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
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_54JWM_2016-02-09_final.stac-item
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_54JXM_2016-02-09_final.stac-item
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_54JYL_2016-02-09_final.stac-item
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_54JYM_2016-02-09_final.stac-item
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_55JBG_2016-02-09_final.stac-item
2016-02-09 10:03:07	ga_s2am_ard_3-2-1_55JCG_2016-02-09_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JKG_2016-03-02_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JLG_2016-03-02_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JMG_2016-03-02_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_52JGL_2016-03-02_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_52JGM_2016-03-02_final.stac-item
2016-03-02 10:44:00	ga_s2am_ard_3-2-1_53JNG_2016-03-02_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JKM_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JLM_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JMM_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNM_2016-03-03_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_50JQM_2016-03-07_final
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JKM_2016-03-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JLM_2016-03-16_final.stac-item
2016-03-18 09:22:41	ga_s2am_ard_3-2-1_56JMM_2016-03-17_final.stac-item
2016-03-18 09:22:41	ga_s2am_ard_3-2-1_56JNM_2016-03-17_final.stac-item
2016-03-23 10:15:14	ga_s2am_ard_3-2-1_54JUM_2016-03-23_final.stac-item
2016-03-23 10:15:14	ga_s2am_ard_3-2-1_54JVM_2016-03-23_final.stac-item
2016-03-23 10:15:14	ga_s2am_ard_3-2-1_54JWM_2016-03-23_final.stac-item
2016-03-23 10:15:14	ga_s2am_ard_3-2-1_54JXM_2016-03-23_final.stac-item
2016-03-28 11:01:10	ga_s2am_ard_3-2-1_52JBM_2016-03-28_final.stac-item
2016-03-28 11:01:10	ga_s2am_ard_3-2-1_52JCM_2016-03-28_final.stac-item
2016-03-29 10:28:49	ga_s2am_ard_3-2-1_53JPG_2016-03-29_final.stac-item
2016-03-29 10:28:49	ga_s2am_ard_3-2-1_53JQG_2016-03-29_final.stac-item
2016-04-05 10:24:40	ga_s2am_ard_3-2-1_54JTM_2016-04-05_final.stac-item
2016-04-05 10:24:40	ga_s2am_ard_3-2-1_54JUM_2016-04-05_final.stac-item
2016-04-05 10:24:40	ga_s2am_ard_3-2-1_54JVM_2016-04-05_final.stac-item
2016-04-05 10:24:40	ga_s2am_ard_3-2-1_53JPG_2016-04-05_final.stac-item
2016-04-05 10:24:40	ga_s2am_ard_3-2-1_53JQF_2016-04-05_final.stac-item
2016-04-05 10:24:40	ga_s2am_ard_3-2-1_53JQG_2016-04-05_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_51JXG_2016-04-10_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_51JYF_2016-04-10_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_51JYG_2016-04-10_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_52JBM_2016-04-10_final.stac-item
2018-12-15 11:45:48	ga_s2am_ard_3-2-1_51JTG_2018-12-15_final.stac-item
2018-12-15 11:45:52	ga_s2am_ard_3-2-1_50JQM_2018-12-15_final.stac-item
2018-12-15 11:45:56	ga_s2am_ard_3-2-1_50JPM_2018-12-15_final.stac-item
2018-12-15 11:46:00	ga_s2am_ard_3-2-1_50JNM_2018-12-15_final.stac-item
2018-12-15 11:46:04	ga_s2am_ard_3-2-1_50JMM_2018-12-15_final.stac-item
2018-12-16 09:34:57	ga_s2am_ard_3-2-1_56JMM_2018-12-16_final.stac-item
2018-12-16 09:35:01	ga_s2am_ard_3-2-1_56JLM_2018-12-16_final.stac-item
2018-12-16 09:35:04	ga_s2am_ard_3-2-1_56JKM_2018-12-16_final.stac-item
2018-12-16 09:35:07	ga_s2am_ard_3-2-1_55JGG_2018-12-16_final.stac-item
2018-12-16 09:35:21	ga_s2am_ard_3-2-1_55JGF_2018-12-16_final.stac-item
2018-12-18 10:15:14	ga_s2am_ard_3-2-1_54JXM_2018-12-18_final.stac-item
2018-12-18 10:15:17	ga_s2am_ard_3-2-1_54JWM_2018-12-18_final.stac-item
2018-12-18 10:15:21	ga_s2am_ard_3-2-1_54JVM_2018-12-18_final.stac-item
2018-12-18 10:15:24	ga_s2am_ard_3-2-1_54JUM_2018-12-18_final.stac-item
2018-12-18 11:55:55	ga_s2am_ard_3-2-1_50JNM_2018-12-18_final.stac-item
2018-12-18 11:55:59	ga_s2am_ard_3-2-1_50JMM_2018-12-18_final.stac-item
2018-12-18 11:56:02	ga_s2am_ard_3-2-1_50JLM_2018-12-18_final.stac-item
2018-12-18 11:56:05	ga_s2am_ard_3-2-1_50JKM_2018-12-18_final.stac-item
2018-12-19 09:45:00	ga_s2am_ard_3-2-1_56JKM_2018-12-19_final.stac-item
2018-12-19 09:45:02	ga_s2am_ard_3-2-1_55JGG_2018-12-19_final.stac-item
2018-12-19 09:45:06	ga_s2am_ard_3-2-1_55JFG_2018-12-19_final.stac-item
2018-12-19 09:45:10	ga_s2am_ard_3-2-1_55JEG_2018-12-19_final.stac-item
2018-12-19 09:45:17	ga_s2am_ard_3-2-1_55JDG_2018-12-19_final.stac-item
2018-12-21 10:25:16	ga_s2am_ard_3-2-1_54JVM_2018-12-21_final.stac-item
2018-12-21 10:25:20	ga_s2am_ard_3-2-1_54JUM_2018-12-21_final.stac-item
2018-12-21 10:25:23	ga_s2am_ard_3-2-1_54JTM_2018-12-21_final.stac-item
2018-12-21 10:25:26	ga_s2am_ard_3-2-1_53JQG_2018-12-21_final.stac-item
2018-12-21 10:25:31	ga_s2am_ard_3-2-1_53JPG_2018-12-21_final.stac-item
2018-12-21 10:25:40	ga_s2am_ard_3-2-1_53JQF_2018-12-21_final.stac-item
2018-12-23 11:05:37	ga_s2am_ard_3-2-1_52JEM_2018-12-23_final.stac-item
2018-12-23 11:05:41	ga_s2am_ard_3-2-1_52JDM_2018-12-23_final.stac-item
2018-12-23 11:05:44	ga_s2am_ard_3-2-1_52JCM_2018-12-23_final.stac-item
2018-12-23 11:05:50	ga_s2am_ard_3-2-1_52JBM_2018-12-23_final.stac-item
2018-12-26 09:34:59	ga_s2am_ard_3-2-1_56JMM_2018-12-26_final.stac-item
2018-12-26 09:35:02	ga_s2am_ard_3-2-1_56JLM_2018-12-26_final.stac-item
2018-12-26 09:35:05	ga_s2am_ard_3-2-1_56JKM_2018-12-26_final.stac-item
2018-12-26 09:35:08	ga_s2am_ard_3-2-1_55JGG_2018-12-26_final.stac-item
2018-12-26 09:35:23	ga_s2am_ard_3-2-1_55JGF_2018-12-26_final.stac-item
2018-12-27 10:45:25	ga_s2am_ard_3-2-1_53JNG_2018-12-27_final.stac-item
2018-12-27 10:45:30	ga_s2am_ard_3-2-1_53JMG_2018-12-27_final.stac-item
2018-12-27 10:45:33	ga_s2am_ard_3-2-1_53JLG_2018-12-27_final.stac-item
2018-12-27 10:45:36	ga_s2am_ard_3-2-1_53JKG_2018-12-27_final.stac-item
2018-12-27 10:45:40	ga_s2am_ard_3-2-1_52JGM_2018-12-27_final.stac-item
2018-12-27 10:45:53	ga_s2am_ard_3-2-1_52JGL_2018-12-27_final.stac-item
2018-12-28 10:15:15	ga_s2am_ard_3-2-1_54JXM_2018-12-28_final.stac-item
2019-01-02 11:05:39	ga_s2am_ard_3-2-1_52JEM_2019-01-02_final.stac-item
2019-01-02 11:05:43	ga_s2am_ard_3-2-1_52JDM_2019-01-02_final.stac-item
2019-01-02 11:05:46	ga_s2am_ard_3-2-1_52JCM_2019-01-02_final.stac-item
2019-01-02 11:05:52	ga_s2am_ard_3-2-1_52JBM_2019-01-02_final.stac-item
2019-01-03 10:35:25	ga_s2am_ard_3-2-1_53JQG_2019-01-03_final.stac-item
2019-01-03 10:35:28	ga_s2am_ard_3-2-1_53JPG_2019-01-03_final.stac-item
2019-01-03 10:35:32	ga_s2am_ard_3-2-1_53JNG_2019-01-03_final.stac-item
2019-01-03 10:35:35	ga_s2am_ard_3-2-1_53JMG_2019-01-03_final.stac-item
2019-01-05 09:35:01	ga_s2am_ard_3-2-1_56JMM_2019-01-05_final.stac-item
2019-01-05 09:35:04	ga_s2am_ard_3-2-1_56JLM_2019-01-05_final.stac-item
2019-01-05 09:35:07	ga_s2am_ard_3-2-1_56JKM_2019-01-05_final.stac-item
2019-01-05 09:35:10	ga_s2am_ard_3-2-1_55JGG_2019-01-05_final.stac-item
2019-01-05 09:35:24	ga_s2am_ard_3-2-1_55JGF_2019-01-05_final.stac-item
2019-04-28 11:25:56	ga_s2am_ard_3-2-1_51JXG_2019-04-28_final.stac-item
2019-04-28 11:26:00	ga_s2am_ard_3-2-1_51JWG_2019-04-28_final.stac-item
2019-04-28 11:26:04	ga_s2am_ard_3-2-1_51JVG_2019-04-28_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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