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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50JMR_2015-10-28_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_50JMR_2015-12-27_final.stac-item
2015-12-28 11:36:25	ga_s2am_ard_3-2-1_50HQK_2015-12-28_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JQT_2016-02-02_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HLG_2016-03-20_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JPQ_2016-07-01_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JPR_2016-07-21_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JQT_2016-10-09_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JMR_2016-11-11_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JQT_2017-02-26_final
2017-05-04 11:38:37	ga_s2am_ard_3-2-1_50JNQ_2017-05-04_final
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JPP_2017-05-17_final
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JPP_2017-06-06_final
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JPP_2017-06-26_final
2017-06-26 11:56:32	ga_s2am_ard_3-2-1_50HMG_2017-06-26_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JPP_2017-08-05_final
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JMT_2017-08-18_final
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_50JPL_2017-09-08_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_50JQT_2017-11-13_final
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JQT_2018-02-11_final
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JMT_2018-05-05_final
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_50JMT_2018-05-15_final
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50JQS_2018-05-29_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JPP_2018-07-11_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JMS_2018-07-24_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPM_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
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JQT_2018-10-19_final
2019-02-06 11:54:30	ga_s2am_ard_3-2-1_50KLU_2019-02-06_final
2019-03-18 11:54:20	ga_s2am_ard_3-2-1_50JQT_2019-03-18_final
2019-05-07 11:54:37	ga_s2am_ard_3-2-1_50KLU_2019-05-07_final
2019-05-14 11:45:59	ga_s2am_ard_3-2-1_50JPM_2019-05-14_final
2019-05-17 11:55:30	ga_s2am_ard_3-2-1_50JPP_2019-05-17_final
2019-05-24 11:44:57	ga_s2am_ard_3-2-1_50JQR_2019-05-24_final
2019-05-30 12:04:38	ga_s2am_ard_3-2-1_50JMT_2019-05-30_final
2019-06-16 11:55:30	ga_s2am_ard_3-2-1_50JPP_2019-06-16_final
2019-07-16 11:54:38	ga_s2am_ard_3-2-1_50KLU_2019-07-16_final
2019-07-16 11:55:31	ga_s2am_ard_3-2-1_50JPP_2019-07-16_final
2019-07-26 11:54:38	ga_s2am_ard_3-2-1_50KLU_2019-07-26_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
2019-08-18 12:04:38	ga_s2am_ard_3-2-1_50JMT_2019-08-18_final
2019-08-28 12:04:37	ga_s2am_ard_3-2-1_50JMT_2019-08-28_final
2019-09-04 11:54:33	ga_s2am_ard_3-2-1_50KLU_2019-09-04_final
2019-09-07 12:04:35	ga_s2am_ard_3-2-1_50JMT_2019-09-07_final
2019-09-17 12:04:35	ga_s2am_ard_3-2-1_50JMT_2019-09-17_final
2019-10-04 11:54:35	ga_s2am_ard_3-2-1_50KLU_2019-10-04_final
2019-10-31 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-10-31_final
2019-10-31 11:47:29	ga_s2am_ard_3-2-1_50HMG_2019-10-31_final.stac-item
2019-11-03 11:54:26	ga_s2am_ard_3-2-1_50JQT_2019-11-03_final
2019-11-13 11:54:25	ga_s2am_ard_3-2-1_50JQT_2019-11-13_final
2019-11-13 11:54:35	ga_s2am_ard_3-2-1_50KLU_2019-11-13_final
2019-11-23 11:54:34	ga_s2am_ard_3-2-1_50KLU_2019-11-23_final
2020-03-28 12:14:27	ga_s2am_ard_3-2-1_49JHN_2020-03-28_final
2020-04-01 11:54:29	ga_s2am_ard_3-2-1_50KLU_2020-04-01_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
2020-06-30 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-06-30_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
2020-07-16 12:13:44	ga_s2am_ard_3-2-1_49KHS_2020-07-16_final.stac-item
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
2020-08-22 12:04:41	ga_s2am_ard_3-2-1_50JMT_2020-08-22_final
2020-10-18 11:54:29	ga_s2am_ard_3-2-1_50JQT_2020-10-18_final
2020-10-28 11:54:28	ga_s2am_ard_3-2-1_50JQT_2020-10-28_final
2020-10-28 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-10-28_final
2020-11-07 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-11-07_final
2020-11-24 11:45:57	ga_s2am_ard_3-2-1_50JPM_2020-11-24_final
2020-11-27 11:54:24	ga_s2am_ard_3-2-1_50JQT_2020-11-27_final
2021-04-30 11:34:41	ga_s2am_ard_3-2-1_50JRS_2021-04-30_final
2021-09-13 11:54:24	ga_s2am_ard_3-2-1_50JQT_2021-09-13_final
2021-12-12 11:54:22	ga_s2am_ard_3-2-1_50JQT_2021-12-12_final
2022-01-11 11:54:24	ga_s2am_ard_3-2-1_50JQT_2022-01-11_final
2022-01-18 11:45:45	ga_s2am_ard_3-2-1_50JNN_2022-01-18_final
2022-02-20 11:54:25	ga_s2am_ard_3-2-1_50JQT_2022-02-20_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
2022-05-14 12:04:37	ga_s2am_ard_3-2-1_49JHN_2022-05-14_final
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_49JHN_2022-05-24_final
2022-10-18 11:54:26	ga_s2am_ard_3-2-1_50JQT_2022-10-18_final.stac-item
2022-10-25 11:45:48	ga_s2am_ard_3-2-1_50JNN_2022-10-25_final.stac-item
2022-11-07 11:54:27	ga_s2am_ard_3-2-1_50JQT_2022-11-07_final.stac-item
2022-12-17 11:54:22	ga_s2am_ard_3-2-1_50JQT_2022-12-17_final.stac-item
2023-01-06 11:54:22	ga_s2am_ard_3-2-1_50JQT_2023-01-06_final.stac-item
2023-02-05 11:54:22	ga_s2am_ard_3-2-1_50JQT_2023-02-05_final.stac-item
2023-03-17 11:54:31	ga_s2am_ard_3-2-1_50KLU_2023-03-17_final.stac-item
2023-03-27 11:54:31	ga_s2am_ard_3-2-1_50KLU_2023-03-27_final.stac-item
2023-04-16 11:54:33	ga_s2am_ard_3-2-1_50KLU_2023-04-16_final.stac-item
2023-04-26 11:54:33	ga_s2am_ard_3-2-1_50KLU_2023-04-26_final.stac-item
2023-05-06 11:54:33	ga_s2am_ard_3-2-1_50KLU_2023-05-06_final.stac-item
2023-05-16 11:54:34	ga_s2am_ard_3-2-1_50KLU_2023-05-16_final.stac-item
2023-06-28 12:04:49	ga_s2am_ard_3-2-1_50JMS_2023-06-28_final.stac-item
2023-07-25 11:55:31	ga_s2am_ard_3-2-1_50JPP_2023-07-25_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
2023-11-12 11:54:22	ga_s2am_ard_3-2-1_50JQT_2023-11-12_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