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
2022-04-01 11:55:44	ga_s2am_ard_3-2-1_50JLP_2022-04-01_final
2022-04-01 11:55:47	ga_s2am_ard_3-2-1_50JNN_2022-04-01_final
2022-04-01 11:55:51	ga_s2am_ard_3-2-1_50JLP_2022-04-01_final
2022-04-01 11:55:51	ga_s2am_ard_3-2-1_50JLN_2022-04-01_final
2022-04-01 11:55:54	ga_s2am_ard_3-2-1_50JNN_2022-04-01_final
2022-04-01 11:55:58	ga_s2am_ard_3-2-1_50JLN_2022-04-01_final
2022-04-04 12:04:29	ga_s2am_ard_3-2-1_49KHP_2022-04-04_final
2022-04-04 12:04:47	ga_s2am_ard_3-2-1_49JGN_2022-04-04_final
2022-04-04 12:05:39	ga_s2am_ard_3-2-1_50JLP_2022-04-04_final
2022-04-04 12:05:53	ga_s2am_ard_3-2-1_50JLN_2022-04-04_final
2022-04-07 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-04-07_final
2022-04-07 12:14:42	ga_s2am_ard_3-2-1_49JGN_2022-04-07_final
2022-04-08 11:45:51	ga_s2am_ard_3-2-1_50JPN_2022-04-08_final
2022-04-08 11:45:55	ga_s2am_ard_3-2-1_50JNN_2022-04-08_final
2022-04-11 11:55:44	ga_s2am_ard_3-2-1_50JLP_2022-04-11_final
2022-04-11 11:55:51	ga_s2am_ard_3-2-1_50JNN_2022-04-11_final
2022-04-11 11:55:58	ga_s2am_ard_3-2-1_50JLN_2022-04-11_final
2022-04-14 12:04:31	ga_s2am_ard_3-2-1_49KHP_2022-04-14_final
2022-04-14 12:04:49	ga_s2am_ard_3-2-1_49JGN_2022-04-14_final
2022-04-14 12:05:40	ga_s2am_ard_3-2-1_50JLP_2022-04-14_final
2022-04-14 12:05:54	ga_s2am_ard_3-2-1_50JLN_2022-04-14_final
2022-04-17 12:14:02	ga_s2am_ard_3-2-1_49KGR_2022-04-17_final
2022-04-17 12:14:45	ga_s2am_ard_3-2-1_49JGN_2022-04-17_final
2022-04-18 11:45:54	ga_s2am_ard_3-2-1_50JPN_2022-04-18_final
2022-04-18 11:45:58	ga_s2am_ard_3-2-1_50JNN_2022-04-18_final
2022-04-21 11:55:46	ga_s2am_ard_3-2-1_50JLP_2022-04-21_final
2022-04-21 11:55:54	ga_s2am_ard_3-2-1_50JNN_2022-04-21_final
2022-04-21 11:56:01	ga_s2am_ard_3-2-1_50JLN_2022-04-21_final
2022-04-24 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-04-24_final
2022-04-24 12:04:51	ga_s2am_ard_3-2-1_49JGN_2022-04-24_final
2022-04-24 12:05:42	ga_s2am_ard_3-2-1_50JLP_2022-04-24_final
2022-04-24 12:05:56	ga_s2am_ard_3-2-1_50JLN_2022-04-24_final
2022-04-27 12:14:03	ga_s2am_ard_3-2-1_49KGR_2022-04-27_final
2022-04-27 12:14:26	ga_s2am_ard_3-2-1_49KHP_2022-04-27_final
2022-04-27 12:14:46	ga_s2am_ard_3-2-1_49JGN_2022-04-27_final
2022-04-28 11:45:55	ga_s2am_ard_3-2-1_50JPN_2022-04-28_final
2022-04-28 11:45:59	ga_s2am_ard_3-2-1_50JNN_2022-04-28_final
2022-05-01 11:56:09	ga_s2am_ard_3-2-1_50JNM_2022-05-01_final
2022-05-01 11:56:13	ga_s2am_ard_3-2-1_50JMM_2022-05-01_final
2022-05-01 11:56:27	ga_s2am_ard_3-2-1_50JML_2022-05-01_final
2022-05-01 11:56:41	ga_s2am_ard_3-2-1_50HMK_2022-05-01_final
2022-05-01 11:56:45	ga_s2am_ard_3-2-1_50HLK_2022-05-01_final
2022-05-01 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2022-05-01_final
2022-05-01 11:57:14	ga_s2am_ard_3-2-1_50HLH_2022-05-01_final
2022-05-01 11:57:23	ga_s2am_ard_3-2-1_50HLH_2022-05-01_final
2022-05-05 11:36:31	ga_s2am_ard_3-2-1_50JPL_2022-05-05_final
2022-05-05 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2022-05-05_final
2022-05-05 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-05_final
2022-05-08 11:46:13	ga_s2am_ard_3-2-1_50JNM_2022-05-08_final
2022-05-08 11:46:17	ga_s2am_ard_3-2-1_50JMM_2022-05-08_final
2022-05-08 11:46:23	ga_s2am_ard_3-2-1_50JPL_2022-05-08_final
2022-05-08 11:46:30	ga_s2am_ard_3-2-1_50JML_2022-05-08_final
2022-05-08 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-05-08_final
2022-05-08 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2022-05-08_final
2022-05-08 11:47:06	ga_s2am_ard_3-2-1_50HPH_2022-05-08_final
2022-05-08 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-05-08_final
2022-05-11 11:56:08	ga_s2am_ard_3-2-1_50JNM_2022-05-11_final
2022-05-11 11:56:11	ga_s2am_ard_3-2-1_50JMM_2022-05-11_final
2022-05-11 11:56:26	ga_s2am_ard_3-2-1_50JML_2022-05-11_final
2022-05-11 11:56:40	ga_s2am_ard_3-2-1_50HMK_2022-05-11_final
2022-05-11 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-05-11_final
2022-05-11 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-05-11_final
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final
2022-05-15 11:36:31	ga_s2am_ard_3-2-1_50JPL_2022-05-15_final
2022-05-15 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2022-05-15_final
2022-05-15 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-15_final
2022-05-18 11:46:10	ga_s2am_ard_3-2-1_50JPM_2022-05-18_final
2022-05-18 11:46:14	ga_s2am_ard_3-2-1_50JNM_2022-05-18_final
2022-05-18 11:46:18	ga_s2am_ard_3-2-1_50JMM_2022-05-18_final
2022-05-18 11:46:25	ga_s2am_ard_3-2-1_50JPL_2022-05-18_final
2022-05-18 11:46:31	ga_s2am_ard_3-2-1_50JML_2022-05-18_final
2022-05-18 11:46:46	ga_s2am_ard_3-2-1_50HMK_2022-05-18_final
2022-05-18 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2022-05-18_final
2022-05-18 11:47:08	ga_s2am_ard_3-2-1_50HPH_2022-05-18_final
2022-05-18 11:47:20	ga_s2am_ard_3-2-1_50HLH_2022-05-18_final
2022-05-21 11:56:11	ga_s2am_ard_3-2-1_50JNM_2022-05-21_final
2022-05-21 11:56:14	ga_s2am_ard_3-2-1_50JMM_2022-05-21_final
2022-05-21 11:56:43	ga_s2am_ard_3-2-1_50HMK_2022-05-21_final
2022-05-21 11:56:46	ga_s2am_ard_3-2-1_50HLK_2022-05-21_final
2022-05-21 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-05-21_final
2022-05-21 11:57:16	ga_s2am_ard_3-2-1_50HLH_2022-05-21_final
2022-05-25 11:36:34	ga_s2am_ard_3-2-1_50JPL_2022-05-25_final
2022-05-25 11:36:55	ga_s2am_ard_3-2-1_50HQJ_2022-05-25_final
2022-05-25 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-05-25_final
2022-05-28 11:46:12	ga_s2am_ard_3-2-1_50JPM_2022-05-28_final
2022-05-28 11:46:16	ga_s2am_ard_3-2-1_50JNM_2022-05-28_final
2022-05-28 11:46:20	ga_s2am_ard_3-2-1_50JMM_2022-05-28_final
2022-05-28 11:46:23	ga_s2am_ard_3-2-1_50JQL_2022-05-28_final
2022-05-28 11:46:27	ga_s2am_ard_3-2-1_50JPL_2022-05-28_final
2022-05-28 11:46:33	ga_s2am_ard_3-2-1_50JML_2022-05-28_final
2022-05-28 11:46:48	ga_s2am_ard_3-2-1_50HMK_2022-05-28_final
2022-05-28 11:46:50	ga_s2am_ard_3-2-1_50HQJ_2022-05-28_final
2022-05-28 11:47:10	ga_s2am_ard_3-2-1_50HPH_2022-05-28_final
2022-05-28 11:47:22	ga_s2am_ard_3-2-1_50HLH_2022-05-28_final
2022-05-31 11:56:12	ga_s2am_ard_3-2-1_50JNM_2022-05-31_final
2022-05-31 11:56:15	ga_s2am_ard_3-2-1_50JMM_2022-05-31_final
2022-05-31 11:56:30	ga_s2am_ard_3-2-1_50JML_2022-05-31_final
2022-05-31 11:56:44	ga_s2am_ard_3-2-1_50HMK_2022-05-31_final
2022-05-31 11:56:48	ga_s2am_ard_3-2-1_50HLK_2022-05-31_final
2022-05-31 11:57:02	ga_s2am_ard_3-2-1_50HLJ_2022-05-31_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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