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
2022-02-03 12:04:57	ga_s2am_ard_3-2-1_49JHM_2022-02-03_final
2022-02-03 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-03_final
2022-02-03 12:05:29	ga_s2am_ard_3-2-1_49JGK_2022-02-03_final
2022-02-06 12:14:45	ga_s2am_ard_3-2-1_49JFN_2022-02-06_final
2022-02-06 12:14:59	ga_s2am_ard_3-2-1_49JFM_2022-02-06_final
2022-02-06 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-02-06_final
2022-02-06 12:15:19	ga_s2am_ard_3-2-1_49JGK_2022-02-06_final
2022-02-07 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-02-07_final
2022-02-07 11:47:14	ga_s2am_ard_3-2-1_50HLH_2022-02-07_final
2022-02-10 11:56:39	ga_s2am_ard_3-2-1_50HLK_2022-02-10_final
2022-02-10 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-02-10_final
2022-02-10 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2022-02-10_final
2022-02-10 11:57:08	ga_s2am_ard_3-2-1_50HLH_2022-02-10_final
2022-02-13 12:04:56	ga_s2am_ard_3-2-1_49JHM_2022-02-13_final
2022-02-13 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-13_final
2022-02-13 12:05:29	ga_s2am_ard_3-2-1_49JGK_2022-02-13_final
2022-02-13 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2022-02-13_final
2022-02-16 12:15:00	ga_s2am_ard_3-2-1_49JFM_2022-02-16_final
2022-02-16 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-02-16_final
2022-02-16 12:15:20	ga_s2am_ard_3-2-1_49JGK_2022-02-16_final
2022-02-17 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2022-02-17_final
2022-02-17 11:47:15	ga_s2am_ard_3-2-1_50HLH_2022-02-17_final
2022-02-20 11:56:42	ga_s2am_ard_3-2-1_50HLK_2022-02-20_final
2022-02-20 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-02-20_final
2022-02-20 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-02-20_final
2022-02-20 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-02-20_final
2022-02-23 12:04:59	ga_s2am_ard_3-2-1_49JHM_2022-02-23_final
2022-02-23 12:05:11	ga_s2am_ard_3-2-1_49JFM_2022-02-23_final
2022-02-23 12:05:17	ga_s2am_ard_3-2-1_49JGL_2022-02-23_final
2022-02-23 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-02-23_final
2022-02-26 12:15:03	ga_s2am_ard_3-2-1_49JFM_2022-02-26_final
2022-02-26 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-02-26_final
2022-02-26 12:15:23	ga_s2am_ard_3-2-1_49JGK_2022-02-26_final
2022-02-27 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2022-02-27_final
2022-02-27 11:47:17	ga_s2am_ard_3-2-1_50HLH_2022-02-27_final
2022-03-02 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-03-02_final
2022-03-02 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2022-03-02_final
2022-03-02 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-03-02_final
2022-03-02 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-03-02_final
2022-03-05 12:04:32	ga_s2am_ard_3-2-1_49KHP_2022-03-05_final
2022-03-05 12:04:46	ga_s2am_ard_3-2-1_49JHN_2022-03-05_final
2022-03-05 12:05:00	ga_s2am_ard_3-2-1_49JHM_2022-03-05_final
2022-03-05 12:05:08	ga_s2am_ard_3-2-1_49JHM_2022-03-05_final
2022-03-05 12:05:09	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final
2022-03-05 12:05:12	ga_s2am_ard_3-2-1_49JFM_2022-03-05_final
2022-03-05 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-05_final
2022-03-08 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-03-08_final
2022-03-08 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-03-08_final
2022-03-08 12:14:35	ga_s2am_ard_3-2-1_49JHN_2022-03-08_final
2022-03-08 12:14:49	ga_s2am_ard_3-2-1_49JFN_2022-03-08_final
2022-03-08 12:15:04	ga_s2am_ard_3-2-1_49JFM_2022-03-08_final
2022-03-08 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-03-08_final
2022-03-08 12:15:24	ga_s2am_ard_3-2-1_49JGK_2022-03-08_final
2022-03-09 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2022-03-09_final
2022-03-09 11:47:10	ga_s2am_ard_3-2-1_50HNH_2022-03-09_final
2022-03-09 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-03-09_final
2022-03-12 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-03-12_final
2022-03-12 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2022-03-12_final
2022-03-12 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2022-03-12_final
2022-03-12 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-03-12_final
2022-03-12 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-03-12_final
2022-03-15 12:04:32	ga_s2am_ard_3-2-1_49KHP_2022-03-15_final
2022-03-15 12:04:46	ga_s2am_ard_3-2-1_49JHN_2022-03-15_final
2022-03-15 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-03-15_final
2022-03-15 12:05:12	ga_s2am_ard_3-2-1_49JFM_2022-03-15_final
2022-03-15 12:05:19	ga_s2am_ard_3-2-1_49JGL_2022-03-15_final
2022-03-15 12:05:33	ga_s2am_ard_3-2-1_49JGK_2022-03-15_final
2022-03-15 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-03-15_final
2022-03-15 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final
2022-03-15 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final
2022-03-18 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-03-18_final
2022-03-18 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-03-18_final
2022-03-18 12:14:34	ga_s2am_ard_3-2-1_49JHN_2022-03-18_final
2022-03-18 12:14:49	ga_s2am_ard_3-2-1_49JFN_2022-03-18_final
2022-03-18 12:15:03	ga_s2am_ard_3-2-1_49JFM_2022-03-18_final
2022-03-18 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-03-18_final
2022-03-18 12:15:23	ga_s2am_ard_3-2-1_49JGK_2022-03-18_final
2022-03-19 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2022-03-19_final
2022-03-19 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-03-19_final
2022-03-22 11:56:43	ga_s2am_ard_3-2-1_50HLK_2022-03-22_final
2022-03-22 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2022-03-22_final
2022-03-22 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-03-22_final
2022-03-22 11:57:12	ga_s2am_ard_3-2-1_50HLH_2022-03-22_final
2022-03-25 12:04:30	ga_s2am_ard_3-2-1_49KHP_2022-03-25_final
2022-03-25 12:04:45	ga_s2am_ard_3-2-1_49JHN_2022-03-25_final
2022-03-25 12:04:59	ga_s2am_ard_3-2-1_49JHM_2022-03-25_final
2022-03-25 12:05:07	ga_s2am_ard_3-2-1_49JHM_2022-03-25_final
2022-03-25 12:05:08	ga_s2am_ard_3-2-1_49JGL_2022-03-25_final
2022-03-25 12:05:18	ga_s2am_ard_3-2-1_49JGL_2022-03-25_final
2022-03-25 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-03-25_final
2022-03-25 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2022-03-25_final
2022-03-28 12:14:01	ga_s2am_ard_3-2-1_49KGR_2022-03-28_final
2022-03-28 12:14:19	ga_s2am_ard_3-2-1_49KHP_2022-03-28_final
2022-03-28 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-03-28_final
2022-03-28 12:14:33	ga_s2am_ard_3-2-1_49JHN_2022-03-28_final
2022-03-28 12:14:48	ga_s2am_ard_3-2-1_49JFN_2022-03-28_final
2022-03-28 12:15:02	ga_s2am_ard_3-2-1_49JFM_2022-03-28_final
2022-03-28 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-03-28_final
2022-03-28 12:15:22	ga_s2am_ard_3-2-1_49JGK_2022-03-28_final
2022-03-29 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2022-03-29_final

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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