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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

69 results

Time (local)	Label
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_52JBL_2016-01-11_final.stac-item
2016-07-25 09:52:36	ga_s2am_ard_3-2-1_55JDG_2016-07-25_final.stac-item
2016-08-21 09:44:28	ga_s2am_ard_3-2-1_55JGJ_2016-08-21_final.stac-item
2016-09-05 10:28:01	ga_s2am_ard_3-2-1_54KTD_2016-09-05_final.stac-item
2016-11-08 10:12:13	ga_s2am_ard_3-2-1_54KXV_2016-11-08_final.stac-item
2017-08-19 09:52:15	ga_s2am_ard_3-2-1_55KER_2017-08-19_final
2017-10-22 11:12:14	ga_s2am_ard_3-2-1_52KDE_2017-10-22_final
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50KPB_2018-04-12_final
2018-04-14 10:47:26	ga_s2am_ard_3-2-1_53JKL_2018-04-14_final
2018-04-28 10:27:10	ga_s2am_ard_3-2-1_53JQN_2018-04-28_final
2018-05-11 10:37:30	ga_s2am_ard_3-2-1_53KMP_2018-05-11_final
2018-05-23 09:41:11	ga_s2am_ard_3-2-1_55JFK_2018-05-23_final
2018-05-23 09:41:11	ga_s2am_ard_3-2-1_55JFF_2018-05-23_final
2018-05-28 10:27:09	ga_s2am_ard_3-2-1_53JPM_2018-05-28_final
2018-06-05 09:50:55	ga_s2am_ard_3-2-1_55KER_2018-06-05_final
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51KXA_2018-06-05_final
2018-08-30 11:48:24	ga_s2am_ard_3-2-1_50KNB_2018-08-30_final
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53KRQ_2018-09-25_final
2018-12-18 10:13:18	ga_s2am_ard_3-2-1_54KXV_2018-12-18_final
2018-12-25 10:03:27	ga_s2am_ard_3-2-1_55KCP_2018-12-25_final
2019-02-23 10:04:03	ga_s2am_ard_3-2-1_55JBM_2019-02-23_final
2019-03-11 12:03:51	ga_s2am_ard_3-2-1_50KLA_2019-03-11_final
2019-03-12 09:55:46	ga_s2am_ard_3-2-1_55HCE_2019-03-12_final
2019-05-10 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2019-05-10_final
2019-06-13 11:44:19	ga_s2am_ard_3-2-1_50KRU_2019-06-13_final
2019-07-01 11:04:34	ga_s2am_ard_3-2-1_52JFS_2019-07-01_final
2019-07-07 11:21:40	ga_s2am_ard_3-2-1_52LCJ_2019-07-07_final
2019-07-14 11:12:51	ga_s2am_ard_3-2-1_52KED_2019-07-14_final
2019-07-23 11:44:07	ga_s2am_ard_3-2-1_50KRV_2019-07-23_final
2019-08-22 11:44:18	ga_s2am_ard_3-2-1_51KTP_2019-08-22_final
2019-09-11 11:44:00	ga_s2am_ard_3-2-1_50KRV_2019-09-11_final
2019-11-16 12:04:44	ga_s2am_ard_3-2-1_50JKT_2019-11-16_final
2019-12-01 11:15:21	ga_s2am_ard_3-2-1_52JBP_2019-12-01_final
2019-12-10 10:05:34	ga_s2am_ard_3-2-1_54JYL_2019-12-10_final
2020-01-09 10:05:46	ga_s2am_ard_3-2-1_54HYK_2020-01-09_final
2020-01-18 10:33:58	ga_s2am_ard_3-2-1_53JQN_2020-01-18_final
2020-02-01 11:53:42	ga_s2am_ard_3-2-1_50KPA_2020-02-01_final
2020-02-17 10:33:43	ga_s2am_ard_3-2-1_53KQP_2020-02-17_final
2020-07-29 10:45:02	ga_s2am_ard_3-2-1_53JLK_2020-07-29_final
2020-09-14 10:34:08	ga_s2am_ard_3-2-1_53JQN_2020-09-14_final
2020-09-24 10:33:36	ga_s2am_ard_3-2-1_53KRQ_2020-09-24_final
2021-02-18 12:04:12	ga_s2am_ard_3-2-1_50KKV_2021-02-18_final
2021-05-12 10:33:16	ga_s2am_ard_3-2-1_54KTA_2021-05-12_final
2021-06-05 10:15:59	ga_s2am_ard_3-2-1_54HVK_2021-06-05_final
2021-07-31 10:33:20	ga_s2am_ard_3-2-1_53KRR_2021-07-31_final
2021-08-19 11:01:15	ga_s2am_ard_3-2-1_53LKE_2021-08-19_final
2021-08-20 10:33:19	ga_s2am_ard_3-2-1_54KTA_2021-08-20_final
2021-09-22 10:44:56	ga_s2am_ard_3-2-1_53JMK_2021-09-22_final
2021-09-26 10:22:34	ga_s2am_ard_3-2-1_54KVD_2021-09-26_final
2022-05-06 11:01:47	ga_s2am_ard_3-2-1_52LHH_2022-05-06_final
2022-06-07 11:42:39	ga_s2am_ard_3-2-1_51KUA_2022-06-07_final
2022-06-10 10:12:20	ga_s2am_ard_3-2-1_54KYE_2022-06-10_final
2022-07-17 11:42:43	ga_s2am_ard_3-2-1_51KUA_2022-07-17_final
2022-08-17 11:11:17	ga_s2am_ard_3-2-1_52LEL_2022-08-17_final.stac-item
2022-08-21 10:55:11	ga_s2am_ard_3-2-1_52JGQ_2022-08-21_final
2022-10-08 11:54:14	ga_s2am_ard_3-2-1_50KNV_2022-10-08_final.stac-item
2023-02-02 10:04:53	ga_s2am_ard_3-2-1_54JYP_2023-02-02_final.stac-item
2023-02-04 10:45:10	ga_s2am_ard_3-2-1_53JLJ_2023-02-04_final.stac-item
2023-03-31 09:53:46	ga_s2am_ard_3-2-1_55JEN_2023-03-31_final.stac-item
2023-04-02 10:31:30	ga_s2am_ard_3-2-1_54LUH_2023-04-02_final.stac-item
2023-06-15 10:12:58	ga_s2am_ard_3-2-1_54KYB_2023-06-15_final.stac-item
2023-10-11 11:13:35	ga_s2am_ard_3-2-1_52KCA_2023-10-11_final.stac-item
2023-10-15 10:54:57	ga_s2am_ard_3-2-1_52JGQ_2023-10-15_final.stac-item
2023-10-16 10:22:12	ga_s2am_ard_3-2-1_54KWE_2023-10-16_final.stac-item
2023-12-02 11:54:00	ga_s2am_ard_3-2-1_50KNV_2023-12-02_final.stac-item
2024-03-21 11:53:08	ga_s2am_ard_3-2-1_50KPD_2024-03-21_final.stac-item
2024-04-06 12:14:43	ga_s2am_ard_3-2-1_49JFN_2024-04-06_final.stac-item
2024-05-15 11:04:32	ga_s2am_ard_3-2-1_52JFS_2024-05-15_final.stac-item
2024-05-19 10:44:40	ga_s2am_ard_3-2-1_53JML_2024-05-19_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