021-12-28_final
2023-02-18 10:21:18	ga_s2am_ard_3-2-1_54LVJ_2023-02-18_nrt.stac-item
2023-02-21 10:31:08	ga_s2am_ard_3-2-1_54LVJ_2023-02-21_nrt.stac-item
2023-08-07 10:21:25	ga_s2am_ard_3-2-1_54LVJ_2023-08-07_final
2023-08-10 10:31:18	ga_s2am_ard_3-2-1_54LVJ_2023-08-10_final
2023-08-17 10:21:26	ga_s2am_ard_3-2-1_54LVJ_2023-08-17_final

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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years