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_50JLS_2015-11-27_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JMQ_2015-12-04_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_49JHN_2015-12-07_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_49JHN_2015-12-27_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_50JLR_2016-02-05_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JLR_2016-02-15_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JMQ_2016-06-11_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JMR_2016-07-14_final.stac-item
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_50JMR_2016-09-22_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JLR_2016-11-21_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50JLR_2016-12-31_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KHS_2017-02-22_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JMQ_2017-03-18_final
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JMR_2017-06-06_final
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_50JLR_2017-06-09_final
2017-06-10 11:36:05	ga_s2am_ard_3-2-1_50HQK_2017-06-10_final
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JLR_2017-06-19_final
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_50JLR_2017-06-29_final
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JHN_2017-10-27_final
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50JMR_2018-01-12_final
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNG_2018-02-18_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JMR_2018-03-13_final
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KHS_2018-04-08_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JMR_2018-04-12_final
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JMQ_2018-05-12_final
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JMR_2018-06-14_final
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JMR_2018-06-24_final
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50JMR_2018-08-03_final
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JLT_2018-08-20_final
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JMR_2018-08-23_final
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HQH_2018-09-06_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JMQ_2018-09-19_final
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JMR_2018-10-19_final
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JMR_2018-10-29_final
2018-11-18 11:55:03	ga_s2am_ard_3-2-1_50JMR_2018-11-18_final
2018-11-28 11:55:01	ga_s2am_ard_3-2-1_50JMR_2018-11-28_final
2018-12-08 11:55:01	ga_s2am_ard_3-2-1_50JMR_2018-12-08_final
2018-12-18 11:55:01	ga_s2am_ard_3-2-1_50JMR_2018-12-18_final
2018-12-28 11:55:03	ga_s2am_ard_3-2-1_50JMR_2018-12-28_final
2019-01-27 11:54:41	ga_s2am_ard_3-2-1_50JLT_2019-01-27_final
2019-02-06 11:54:41	ga_s2am_ard_3-2-1_50JLT_2019-02-06_final
2019-02-16 11:54:43	ga_s2am_ard_3-2-1_50JLT_2019-02-16_final
2019-03-01 12:05:00	ga_s2am_ard_3-2-1_50JLR_2019-03-01_final
2019-03-15 11:47:10	ga_s2am_ard_3-2-1_50HNG_2019-03-15_final.stac-item
2019-03-18 11:55:07	ga_s2am_ard_3-2-1_50JMR_2019-03-18_final
2019-05-07 11:55:28	ga_s2am_ard_3-2-1_50JMQ_2019-05-07_final
2019-06-16 11:55:27	ga_s2am_ard_3-2-1_50JMQ_2019-06-16_final
2019-06-29 12:05:03	ga_s2am_ard_3-2-1_50JMR_2019-06-29_final
2019-08-01 12:14:21	ga_s2am_ard_3-2-1_49KHP_2019-08-01_final
2019-09-17 12:04:48	ga_s2am_ard_3-2-1_50JMS_2019-09-17_final
2019-09-27 12:05:00	ga_s2am_ard_3-2-1_50JMR_2019-09-27_final
2019-11-23 11:55:10	ga_s2am_ard_3-2-1_50JMR_2019-11-23_final
2019-12-13 11:54:40	ga_s2am_ard_3-2-1_50JLT_2019-12-13_final
2019-12-29 12:14:26	ga_s2am_ard_3-2-1_49JHN_2019-12-29_final
2020-01-05 12:04:53	ga_s2am_ard_3-2-1_50JMR_2020-01-05_final
2020-04-21 11:55:10	ga_s2am_ard_3-2-1_50JMR_2020-04-21_final
2020-05-01 11:54:47	ga_s2am_ard_3-2-1_50JLT_2020-05-01_final
2020-05-11 11:55:14	ga_s2am_ard_3-2-1_50JMR_2020-05-11_final
2020-05-28 11:46:09	ga_s2am_ard_3-2-1_50JMM_2020-05-28_final
2020-06-13 12:04:55	ga_s2am_ard_3-2-1_50JMS_2020-06-13_final
2020-06-20 11:55:15	ga_s2am_ard_3-2-1_50JMR_2020-06-20_final
2020-07-20 11:55:15	ga_s2am_ard_3-2-1_50JMR_2020-07-20_final
2020-07-30 11:55:15	ga_s2am_ard_3-2-1_50JMR_2020-07-30_final
2021-01-06 11:55:24	ga_s2am_ard_3-2-1_50JMQ_2021-01-06_final
2021-04-10 11:37:13	ga_s2am_ard_3-2-1_50HQG_2021-04-10_final.stac-item
2021-07-08 12:05:01	ga_s2am_ard_3-2-1_50JMR_2021-07-08_final
2021-07-18 12:05:02	ga_s2am_ard_3-2-1_50JMR_2021-07-18_final
2021-08-27 12:05:00	ga_s2am_ard_3-2-1_50JMR_2021-08-27_final
2021-09-23 11:55:27	ga_s2am_ard_3-2-1_50JMQ_2021-09-23_final
2021-10-07 11:37:17	ga_s2am_ard_3-2-1_50HPG_2021-10-07_final.stac-item
2021-10-23 11:55:29	ga_s2am_ard_3-2-1_50JMQ_2021-10-23_final
2021-12-16 11:37:12	ga_s2am_ard_3-2-1_50HPG_2021-12-16_final.stac-item
2022-01-31 11:54:44	ga_s2am_ard_3-2-1_50JLT_2022-01-31_final
2022-02-10 11:54:43	ga_s2am_ard_3-2-1_50JLT_2022-02-10_final
2022-04-11 11:54:46	ga_s2am_ard_3-2-1_50JLT_2022-04-11_final
2022-05-04 12:05:03	ga_s2am_ard_3-2-1_50JMR_2022-05-04_final
2022-06-03 12:05:06	ga_s2am_ard_3-2-1_50JMR_2022-06-03_final
2022-06-30 11:54:57	ga_s2am_ard_3-2-1_50JLT_2022-06-30_final
2022-07-03 12:05:11	ga_s2am_ard_3-2-1_50JMR_2022-07-03_final
2023-01-16 11:55:20	ga_s2am_ard_3-2-1_50JMQ_2023-01-16_final.stac-item
2023-02-08 12:04:47	ga_s2am_ard_3-2-1_50JMS_2023-02-08_final.stac-item
2023-02-18 12:05:12	ga_s2am_ard_3-2-1_50JLR_2023-02-18_final.stac-item
2023-02-25 11:55:07	ga_s2am_ard_3-2-1_50JMR_2023-02-25_final.stac-item
2023-03-17 11:55:07	ga_s2am_ard_3-2-1_50JMR_2023-03-17_final.stac-item
2023-03-20 12:05:06	ga_s2am_ard_3-2-1_50JLR_2023-03-20_final.stac-item
2023-04-09 12:04:49	ga_s2am_ard_3-2-1_50JMS_2023-04-09_final.stac-item
2023-04-19 12:04:47	ga_s2am_ard_3-2-1_50JMS_2023-04-19_final.stac-item
2023-04-19 12:04:57	ga_s2am_ard_3-2-1_50JMR_2023-04-19_final.stac-item
2023-06-28 12:04:54	ga_s2am_ard_3-2-1_50JMS_2023-06-28_final.stac-item
2023-07-15 11:55:29	ga_s2am_ard_3-2-1_50JMQ_2023-07-15_final.stac-item
2023-08-24 11:54:50	ga_s2am_ard_3-2-1_50JLT_2023-08-24_final.stac-item
2023-08-24 11:55:30	ga_s2am_ard_3-2-1_50JMQ_2023-08-24_final.stac-item
2023-08-30 12:14:51	ga_s2am_ard_3-2-1_49JFN_2023-08-30_final.stac-item
2023-10-23 11:55:24	ga_s2am_ard_3-2-1_50JMQ_2023-10-23_final.stac-item
2023-11-02 11:57:19	ga_s2am_ard_3-2-1_50HMG_2023-11-02_final.stac-item
2023-11-12 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2023-11-12_nrt.stac-item
2024-02-20 11:55:07	ga_s2am_ard_3-2-1_50JMR_2024-02-20_final.stac-item
2024-02-23 12:04:43	ga_s2am_ard_3-2-1_50JLS_2024-02-23_final.stac-item
2024-03-08 11:47:25	ga_s2am_ard_3-2-1_50HMG_2024-03-08_final.stac-item
2024-03-21 11:55:11	ga_s2am_ard_3-2-1_50JMR_2024-03-21_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