Search ga_ls7e_ard_3 across December 2016

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:

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):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

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:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

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 Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-12-01 10:42:56	ga_ls7e_ard_3-0-0_104068_2016-12-01_final
2016-12-01 10:43:20	ga_ls7e_ard_3-0-0_104069_2016-12-01_final
2016-12-01 10:43:44	ga_ls7e_ard_3-1-0_104070_2016-12-01_final
2016-12-01 10:44:08	ga_ls7e_ard_3-0-0_104071_2016-12-01_final
2016-12-01 10:44:32	ga_ls7e_ard_3-0-0_104072_2016-12-01_final
2016-12-01 10:44:56	ga_ls7e_ard_3-0-0_104073_2016-12-01_final
2016-12-01 10:45:20	ga_ls7e_ard_3-0-0_104074_2016-12-01_final
2016-12-01 10:45:44	ga_ls7e_ard_3-0-0_104075_2016-12-01_final
2016-12-01 10:46:08	ga_ls7e_ard_3-0-0_104076_2016-12-01_final
2016-12-01 10:46:32	ga_ls7e_ard_3-0-0_104077_2016-12-01_final
2016-12-01 10:46:56	ga_ls7e_ard_3-0-0_104078_2016-12-01_final
2016-12-01 10:47:20	ga_ls7e_ard_3-0-0_104079_2016-12-01_final
2016-12-01 10:47:43	ga_ls7e_ard_3-0-0_104080_2016-12-01_final
2016-12-01 10:48:07	ga_ls7e_ard_3-0-0_104081_2016-12-01_final
2016-12-01 10:48:31	ga_ls7e_ard_3-0-0_104082_2016-12-01_final
2016-12-13 09:31:55	ga_ls7e_ard_3-0-0_092076_2016-12-13_final
2016-12-13 09:32:42	ga_ls7e_ard_3-0-0_092078_2016-12-13_final
2016-12-13 09:33:06	ga_ls7e_ard_3-0-0_092079_2016-12-13_final
2016-12-13 09:33:30	ga_ls7e_ard_3-0-0_092080_2016-12-13_final
2016-12-13 09:33:54	ga_ls7e_ard_3-0-0_092081_2016-12-13_final
2016-12-13 09:34:18	ga_ls7e_ard_3-0-0_092082_2016-12-13_final
2016-12-14 10:12:22	ga_ls7e_ard_3-0-0_099069_2016-12-14_final
2016-12-14 10:12:46	ga_ls7e_ard_3-0-0_099070_2016-12-14_final
2016-12-14 10:13:10	ga_ls7e_ard_3-0-0_099071_2016-12-14_final
2016-12-14 10:13:34	ga_ls7e_ard_3-0-0_099072_2016-12-14_final
2016-12-14 10:13:58	ga_ls7e_ard_3-0-0_099073_2016-12-14_final
2016-12-14 10:14:22	ga_ls7e_ard_3-0-0_099074_2016-12-14_final
2016-12-14 10:14:46	ga_ls7e_ard_3-0-0_099075_2016-12-14_final
2016-12-14 10:15:10	ga_ls7e_ard_3-0-0_099076_2016-12-14_final
2016-12-14 10:15:34	ga_ls7e_ard_3-0-0_099077_2016-12-14_final
2016-12-14 10:15:58	ga_ls7e_ard_3-0-0_099078_2016-12-14_final
2016-12-14 10:16:22	ga_ls7e_ard_3-0-0_099079_2016-12-14_final
2016-12-14 11:53:15	ga_ls7e_ard_3-0-0_115074_2016-12-14_final
2016-12-14 11:53:39	ga_ls7e_ard_3-0-0_115075_2016-12-14_final
2016-12-14 11:54:03	ga_ls7e_ard_3-0-0_115076_2016-12-14_final
2016-12-14 11:54:27	ga_ls7e_ard_3-1-0_115077_2016-12-14_final
2016-12-14 11:54:51	ga_ls7e_ard_3-0-0_115078_2016-12-14_final
2016-12-14 11:55:15	ga_ls7e_ard_3-0-0_115079_2016-12-14_final
2016-12-15 09:19:56	ga_ls7e_ard_3-0-0_090077_2016-12-14_final
2016-12-15 09:20:20	ga_ls7e_ard_3-0-0_090078_2016-12-14_final
2016-12-15 09:20:44	ga_ls7e_ard_3-0-0_090079_2016-12-14_final
2016-12-15 09:21:08	ga_ls7e_ard_3-0-0_090080_2016-12-14_final
2016-12-15 09:21:32	ga_ls7e_ard_3-0-0_090081_2016-12-14_final
2016-12-15 09:24:20	ga_ls7e_ard_3-0-0_090088_2016-12-14_final
2016-12-15 09:24:44	ga_ls7e_ard_3-0-0_090089_2016-12-14_final
2016-12-15 09:25:08	ga_ls7e_ard_3-0-0_090090_2016-12-14_final
2016-12-15 10:55:14	ga_ls7e_ard_3-0-0_106068_2016-12-15_final
2016-12-15 10:55:38	ga_ls7e_ard_3-0-0_106069_2016-12-15_final
2016-12-15 10:56:02	ga_ls7e_ard_3-0-0_106070_2016-12-15_final
2016-12-15 10:56:26	ga_ls7e_ard_3-0-0_106071_2016-12-15_final
2016-12-15 10:56:50	ga_ls7e_ard_3-0-0_106072_2016-12-15_final
2016-12-15 10:57:13	ga_ls7e_ard_3-0-0_106073_2016-12-15_final
2016-12-15 10:57:37	ga_ls7e_ard_3-0-0_106074_2016-12-15_final
2016-12-15 10:58:01	ga_ls7e_ard_3-1-0_106075_2016-12-15_final
2016-12-15 10:58:25	ga_ls7e_ard_3-0-0_106076_2016-12-15_final
2016-12-15 10:58:49	ga_ls7e_ard_3-1-0_106077_2016-12-15_final
2016-12-15 10:59:13	ga_ls7e_ard_3-0-0_106078_2016-12-15_final
2016-12-15 11:01:13	ga_ls7e_ard_3-0-0_106083_2016-12-15_final
2016-12-16 10:00:00	ga_ls7e_ard_3-0-0_097069_2016-12-16_final
2016-12-16 10:00:24	ga_ls7e_ard_3-0-0_097070_2016-12-16_final
2016-12-16 10:00:48	ga_ls7e_ard_3-0-0_097071_2016-12-16_final
2016-12-16 10:01:12	ga_ls7e_ard_3-0-0_097072_2016-12-16_final
2016-12-16 10:01:36	ga_ls7e_ard_3-0-0_097073_2016-12-16_final
2016-12-16 10:02:00	ga_ls7e_ard_3-0-0_097074_2016-12-16_final
2016-12-16 10:02:24	ga_ls7e_ard_3-0-0_097075_2016-12-16_final
2016-12-16 10:02:48	ga_ls7e_ard_3-1-0_097076_2016-12-16_final
2016-12-16 10:03:12	ga_ls7e_ard_3-0-0_097077_2016-12-16_final
2016-12-16 10:03:35	ga_ls7e_ard_3-0-0_097078_2016-12-16_final
2016-12-16 10:03:59	ga_ls7e_ard_3-0-0_097079_2016-12-16_final
2016-12-16 10:04:23	ga_ls7e_ard_3-0-0_097080_2016-12-16_final
2016-12-16 10:04:47	ga_ls7e_ard_3-0-0_097081_2016-12-16_final
2016-12-16 10:05:11	ga_ls7e_ard_3-0-0_097082_2016-12-16_final
2016-12-16 10:05:35	ga_ls7e_ard_3-0-0_097083_2016-12-16_final
2016-12-16 10:05:59	ga_ls7e_ard_3-0-0_097084_2016-12-16_final
2016-12-16 10:06:23	ga_ls7e_ard_3-0-0_097085_2016-12-16_final
2016-12-16 11:38:05	ga_ls7e_ard_3-0-0_113067_2016-12-16_final
2016-12-16 11:40:53	ga_ls7e_ard_3-0-0_113074_2016-12-16_final
2016-12-16 11:41:17	ga_ls7e_ard_3-0-0_113075_2016-12-16_final
2016-12-16 11:41:41	ga_ls7e_ard_3-0-0_113076_2016-12-16_final
2016-12-16 11:42:05	ga_ls7e_ard_3-0-0_113077_2016-12-16_final
2016-12-16 11:42:28	ga_ls7e_ard_3-0-0_113078_2016-12-16_final
2016-12-16 11:42:52	ga_ls7e_ard_3-0-0_113079_2016-12-16_final
2016-12-16 11:43:16	ga_ls7e_ard_3-0-0_113080_2016-12-16_final
2016-12-16 11:43:40	ga_ls7e_ard_3-0-0_113081_2016-12-16_final
2016-12-16 11:44:04	ga_ls7e_ard_3-0-0_113082_2016-12-16_final
2016-12-16 11:44:28	ga_ls7e_ard_3-0-0_113083_2016-12-16_final
2016-12-16 11:44:52	ga_ls7e_ard_3-0-0_113084_2016-12-16_final
2016-12-17 10:42:51	ga_ls7e_ard_3-0-0_104068_2016-12-17_final
2016-12-17 10:43:15	ga_ls7e_ard_3-0-0_104069_2016-12-17_final
2016-12-17 10:43:39	ga_ls7e_ard_3-1-0_104070_2016-12-17_final
2016-12-17 10:44:03	ga_ls7e_ard_3-0-0_104071_2016-12-17_final
2016-12-17 10:44:27	ga_ls7e_ard_3-0-0_104072_2016-12-17_final
2016-12-17 10:44:51	ga_ls7e_ard_3-0-0_104073_2016-12-17_final
2016-12-17 10:45:15	ga_ls7e_ard_3-0-0_104074_2016-12-17_final
2016-12-17 10:45:39	ga_ls7e_ard_3-0-0_104075_2016-12-17_final
2016-12-17 10:46:03	ga_ls7e_ard_3-0-0_104076_2016-12-17_final
2016-12-17 10:46:27	ga_ls7e_ard_3-0-0_104077_2016-12-17_final
2016-12-17 10:46:51	ga_ls7e_ard_3-0-0_104078_2016-12-17_final
2016-12-17 10:47:15	ga_ls7e_ard_3-0-0_104079_2016-12-17_final
2016-12-17 10:47:39	ga_ls7e_ard_3-0-0_104080_2016-12-17_final

Return to ga_ls7e_ard_3 across December 2016 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2016

December

All days