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
2015-09-29 11:36:06	ga_s2am_ard_3-2-1_50HQK_2015-09-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_51JUL_2016-04-29_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JQT_2016-06-11_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50KPF_2016-06-11_final.stac-item
2016-06-17 12:13:46	ga_s2am_ard_3-2-1_50KKV_2016-06-17_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JQT_2016-07-21_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_51JUL_2016-07-28_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HNG_2016-08-17_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50KPF_2016-09-19_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JQT_2016-10-09_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JQT_2017-02-26_final
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JPP_2017-06-06_final
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50KLU_2017-08-05_final
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50KLU_2017-10-04_final
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50KLU_2017-10-24_final
2018-02-21 11:50:43	ga_s2am_ard_3-2-1_50KLU_2018-02-21_final
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HLG_2018-02-28_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JQT_2018-03-13_final
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50KLU_2018-03-13_final
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50KLU_2018-03-23_final
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50KLU_2018-04-12_final
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50KLU_2018-05-12_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50KLU_2018-05-22_final
2018-05-29 11:39:24	ga_s2am_ard_3-2-1_50JQR_2018-05-29_final
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JQT_2018-07-01_final
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JQM_2018-07-08_final
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JQT_2018-07-21_final
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JQT_2018-07-31_final
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JQT_2018-08-30_final
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KLU_2018-10-19_final
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KLU_2018-10-29_final
2018-11-18 11:54:17	ga_s2am_ard_3-2-1_50JQT_2018-11-18_final
2019-02-06 11:54:30	ga_s2am_ard_3-2-1_50KLU_2019-02-06_final
2019-02-16 11:54:20	ga_s2am_ard_3-2-1_50JQT_2019-02-16_final
2019-02-16 11:54:30	ga_s2am_ard_3-2-1_50KLU_2019-02-16_final
2019-02-26 11:54:19	ga_s2am_ard_3-2-1_50JQT_2019-02-26_final
2019-03-18 11:54:20	ga_s2am_ard_3-2-1_50JQT_2019-03-18_final
2019-03-28 11:54:33	ga_s2am_ard_3-2-1_50KLU_2019-03-28_final
2019-04-07 11:54:34	ga_s2am_ard_3-2-1_50KLU_2019-04-07_final
2019-05-14 11:45:56	ga_s2am_ard_3-2-1_51JTG_2019-05-14_final
2019-06-16 11:54:27	ga_s2am_ard_3-2-1_50JQT_2019-06-16_final
2019-07-26 11:52:42	ga_s2am_ard_3-2-1_50KPF_2019-07-26_final.stac-item
2019-08-05 11:54:33	ga_s2am_ard_3-2-1_50KPU_2019-08-05_final
2019-08-05 11:54:38	ga_s2am_ard_3-2-1_50KLU_2019-08-05_final
2019-08-25 11:52:39	ga_s2am_ard_3-2-1_50KPF_2019-08-25_final.stac-item
2019-08-25 11:54:35	ga_s2am_ard_3-2-1_50KLU_2019-08-25_final
2019-09-14 11:54:32	ga_s2am_ard_3-2-1_50KLU_2019-09-14_final
2019-10-14 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-10-14_final
2019-10-24 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-10-24_final
2019-11-03 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-11-03_final
2020-02-14 12:04:22	ga_s2am_ard_3-2-1_50JMT_2020-02-14_final
2020-02-17 12:14:24	ga_s2am_ard_3-2-1_49KHP_2020-02-17_final
2020-03-02 11:54:29	ga_s2am_ard_3-2-1_50KLU_2020-03-02_final
2020-04-01 11:54:21	ga_s2am_ard_3-2-1_50JPT_2020-04-01_final
2020-04-11 11:54:21	ga_s2am_ard_3-2-1_50JQT_2020-04-11_final
2020-05-01 11:54:28	ga_s2am_ard_3-2-1_50JPT_2020-05-01_final
2020-05-01 11:54:36	ga_s2am_ard_3-2-1_50KLU_2020-05-01_final
2020-05-11 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-05-11_final
2020-06-30 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-06-30_final
2020-07-28 11:17:01	ga_s2am_ard_3-2-1_51HXC_2020-07-28_final.stac-item
2020-07-30 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-07-30_final
2020-08-19 11:54:29	ga_s2am_ard_3-2-1_50JQT_2020-08-19_final
2020-09-08 11:54:37	ga_s2am_ard_3-2-1_50KLU_2020-09-08_final
2020-09-18 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-09-18_final
2020-09-28 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-09-28_final
2020-10-08 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-10-08_final
2021-04-06 11:54:19	ga_s2am_ard_3-2-1_50JQT_2021-04-06_final
2021-04-06 11:54:30	ga_s2am_ard_3-2-1_50KLU_2021-04-06_final
2021-04-26 11:54:30	ga_s2am_ard_3-2-1_50KLU_2021-04-26_final
2021-05-16 11:54:23	ga_s2am_ard_3-2-1_50JQT_2021-05-16_final
2021-06-25 11:54:25	ga_s2am_ard_3-2-1_50JQT_2021-06-25_final
2021-08-24 11:54:25	ga_s2am_ard_3-2-1_50JQT_2021-08-24_final
2021-09-13 11:54:24	ga_s2am_ard_3-2-1_50JQT_2021-09-13_final
2021-11-02 11:54:27	ga_s2am_ard_3-2-1_50JQT_2021-11-02_final
2022-01-18 11:45:45	ga_s2am_ard_3-2-1_50JNN_2022-01-18_final
2022-04-21 11:54:27	ga_s2am_ard_3-2-1_50JQT_2022-04-21_final
2022-06-21 11:25:57	ga_s2am_ard_3-2-1_51JYG_2022-06-21_final
2022-08-10 11:25:57	ga_s2am_ard_3-2-1_51JYG_2022-08-10_final
2022-11-21 11:36:34	ga_s2am_ard_3-2-1_51HVD_2022-11-21_final.stac-item
2022-12-17 11:54:22	ga_s2am_ard_3-2-1_50JQT_2022-12-17_final.stac-item
2023-03-07 11:53:48	ga_s2am_ard_3-2-1_50KQV_2023-03-07_final.stac-item
2023-03-28 11:25:43	ga_s2am_ard_3-2-1_51JYG_2023-03-28_final.stac-item
2023-04-27 11:25:45	ga_s2am_ard_3-2-1_51JYG_2023-04-27_final.stac-item
2023-05-17 11:25:46	ga_s2am_ard_3-2-1_51JYG_2023-05-17_final.stac-item
2023-05-27 11:25:48	ga_s2am_ard_3-2-1_51JYG_2023-05-27_final.stac-item
2023-06-28 12:04:49	ga_s2am_ard_3-2-1_50JMS_2023-06-28_final.stac-item
2023-07-23 11:15:52	ga_s2am_ard_3-2-1_51JXG_2023-07-23_final.stac-item
2023-08-01 11:44:54	ga_s2am_ard_3-2-1_51JUL_2023-08-01_final.stac-item
2023-08-01 11:44:55	ga_s2am_ard_3-2-1_51JTL_2023-08-01_final.stac-item
2023-09-13 11:54:38	ga_s2am_ard_3-2-1_50KLU_2023-09-13_final.stac-item
2023-09-23 11:54:35	ga_s2am_ard_3-2-1_50KLU_2023-09-23_final.stac-item
2023-10-03 11:54:25	ga_s2am_ard_3-2-1_50JQT_2023-10-03_final.stac-item
2023-11-02 11:54:22	ga_s2am_ard_3-2-1_50JQT_2023-11-02_final.stac-item
2024-02-10 11:54:30	ga_s2am_ard_3-2-1_50KLU_2024-02-10_final.stac-item
2024-02-20 11:54:21	ga_s2am_ard_3-2-1_50JQT_2024-02-20_final.stac-item
2024-02-20 11:54:31	ga_s2am_ard_3-2-1_50KLU_2024-02-20_final.stac-item
2024-04-20 11:54:36	ga_s2am_ard_3-2-1_50KLU_2024-04-20_final.stac-item
2024-04-28 11:16:22	ga_s2am_ard_3-2-1_51JWF_2024-04-28_final.stac-item
2024-05-07 11:44:33	ga_s2am_ard_3-2-1_50KPU_2024-05-07_final.stac-item
2024-05-10 11:54:36	ga_s2am_ard_3-2-1_50KLU_2024-05-10_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

Other products

All years