Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2018-11-23 11:05:37	ga_s2am_ard_3-2-1_52JEM_2018-11-23_final.stac-item
2018-11-23 11:05:41	ga_s2am_ard_3-2-1_52JDM_2018-11-23_final.stac-item
2018-11-23 11:05:45	ga_s2am_ard_3-2-1_52JCM_2018-11-23_final.stac-item
2018-11-23 11:05:51	ga_s2am_ard_3-2-1_52JBM_2018-11-23_final.stac-item
2018-11-23 11:05:59	ga_s2am_ard_3-2-1_52JCL_2018-11-23_final.stac-item
2018-11-23 11:06:03	ga_s2am_ard_3-2-1_52JBL_2018-11-23_final.stac-item
2018-11-26 11:15:39	ga_s2am_ard_3-2-1_52JCM_2018-11-26_final.stac-item
2018-11-26 11:15:43	ga_s2am_ard_3-2-1_52JBM_2018-11-26_final.stac-item
2018-11-26 11:15:46	ga_s2am_ard_3-2-1_51JYG_2018-11-26_final.stac-item
2018-11-26 11:15:49	ga_s2am_ard_3-2-1_51JXG_2018-11-26_final.stac-item
2018-11-26 11:15:54	ga_s2am_ard_3-2-1_52JCL_2018-11-26_final.stac-item
2018-11-26 11:15:57	ga_s2am_ard_3-2-1_52JBL_2018-11-26_final.stac-item
2018-11-26 11:16:00	ga_s2am_ard_3-2-1_51JYF_2018-11-26_final.stac-item
2018-11-26 11:16:04	ga_s2am_ard_3-2-1_51JXF_2018-11-26_final.stac-item
2018-11-27 10:45:24	ga_s2am_ard_3-2-1_53JNG_2018-11-27_final.stac-item
2018-11-27 10:45:28	ga_s2am_ard_3-2-1_53JMG_2018-11-27_final.stac-item
2018-11-27 10:45:32	ga_s2am_ard_3-2-1_53JLG_2018-11-27_final.stac-item
2018-11-27 10:45:35	ga_s2am_ard_3-2-1_53JKG_2018-11-27_final.stac-item
2018-11-27 10:45:39	ga_s2am_ard_3-2-1_52JGM_2018-11-27_final.stac-item
2018-11-27 10:45:47	ga_s2am_ard_3-2-1_53JLF_2018-11-27_final.stac-item
2018-11-27 10:45:50	ga_s2am_ard_3-2-1_53JKF_2018-11-27_final.stac-item
2018-11-29 11:25:44	ga_s2am_ard_3-2-1_51JXG_2018-11-29_final.stac-item
2018-11-29 11:25:48	ga_s2am_ard_3-2-1_51JWG_2018-11-29_final.stac-item
2018-11-29 11:25:51	ga_s2am_ard_3-2-1_51JVG_2018-11-29_final.stac-item
2018-11-29 11:25:57	ga_s2am_ard_3-2-1_51JUG_2018-11-29_final.stac-item
2018-11-29 11:25:59	ga_s2am_ard_3-2-1_51JXF_2018-11-29_final.stac-item
2018-12-03 11:05:36	ga_s2am_ard_3-2-1_52JEM_2018-12-03_final.stac-item
2018-12-03 11:05:40	ga_s2am_ard_3-2-1_52JDM_2018-12-03_final.stac-item
2018-12-03 11:05:43	ga_s2am_ard_3-2-1_52JCM_2018-12-03_final.stac-item
2018-12-03 11:05:50	ga_s2am_ard_3-2-1_52JBM_2018-12-03_final.stac-item
2018-12-03 11:05:58	ga_s2am_ard_3-2-1_52JCL_2018-12-03_final.stac-item
2018-12-03 11:06:01	ga_s2am_ard_3-2-1_52JBL_2018-12-03_final.stac-item
2018-12-11 12:05:56	ga_s2am_ard_3-2-1_50JLM_2018-12-11_final.stac-item
2018-12-11 12:06:01	ga_s2am_ard_3-2-1_50JKM_2018-12-11_final.stac-item
2018-12-11 12:06:06	ga_s2am_ard_3-2-1_50JLL_2018-12-11_final.stac-item
2018-12-12 09:55:06	ga_s2am_ard_3-2-1_55JEG_2018-12-12_final.stac-item
2018-12-12 09:55:09	ga_s2am_ard_3-2-1_55JDG_2018-12-12_final.stac-item
2018-12-12 09:55:13	ga_s2am_ard_3-2-1_55JCG_2018-12-12_final.stac-item
2018-12-12 09:55:16	ga_s2am_ard_3-2-1_55JBG_2018-12-12_final.stac-item
2018-12-12 09:55:27	ga_s2am_ard_3-2-1_55JCF_2018-12-12_final.stac-item
2018-12-12 09:55:30	ga_s2am_ard_3-2-1_55JBF_2018-12-12_final.stac-item
2022-10-07 09:05:02	ga_s2am_ard_3-2-1_57JWG_2022-10-06_interim
2022-10-07 09:05:06	ga_s2am_ard_3-2-1_57JVG_2022-10-06_interim
2022-10-07 10:45:38	ga_s2am_ard_3-2-1_53JNG_2022-10-07_final.stac-item
2022-10-07 10:45:43	ga_s2am_ard_3-2-1_53JMG_2022-10-07_final.stac-item
2022-10-07 10:45:47	ga_s2am_ard_3-2-1_53JLG_2022-10-07_final.stac-item
2022-10-07 10:45:50	ga_s2am_ard_3-2-1_53JKG_2022-10-07_final.stac-item
2022-10-07 10:45:54	ga_s2am_ard_3-2-1_52JGM_2022-10-07_final.stac-item
2022-10-07 10:46:02	ga_s2am_ard_3-2-1_53JLF_2022-10-07_final.stac-item
2022-10-07 10:46:05	ga_s2am_ard_3-2-1_53JKF_2022-10-07_final.stac-item
2022-10-07 10:46:07	ga_s2am_ard_3-2-1_52JGL_2022-10-07_final.stac-item
2022-10-08 10:15:29	ga_s2am_ard_3-2-1_54JXM_2022-10-08_final.stac-item
2022-10-08 10:15:32	ga_s2am_ard_3-2-1_54JWM_2022-10-08_final.stac-item
2022-10-08 10:15:36	ga_s2am_ard_3-2-1_54JVM_2022-10-08_final.stac-item
2022-10-08 10:15:39	ga_s2am_ard_3-2-1_54JUM_2022-10-08_final.stac-item
2022-10-14 10:35:35	ga_s2am_ard_3-2-1_53JQG_2022-10-14_final.stac-item
2022-10-14 10:35:39	ga_s2am_ard_3-2-1_53JPG_2022-10-14_final.stac-item
2022-10-14 10:35:42	ga_s2am_ard_3-2-1_53JNG_2022-10-14_final.stac-item
2022-10-14 10:35:45	ga_s2am_ard_3-2-1_53JMG_2022-10-14_final.stac-item
2022-10-14 10:35:49	ga_s2am_ard_3-2-1_53JQF_2022-10-14_final.stac-item
2022-10-14 10:35:53	ga_s2am_ard_3-2-1_53JPF_2022-10-14_final.stac-item
2022-10-17 09:04:59	ga_s2am_ard_3-2-1_57JWG_2022-10-16_interim
2022-10-17 09:05:02	ga_s2am_ard_3-2-1_57JVG_2022-10-16_interim
2022-10-17 10:45:35	ga_s2am_ard_3-2-1_53JNG_2022-10-17_final.stac-item
2022-10-20 10:55:41	ga_s2am_ard_3-2-1_53JKG_2022-10-20_final.stac-item
2022-10-20 10:55:44	ga_s2am_ard_3-2-1_52JGM_2022-10-20_final.stac-item
2022-10-20 10:55:47	ga_s2am_ard_3-2-1_52JFM_2022-10-20_final.stac-item
2022-10-20 10:55:51	ga_s2am_ard_3-2-1_52JEM_2022-10-20_final.stac-item
2022-10-20 10:55:56	ga_s2am_ard_3-2-1_53JKF_2022-10-20_final.stac-item
2022-10-20 10:55:58	ga_s2am_ard_3-2-1_52JGL_2022-10-20_final.stac-item
2022-10-23 11:05:47	ga_s2am_ard_3-2-1_52JEM_2022-10-23_final.stac-item
2022-10-23 11:05:51	ga_s2am_ard_3-2-1_52JDM_2022-10-23_final.stac-item
2022-10-23 11:05:54	ga_s2am_ard_3-2-1_52JCM_2022-10-23_final.stac-item
2022-10-23 11:06:01	ga_s2am_ard_3-2-1_52JBM_2022-10-23_final.stac-item
2022-10-23 11:06:08	ga_s2am_ard_3-2-1_52JCL_2022-10-23_final.stac-item
2022-10-23 11:06:12	ga_s2am_ard_3-2-1_52JBL_2022-10-23_final.stac-item
2023-01-11 09:25:01	ga_s2am_ard_3-2-1_56JPM_2023-01-10_nrt.stac-item
2023-01-11 09:25:05	ga_s2am_ard_3-2-1_56JNM_2023-01-10_final.stac-item
2023-01-11 09:25:09	ga_s2am_ard_3-2-1_56JMM_2023-01-10_final.stac-item
2023-01-11 09:25:16	ga_s2am_ard_3-2-1_56JPL_2023-01-10_nrt.stac-item
2023-01-11 11:05:42	ga_s2am_ard_3-2-1_52JEM_2023-01-11_final.stac-item
2023-01-11 11:05:49	ga_s2am_ard_3-2-1_52JEM_2023-01-11_final.stac-item
2023-01-11 11:05:51	ga_s2am_ard_3-2-1_52JDM_2023-01-11_final.stac-item
2023-01-11 11:05:52	ga_s2am_ard_3-2-1_52JCM_2023-01-11_final.stac-item
2023-01-11 11:05:56	ga_s2am_ard_3-2-1_52JBM_2023-01-11_final.stac-item
2023-01-11 11:06:04	ga_s2am_ard_3-2-1_52JCL_2023-01-11_final.stac-item
2023-01-11 11:06:08	ga_s2am_ard_3-2-1_52JBL_2023-01-11_final.stac-item
2023-01-12 10:35:28	ga_s2am_ard_3-2-1_53JQG_2023-01-12_final.stac-item
2023-01-12 10:35:32	ga_s2am_ard_3-2-1_53JPG_2023-01-12_final.stac-item
2023-01-12 10:35:35	ga_s2am_ard_3-2-1_53JNG_2023-01-12_final.stac-item
2023-01-12 10:35:39	ga_s2am_ard_3-2-1_53JMG_2023-01-12_final.stac-item
2023-01-12 10:35:42	ga_s2am_ard_3-2-1_53JQF_2023-01-12_final.stac-item
2023-01-12 10:35:46	ga_s2am_ard_3-2-1_53JPF_2023-01-12_final.stac-item
2023-01-14 11:15:45	ga_s2am_ard_3-2-1_52JCM_2023-01-14_final.stac-item
2023-01-14 11:15:48	ga_s2am_ard_3-2-1_52JBM_2023-01-14_final.stac-item
2023-01-14 11:15:51	ga_s2am_ard_3-2-1_51JYG_2023-01-14_final.stac-item
2023-01-14 11:15:54	ga_s2am_ard_3-2-1_51JXG_2023-01-14_final.stac-item
2023-01-14 11:15:59	ga_s2am_ard_3-2-1_52JCL_2023-01-14_final.stac-item
2023-01-14 11:16:03	ga_s2am_ard_3-2-1_52JBL_2023-01-14_final.stac-item
2023-01-14 11:16:05	ga_s2am_ard_3-2-1_51JYF_2023-01-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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