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
2015-10-23 11:08:22	ga_s2am_ard_3-2-1_52KEB_2015-10-23_final.stac-item
2015-11-13 10:42:13	ga_s2am_ard_3-2-1_53KPT_2015-11-13_final.stac-item
2015-11-22 11:12:12	ga_s2am_ard_3-2-1_52KCU_2015-11-22_final.stac-item
2015-11-23 10:42:01	ga_s2am_ard_3-2-1_53KNU_2015-11-23_final.stac-item
2015-11-29 10:57:18	ga_s2am_ard_3-2-1_52KFD_2015-11-29_final.stac-item
2015-11-29 10:57:18	ga_s2am_ard_3-2-1_52KFE_2015-11-29_final.stac-item
2016-01-12 10:44:10	ga_s2am_ard_3-2-1_53KPQ_2016-01-12_final.stac-item
2016-01-18 11:02:07	ga_s2am_ard_3-2-1_52KGV_2016-01-18_final.stac-item
2016-01-25 10:54:07	ga_s2am_ard_3-2-1_53JLN_2016-01-25_final.stac-item
2016-02-04 10:53:14	ga_s2am_ard_3-2-1_53JLN_2016-02-04_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51KWQ_2016-07-15_final.stac-item
2016-07-26 11:02:15	ga_s2am_ard_3-2-1_52KFD_2016-07-26_final.stac-item
2016-08-31 11:22:38	ga_s2am_ard_3-2-1_51KXQ_2016-08-31_final.stac-item
2016-12-03 11:00:41	ga_s2am_ard_3-2-1_52KEB_2016-12-03_final.stac-item
2016-12-06 11:07:09	ga_s2am_ard_3-2-1_52KDE_2016-12-06_final.stac-item
2016-12-06 11:07:09	ga_s2am_ard_3-2-1_52LGH_2016-12-06_final.stac-item
2017-01-18 11:19:51	ga_s2am_ard_3-2-1_52LBH_2017-01-18_final
2017-03-23 11:02:22	ga_s2am_ard_3-2-1_52KEB_2017-03-23_final
2017-05-12 11:03:02	ga_s2am_ard_3-2-1_52KEC_2017-05-12_final
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKB_2017-11-19_final
2017-12-08 11:02:31	ga_s2am_ard_3-2-1_52KFB_2017-12-08_final
2017-12-08 11:02:31	ga_s2am_ard_3-2-1_52KHC_2017-12-08_final
2017-12-17 11:26:50	ga_s2am_ard_3-2-1_51KVB_2017-12-17_final
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51KWB_2018-02-25_final
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_51KXQ_2018-10-03_final
2019-01-13 10:32:00	ga_s2am_ard_3-2-1_53KRA_2019-01-13_final
2019-01-26 10:42:36	ga_s2am_ard_3-2-1_53KNU_2019-01-26_final
2019-01-26 10:42:47	ga_s2am_ard_3-2-1_53KPT_2019-01-26_final
2019-01-30 10:26:33	ga_s2am_ard_3-2-1_53HPC_2019-01-30_final
2019-02-14 11:11:56	ga_s2am_ard_3-2-1_52KFG_2019-02-14_final
2019-02-14 11:12:57	ga_s2am_ard_3-2-1_52KEC_2019-02-14_final
2019-02-15 10:42:09	ga_s2am_ard_3-2-1_53KRV_2019-02-15_final
2019-03-13 11:02:14	ga_s2am_ard_3-2-1_52KFF_2019-03-13_final
2019-04-15 11:12:55	ga_s2am_ard_3-2-1_52KCD_2019-04-15_final
2019-04-19 10:53:35	ga_s2am_ard_3-2-1_52KGA_2019-04-19_final
2019-06-30 11:34:07	ga_s2am_ard_3-2-1_51KUQ_2019-06-30_final
2019-08-23 11:13:06	ga_s2am_ard_3-2-1_52KDC_2019-08-23_final
2019-08-29 11:34:04	ga_s2am_ard_3-2-1_51KUQ_2019-08-29_final
2019-09-23 10:43:02	ga_s2am_ard_3-2-1_53KQS_2019-09-23_final
2019-10-11 11:43:32	ga_s2am_ard_3-2-1_51KUS_2019-10-11_final
2019-11-21 11:12:29	ga_s2am_ard_3-2-1_52KFE_2019-11-21_final
2019-12-08 11:02:51	ga_s2am_ard_3-2-1_53KKT_2019-12-08_final
2020-01-29 11:42:06	ga_s2am_ard_3-2-1_51KVB_2020-01-29_final
2020-02-19 11:12:08	ga_s2am_ard_3-2-1_52KFF_2020-02-19_final
2020-03-25 12:03:23	ga_s2am_ard_3-2-1_50KLC_2020-03-25_final
2020-05-23 10:52:18	ga_s2am_ard_3-2-1_53KLA_2020-05-23_final
2020-07-31 11:24:04	ga_s2am_ard_3-2-1_51KZP_2020-07-31_final
2020-09-22 11:34:08	ga_s2am_ard_3-2-1_51KUQ_2020-09-22_final
2020-10-02 11:33:58	ga_s2am_ard_3-2-1_51KUR_2020-10-02_final
2020-10-04 12:15:05	ga_s2am_ard_3-2-1_49JFM_2020-10-04_final
2020-10-07 10:42:38	ga_s2am_ard_3-2-1_53KQU_2020-10-07_final
2020-12-02 11:02:18	ga_s2am_ard_3-2-1_52KFF_2020-12-02_final
2021-03-25 11:13:06	ga_s2am_ard_3-2-1_52KCC_2021-03-25_final
2021-10-10 11:43:34	ga_s2am_ard_3-2-1_51KUS_2021-10-10_final
2021-10-11 11:14:14	ga_s2am_ard_3-2-1_51KZP_2021-10-11_final
2021-10-22 10:42:37	ga_s2am_ard_3-2-1_53KQU_2021-10-22_final
2021-12-24 10:54:49	ga_s2am_ard_3-2-1_52JFR_2021-12-24_final
2022-01-30 10:44:35	ga_s2am_ard_3-2-1_53JNL_2022-01-30_final
2022-02-28 11:11:19	ga_s2am_ard_3-2-1_52LFK_2022-02-28_final
2022-03-01 10:45:45	ga_s2am_ard_3-2-1_53JNF_2022-03-01_final
2022-03-26 11:33:18	ga_s2am_ard_3-2-1_51KVT_2022-03-26_final
2022-05-06 11:03:50	ga_s2am_ard_3-2-1_52KFV_2022-05-06_final
2022-05-13 10:54:51	ga_s2am_ard_3-2-1_52JFR_2022-05-13_final
2022-05-16 11:03:24	ga_s2am_ard_3-2-1_52KEB_2022-05-16_final
2022-05-20 10:46:04	ga_s2am_ard_3-2-1_53JKF_2022-05-20_final
2022-06-26 10:33:24	ga_s2am_ard_3-2-1_53KPS_2022-06-26_final
2022-06-27 11:43:27	ga_s2am_ard_3-2-1_51KUT_2022-06-27_final
2022-07-14 11:32:32	ga_s2am_ard_3-2-1_51KVB_2022-07-14_final
2022-08-11 10:54:59	ga_s2am_ard_3-2-1_52JFR_2022-08-11_final
2022-08-13 11:37:04	ga_s2am_ard_3-2-1_50HPJ_2022-08-13_final
2022-08-23 11:34:12	ga_s2am_ard_3-2-1_51KVQ_2022-08-23_final.stac-item
2022-10-04 10:34:43	ga_s2am_ard_3-2-1_53JPL_2022-10-04_final.stac-item
2022-10-27 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-10-27_final.stac-item
2022-12-19 10:55:38	ga_s2am_ard_3-2-1_53JKG_2022-12-19_final.stac-item
2023-01-12 10:33:36	ga_s2am_ard_3-2-1_53KPQ_2023-01-12_final.stac-item
2023-02-10 11:01:27	ga_s2am_ard_3-2-1_52LHJ_2023-02-10_final.stac-item
2023-03-12 11:02:48	ga_s2am_ard_3-2-1_52KED_2023-03-12_final.stac-item
2023-04-26 11:55:27	ga_s2am_ard_3-2-1_50JLQ_2023-04-26_final.stac-item
2023-05-02 10:33:24	ga_s2am_ard_3-2-1_53KPR_2023-05-02_final.stac-item
2023-05-03 11:42:09	ga_s2am_ard_3-2-1_51KWB_2023-05-03_final.stac-item
2023-05-14 11:13:54	ga_s2am_ard_3-2-1_51KZQ_2023-05-14_final.stac-item
2023-06-07 10:55:35	ga_s2am_ard_3-2-1_52JFN_2023-06-07_final.stac-item
2023-07-17 10:53:55	ga_s2am_ard_3-2-1_52KGV_2023-07-17_final.stac-item
2023-08-06 10:54:52	ga_s2am_ard_3-2-1_52JFR_2023-08-06_final.stac-item
2023-08-11 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-08-11_final.stac-item
2023-08-12 11:13:27	ga_s2am_ard_3-2-1_52KCB_2023-08-12_final.stac-item
2023-09-28 11:03:40	ga_s2am_ard_3-2-1_52KEA_2023-09-28_final.stac-item
2023-10-21 11:13:15	ga_s2am_ard_3-2-1_52KEB_2023-10-21_final.stac-item
2023-10-24 11:23:03	ga_s2am_ard_3-2-1_52KCC_2023-10-24_final.stac-item
2023-11-11 10:45:41	ga_s2am_ard_3-2-1_53JNF_2023-11-11_final.stac-item
2023-11-24 10:52:40	ga_s2am_ard_3-2-1_52KHD_2023-11-24_final.stac-item
2023-11-27 11:02:34	ga_s2am_ard_3-2-1_52KHD_2023-11-27_final.stac-item
2023-12-07 11:01:54	ga_s2am_ard_3-2-1_52KGG_2023-12-07_final.stac-item
2023-12-08 10:32:42	ga_s2am_ard_3-2-1_53KRT_2023-12-08_final.stac-item
2023-12-27 11:04:32	ga_s2am_ard_3-2-1_52JGR_2023-12-27_final.stac-item
2024-01-03 10:52:56	ga_s2am_ard_3-2-1_52KHC_2024-01-03_final.stac-item
2024-01-06 11:02:36	ga_s2am_ard_3-2-1_52KHD_2024-01-06_final.stac-item
2024-02-25 11:02:46	ga_s2am_ard_3-2-1_52KFD_2024-02-25_final.stac-item
2024-03-02 11:25:57	ga_s2am_ard_3-2-1_51JWG_2024-03-02_final.stac-item
2024-05-12 10:53:02	ga_s2am_ard_3-2-1_53KKT_2024-05-12_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

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