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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_51JUL_2015-12-21_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JQT_2016-01-03_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JPP_2016-02-02_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JPP_2016-06-11_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JPP_2016-08-30_final.stac-item
2017-03-05 11:37:45	ga_s2am_ard_3-2-1_50JPT_2017-03-05_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_51JTG_2017-03-05_final
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JQT_2017-03-18_final
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_50JMT_2017-04-20_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JPP_2017-05-17_final
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50KLU_2017-05-17_final
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JMT_2017-05-30_final
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_51JUL_2017-06-13_final
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JMT_2017-06-19_final
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JPP_2017-06-26_final
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JMT_2017-07-09_final
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50KLU_2017-07-16_final
2017-09-14 11:51:53	ga_s2am_ard_3-2-1_50KLU_2017-09-14_final
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JMT_2017-09-27_final
2017-11-13 11:49:19	ga_s2am_ard_3-2-1_50KLU_2017-11-13_final
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KLU_2018-01-12_final
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HMG_2018-02-11_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50KPU_2018-03-20_final
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51JUL_2018-04-29_final
2018-05-09 11:34:47	ga_s2am_ard_3-2-1_51JUL_2018-05-09_final
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_51JUL_2018-05-09_final
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_50JMT_2018-05-15_final
2018-05-29 11:39:24	ga_s2am_ard_3-2-1_51JUL_2018-05-29_final
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_51JTH_2018-07-08_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JPP_2018-07-11_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_51JUL_2018-07-18_final
2018-08-11 11:19:45	ga_s2am_ard_3-2-1_51JUG_2018-08-11_final
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50KMV_2018-08-13_final
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_51JUL_2018-08-17_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50KPU_2018-08-27_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_51JUL_2018-08-27_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50KLU_2018-09-19_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50KLU_2018-09-29_final
2018-11-18 11:54:27	ga_s2am_ard_3-2-1_50KLU_2018-11-18_final
2018-12-28 11:54:26	ga_s2am_ard_3-2-1_50KLU_2018-12-28_final
2019-02-16 11:54:20	ga_s2am_ard_3-2-1_50JQT_2019-02-16_final
2019-03-18 11:54:23	ga_s2am_ard_3-2-1_50KMU_2019-03-18_final
2019-05-17 11:54:37	ga_s2am_ard_3-2-1_50KLU_2019-05-17_final
2019-05-30 12:04:38	ga_s2am_ard_3-2-1_50JMT_2019-05-30_final
2019-06-19 12:04:39	ga_s2am_ard_3-2-1_50JMT_2019-06-19_final
2019-07-16 11:55:31	ga_s2am_ard_3-2-1_50JPP_2019-07-16_final
2019-07-19 12:04:41	ga_s2am_ard_3-2-1_50JMT_2019-07-19_final
2019-07-29 12:04:40	ga_s2am_ard_3-2-1_50JMT_2019-07-29_final
2019-08-08 12:04:40	ga_s2am_ard_3-2-1_50JMT_2019-08-08_final
2019-08-25 11:54:13	ga_s2am_ard_3-2-1_50KMV_2019-08-25_final
2019-09-04 11:54:33	ga_s2am_ard_3-2-1_50KLU_2019-09-04_final
2019-09-17 12:04:35	ga_s2am_ard_3-2-1_50JMT_2019-09-17_final
2019-11-23 11:54:34	ga_s2am_ard_3-2-1_50KLU_2019-11-23_final
2019-12-09 12:14:28	ga_s2am_ard_3-2-1_49JHN_2019-12-09_final
2020-02-07 12:14:23	ga_s2am_ard_3-2-1_49JHN_2020-02-07_final
2020-02-11 11:54:16	ga_s2am_ard_3-2-1_50JQT_2020-02-11_final
2020-05-01 11:54:25	ga_s2am_ard_3-2-1_50KMU_2020-05-01_final
2020-05-14 12:04:40	ga_s2am_ard_3-2-1_50JMT_2020-05-14_final
2020-05-21 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-05-21_final
2020-06-03 12:04:42	ga_s2am_ard_3-2-1_50JMT_2020-06-03_final
2020-06-10 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-06-10_final
2020-06-20 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-06-20_final
2020-07-13 12:04:40	ga_s2am_ard_3-2-1_50JMT_2020-07-13_final
2020-07-14 11:34:48	ga_s2am_ard_3-2-1_50JRS_2020-07-14_final
2020-07-14 11:34:48	ga_s2am_ard_3-2-1_51JTM_2020-07-14_final
2020-07-23 12:04:41	ga_s2am_ard_3-2-1_50JMT_2020-07-23_final
2020-08-02 12:04:41	ga_s2am_ard_3-2-1_50JMT_2020-08-02_final
2020-08-19 11:54:32	ga_s2am_ard_3-2-1_50KMU_2020-08-19_final
2020-08-29 11:54:31	ga_s2am_ard_3-2-1_50KMU_2020-08-29_final
2020-10-28 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-10-28_final
2020-11-27 11:54:24	ga_s2am_ard_3-2-1_50JQT_2020-11-27_final
2021-01-26 11:54:34	ga_s2am_ard_3-2-1_50KLU_2021-01-26_final
2021-01-30 11:36:29	ga_s2am_ard_3-2-1_51HVE_2021-01-30_final
2021-11-02 11:54:27	ga_s2am_ard_3-2-1_50JQT_2021-11-02_final
2021-12-12 11:54:22	ga_s2am_ard_3-2-1_50JQT_2021-12-12_final
2021-12-22 11:54:24	ga_s2am_ard_3-2-1_50JQT_2021-12-22_final
2022-02-10 11:54:32	ga_s2am_ard_3-2-1_50KLU_2022-02-10_final
2022-03-02 11:54:37	ga_s2am_ard_3-2-1_50KLU_2022-03-02_final
2022-04-11 11:54:35	ga_s2am_ard_3-2-1_50KLU_2022-04-11_final
2023-02-15 11:54:30	ga_s2am_ard_3-2-1_50KLU_2023-02-15_final.stac-item
2023-03-27 11:54:31	ga_s2am_ard_3-2-1_50KLU_2023-03-27_final.stac-item
2023-04-10 11:36:33	ga_s2am_ard_3-2-1_51HVD_2023-04-10_final.stac-item
2023-05-09 12:04:27	ga_s2am_ard_3-2-1_50KMU_2023-05-09_final.stac-item
2023-05-16 11:54:34	ga_s2am_ard_3-2-1_50KLU_2023-05-16_final.stac-item
2023-05-27 11:26:03	ga_s2am_ard_3-2-1_51JUG_2023-05-27_final.stac-item
2023-07-15 11:55:31	ga_s2am_ard_3-2-1_50JPP_2023-07-15_final.stac-item
2023-07-25 11:54:38	ga_s2am_ard_3-2-1_50KLU_2023-07-25_final.stac-item
2023-08-04 11:54:28	ga_s2am_ard_3-2-1_50JQT_2023-08-04_final.stac-item
2023-08-24 11:54:32	ga_s2am_ard_3-2-1_50KMU_2023-08-24_final.stac-item
2023-08-24 11:55:32	ga_s2am_ard_3-2-1_50JPP_2023-08-24_final.stac-item
2023-08-27 12:04:41	ga_s2am_ard_3-2-1_50JMT_2023-08-27_final.stac-item
2023-09-27 11:36:36	ga_s2am_ard_3-2-1_51HVD_2023-09-27_final.stac-item
2023-10-13 11:54:21	ga_s2am_ard_3-2-1_50JQT_2023-10-13_final.stac-item
2023-10-13 11:54:31	ga_s2am_ard_3-2-1_50KLU_2023-10-13_final.stac-item
2023-10-23 11:54:33	ga_s2am_ard_3-2-1_50KLU_2023-10-23_final.stac-item
2023-11-02 11:54:32	ga_s2am_ard_3-2-1_50KLU_2023-11-02_final.stac-item
2024-01-31 11:54:29	ga_s2am_ard_3-2-1_50KLU_2024-01-31_final.stac-item
2024-02-10 11:55:11	ga_s2am_ard_3-2-1_50JMQ_2024-02-10_final.stac-item
2024-03-01 11:54:33	ga_s2am_ard_3-2-1_50KLU_2024-03-01_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