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
2017-11-01 11:12:01	ga_s2am_ard_3-2-1_52JBS_2017-11-01_final.stac-item
2017-11-14 11:22:07	ga_s2am_ard_3-2-1_52JBS_2017-11-14_final.stac-item
2017-12-11 11:11:56	ga_s2am_ard_3-2-1_52JBS_2017-12-11_final.stac-item
2017-12-24 11:22:03	ga_s2am_ard_3-2-1_52JBS_2017-12-24_final.stac-item
2017-12-31 11:11:55	ga_s2am_ard_3-2-1_52JBS_2017-12-31_final.stac-item
2018-02-02 11:24:26	ga_s2am_ard_3-2-1_52JBS_2018-02-02_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_52JBS_2018-02-12_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_52JBS_2018-02-19_final.stac-item
2018-03-01 11:11:47	ga_s2am_ard_3-2-1_52JBS_2018-03-01_final.stac-item
2018-03-04 11:22:24	ga_s2am_ard_3-2-1_52JBS_2018-03-04_final.stac-item
2018-03-11 11:12:00	ga_s2am_ard_3-2-1_52JBS_2018-03-11_final.stac-item
2018-03-24 11:24:03	ga_s2am_ard_3-2-1_52JBS_2018-03-24_final.stac-item
2018-03-31 11:07:12	ga_s2am_ard_3-2-1_52JBS_2018-03-31_final.stac-item
2018-04-03 11:23:03	ga_s2am_ard_3-2-1_52JBS_2018-04-03_final.stac-item
2018-04-10 11:09:59	ga_s2am_ard_3-2-1_52JBS_2018-04-10_final.stac-item
2018-04-13 11:20:51	ga_s2am_ard_3-2-1_52JBS_2018-04-13_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_52JBS_2018-04-23_final.stac-item
2018-05-30 11:13:18	ga_s2am_ard_3-2-1_52JBS_2018-05-30_final.stac-item
2018-06-09 11:13:13	ga_s2am_ard_3-2-1_52JBS_2018-06-09_final.stac-item
2018-06-12 11:22:26	ga_s2am_ard_3-2-1_52JBS_2018-06-12_final.stac-item
2018-06-22 11:20:28	ga_s2am_ard_3-2-1_52JBS_2018-06-22_final.stac-item
2018-06-29 11:07:13	ga_s2am_ard_3-2-1_52JBS_2018-06-29_final.stac-item
2018-07-02 11:23:55	ga_s2am_ard_3-2-1_52JBS_2018-07-02_final.stac-item
2018-07-12 11:19:28	ga_s2am_ard_3-2-1_52JBS_2018-07-12_final.stac-item
2018-07-19 11:09:45	ga_s2am_ard_3-2-1_52JBS_2018-07-19_final.stac-item
2018-07-29 11:13:14	ga_s2am_ard_3-2-1_52JBS_2018-07-29_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_52JBS_2018-08-01_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52JBS_2018-08-28_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_52JBS_2018-09-10_final.stac-item
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_52JBS_2018-09-20_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_52JBS_2018-10-10_final.stac-item
2018-10-17 11:12:52	ga_s2am_ard_3-2-1_52JBS_2018-10-17_final.stac-item
2018-10-20 11:23:51	ga_s2am_ard_3-2-1_52JBS_2018-10-20_final.stac-item
2018-10-27 11:13:53	ga_s2am_ard_3-2-1_52JBS_2018-10-27_final.stac-item
2018-11-09 11:24:28	ga_s2am_ard_3-2-1_52JBS_2018-11-09_final.stac-item
2018-11-19 11:24:26	ga_s2am_ard_3-2-1_52JBS_2018-11-19_final.stac-item
2018-11-29 11:24:24	ga_s2am_ard_3-2-1_52JBS_2018-11-29_final.stac-item
2018-12-06 11:14:29	ga_s2am_ard_3-2-1_52JBS_2018-12-06_final.stac-item
2018-12-09 11:24:24	ga_s2am_ard_3-2-1_52JBS_2018-12-09_final.stac-item
2018-12-16 11:14:29	ga_s2am_ard_3-2-1_52JBS_2018-12-16_final.stac-item
2018-12-26 11:14:31	ga_s2am_ard_3-2-1_52JBS_2018-12-26_final.stac-item
2018-12-29 11:24:26	ga_s2am_ard_3-2-1_52JBS_2018-12-29_final.stac-item
2019-01-15 11:14:34	ga_s2am_ard_3-2-1_52JBS_2019-01-15_final.stac-item
2019-01-18 11:24:28	ga_s2am_ard_3-2-1_52JBS_2019-01-18_final.stac-item
2019-01-28 11:24:29	ga_s2am_ard_3-2-1_52JBS_2019-01-28_final.stac-item
2019-02-04 11:14:35	ga_s2am_ard_3-2-1_52JBS_2019-02-04_final.stac-item
2019-02-14 11:14:34	ga_s2am_ard_3-2-1_52JBS_2019-02-14_final.stac-item
2019-02-17 11:24:25	ga_s2am_ard_3-2-1_52JBS_2019-02-17_final.stac-item
2019-02-17 11:24:31	ga_s2am_ard_3-2-1_52JBS_2019-02-17_final.stac-item
2019-02-24 11:14:34	ga_s2am_ard_3-2-1_52JBS_2019-02-24_final.stac-item
2022-04-22 11:24:37	ga_s2am_ard_3-2-1_52JBS_2022-04-22_final.stac-item
2022-04-29 11:14:43	ga_s2am_ard_3-2-1_52JBS_2022-04-29_final.stac-item
2022-05-09 11:14:42	ga_s2am_ard_3-2-1_52JBS_2022-05-09_final.stac-item
2022-05-12 11:24:36	ga_s2am_ard_3-2-1_52JBS_2022-05-12_final.stac-item
2022-05-19 11:14:44	ga_s2am_ard_3-2-1_52JBS_2022-05-19_final.stac-item
2022-05-22 11:24:39	ga_s2am_ard_3-2-1_52JBS_2022-05-22_final.stac-item
2022-05-29 11:14:45	ga_s2am_ard_3-2-1_52JBS_2022-05-29_final.stac-item
2022-06-01 11:24:40	ga_s2am_ard_3-2-1_52JBS_2022-06-01_final.stac-item
2022-06-11 11:24:42	ga_s2am_ard_3-2-1_52JBS_2022-06-11_final.stac-item
2022-07-08 11:14:51	ga_s2am_ard_3-2-1_52JBS_2022-07-08_final.stac-item
2022-07-11 11:24:45	ga_s2am_ard_3-2-1_52JBS_2022-07-11_final.stac-item
2022-07-21 11:24:44	ga_s2am_ard_3-2-1_52JBS_2022-07-21_final.stac-item
2022-07-28 11:14:47	ga_s2am_ard_3-2-1_52JBS_2022-07-28_final.stac-item
2022-07-31 11:24:42	ga_s2am_ard_3-2-1_52JBS_2022-07-31_final.stac-item
2022-08-07 11:14:49	ga_s2am_ard_3-2-1_52JBS_2022-08-07_final.stac-item
2022-08-10 11:24:44	ga_s2am_ard_3-2-1_52JBS_2022-08-10_final.stac-item
2022-09-16 11:14:47	ga_s2am_ard_3-2-1_52JBS_2022-09-16_final.stac-item
2022-09-29 11:24:40	ga_s2am_ard_3-2-1_52JBS_2022-09-29_final.stac-item
2022-10-06 11:14:45	ga_s2am_ard_3-2-1_52JBS_2022-10-06_final.stac-item
2022-10-16 11:14:42	ga_s2am_ard_3-2-1_52JBS_2022-10-16_final.stac-item
2022-10-19 11:24:35	ga_s2am_ard_3-2-1_52JBS_2022-10-19_final.stac-item
2022-10-26 11:14:41	ga_s2am_ard_3-2-1_52JBS_2022-10-26_final.stac-item
2022-10-29 11:24:36	ga_s2am_ard_3-2-1_52JBS_2022-10-29_final.stac-item
2022-11-05 11:14:42	ga_s2am_ard_3-2-1_52JBS_2022-11-05_final.stac-item
2022-11-15 11:14:40	ga_s2am_ard_3-2-1_52JBS_2022-11-15_final.stac-item
2022-11-18 11:24:34	ga_s2am_ard_3-2-1_52JBS_2022-11-18_final.stac-item
2022-11-25 11:14:37	ga_s2am_ard_3-2-1_52JBS_2022-11-25_final.stac-item
2022-11-28 11:24:32	ga_s2am_ard_3-2-1_52JBS_2022-11-28_final.stac-item
2022-12-05 11:14:38	ga_s2am_ard_3-2-1_52JBS_2022-12-05_final.stac-item
2022-12-08 11:24:33	ga_s2am_ard_3-2-1_52JBS_2022-12-08_final.stac-item
2022-12-15 11:14:35	ga_s2am_ard_3-2-1_52JBS_2022-12-15_final.stac-item
2022-12-15 11:14:42	ga_s2am_ard_3-2-1_52JBS_2022-12-15_final.stac-item
2022-12-18 11:24:31	ga_s2am_ard_3-2-1_52JBS_2022-12-18_final.stac-item
2022-12-25 11:14:35	ga_s2am_ard_3-2-1_52JBS_2022-12-25_final.stac-item
2022-12-25 11:14:42	ga_s2am_ard_3-2-1_52JBS_2022-12-25_final.stac-item
2022-12-28 11:24:31	ga_s2am_ard_3-2-1_52JBS_2022-12-28_final.stac-item
2023-01-04 11:14:33	ga_s2am_ard_3-2-1_52JBS_2023-01-04_final.stac-item
2023-01-04 11:14:39	ga_s2am_ard_3-2-1_52JBS_2023-01-04_final.stac-item
2023-01-07 11:24:31	ga_s2am_ard_3-2-1_52JBS_2023-01-07_final.stac-item
2023-01-14 11:14:35	ga_s2am_ard_3-2-1_52JBS_2023-01-14_final.stac-item
2023-01-17 11:24:28	ga_s2am_ard_3-2-1_52JBS_2023-01-17_final.stac-item
2023-01-24 11:14:34	ga_s2am_ard_3-2-1_52JBS_2023-01-24_final.stac-item
2023-01-27 11:24:30	ga_s2am_ard_3-2-1_52JBS_2023-01-27_final.stac-item
2023-02-03 11:14:37	ga_s2am_ard_3-2-1_52JBS_2023-02-03_final.stac-item
2023-02-06 11:24:31	ga_s2am_ard_3-2-1_52JBS_2023-02-06_final
2023-02-13 11:14:36	ga_s2am_ard_3-2-1_52JBS_2023-02-13_final
2023-02-16 11:24:29	ga_s2am_ard_3-2-1_52JBS_2023-02-16_final
2023-08-02 11:14:43	ga_s2am_ard_3-2-1_52JBS_2023-08-02_final
2023-08-05 11:24:37	ga_s2am_ard_3-2-1_52JBS_2023-08-05_final
2023-08-12 11:14:43	ga_s2am_ard_3-2-1_52JBS_2023-08-12_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