Search ga_ls7e_ard_3 across July 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
2016-07-07 10:11:41	ga_ls7e_ard_3-0-0_099067_2016-07-07_final
2016-07-07 10:12:05	ga_ls7e_ard_3-0-0_099068_2016-07-07_final
2016-07-07 10:12:29	ga_ls7e_ard_3-0-0_099069_2016-07-07_final
2016-07-07 10:12:53	ga_ls7e_ard_3-0-0_099070_2016-07-07_final
2016-07-07 10:13:17	ga_ls7e_ard_3-0-0_099071_2016-07-07_final
2016-07-07 10:13:41	ga_ls7e_ard_3-0-0_099072_2016-07-07_final
2016-07-07 10:14:05	ga_ls7e_ard_3-0-0_099073_2016-07-07_final
2016-07-07 10:14:29	ga_ls7e_ard_3-0-0_099074_2016-07-07_final
2016-07-07 10:14:53	ga_ls7e_ard_3-0-0_099075_2016-07-07_final
2016-07-07 10:15:17	ga_ls7e_ard_3-0-0_099076_2016-07-07_final
2016-07-07 10:15:41	ga_ls7e_ard_3-0-0_099077_2016-07-07_final
2016-07-07 10:16:05	ga_ls7e_ard_3-0-0_099078_2016-07-07_final
2016-07-07 10:18:28	ga_ls7e_ard_3-0-0_099084_2016-07-07_final
2016-07-07 11:53:22	ga_ls7e_ard_3-0-0_115074_2016-07-07_final
2016-07-07 11:53:46	ga_ls7e_ard_3-0-0_115075_2016-07-07_final
2016-07-07 11:54:10	ga_ls7e_ard_3-0-0_115076_2016-07-07_final
2016-07-07 11:54:34	ga_ls7e_ard_3-1-0_115077_2016-07-07_final
2016-07-07 11:54:58	ga_ls7e_ard_3-0-0_115078_2016-07-07_final
2016-07-07 11:55:22	ga_ls7e_ard_3-0-0_115079_2016-07-07_final
2016-07-08 09:20:03	ga_ls7e_ard_3-0-0_090077_2016-07-07_final
2016-07-08 09:20:27	ga_ls7e_ard_3-0-0_090078_2016-07-07_final
2016-07-08 09:20:51	ga_ls7e_ard_3-0-0_090079_2016-07-07_final
2016-07-08 09:21:15	ga_ls7e_ard_3-0-0_090080_2016-07-07_final
2016-07-08 09:21:39	ga_ls7e_ard_3-0-0_090081_2016-07-07_final
2016-07-08 09:23:39	ga_ls7e_ard_3-0-0_090086_2016-07-07_final
2016-07-08 09:24:27	ga_ls7e_ard_3-0-0_090088_2016-07-07_final
2016-07-08 09:24:51	ga_ls7e_ard_3-0-0_090089_2016-07-07_final
2016-07-08 09:25:15	ga_ls7e_ard_3-0-0_090090_2016-07-07_final
2016-07-08 10:55:21	ga_ls7e_ard_3-0-0_106068_2016-07-08_final
2016-07-08 10:55:45	ga_ls7e_ard_3-0-0_106069_2016-07-08_final
2016-07-08 10:56:09	ga_ls7e_ard_3-0-0_106070_2016-07-08_final
2016-07-08 10:56:33	ga_ls7e_ard_3-0-0_106071_2016-07-08_final
2016-07-08 10:56:57	ga_ls7e_ard_3-0-0_106072_2016-07-08_final
2016-07-08 10:57:21	ga_ls7e_ard_3-0-0_106073_2016-07-08_final
2016-07-08 10:57:44	ga_ls7e_ard_3-0-0_106074_2016-07-08_final
2016-07-08 10:58:08	ga_ls7e_ard_3-1-0_106075_2016-07-08_final
2016-07-08 10:58:32	ga_ls7e_ard_3-0-0_106076_2016-07-08_final
2016-07-08 10:58:56	ga_ls7e_ard_3-0-0_106077_2016-07-08_final
2016-07-08 10:59:20	ga_ls7e_ard_3-0-0_106078_2016-07-08_final
2016-07-08 10:59:44	ga_ls7e_ard_3-0-0_106079_2016-07-08_final
2016-07-08 11:00:08	ga_ls7e_ard_3-0-0_106080_2016-07-08_final
2016-07-09 10:00:07	ga_ls7e_ard_3-0-0_097069_2016-07-09_final
2016-07-09 10:00:31	ga_ls7e_ard_3-0-0_097070_2016-07-09_final
2016-07-09 10:00:55	ga_ls7e_ard_3-0-0_097071_2016-07-09_final
2016-07-09 10:01:19	ga_ls7e_ard_3-0-0_097072_2016-07-09_final
2016-07-09 10:01:43	ga_ls7e_ard_3-0-0_097073_2016-07-09_final
2016-07-09 10:02:07	ga_ls7e_ard_3-0-0_097074_2016-07-09_final
2016-07-09 10:02:31	ga_ls7e_ard_3-0-0_097075_2016-07-09_final
2016-07-09 10:02:55	ga_ls7e_ard_3-1-0_097076_2016-07-09_final
2016-07-09 10:03:19	ga_ls7e_ard_3-0-0_097077_2016-07-09_final
2016-07-09 10:03:43	ga_ls7e_ard_3-0-0_097078_2016-07-09_final
2016-07-09 10:04:07	ga_ls7e_ard_3-0-0_097079_2016-07-09_final
2016-07-09 10:04:31	ga_ls7e_ard_3-0-0_097080_2016-07-09_final
2016-07-09 10:04:55	ga_ls7e_ard_3-0-0_097081_2016-07-09_final
2016-07-09 10:05:19	ga_ls7e_ard_3-0-0_097082_2016-07-09_final
2016-07-09 10:05:43	ga_ls7e_ard_3-0-0_097083_2016-07-09_final
2016-07-09 10:06:07	ga_ls7e_ard_3-0-0_097084_2016-07-09_final
2016-07-09 10:06:30	ga_ls7e_ard_3-0-0_097085_2016-07-09_final
2016-07-09 11:41:00	ga_ls7e_ard_3-0-0_113074_2016-07-09_final
2016-07-09 11:41:24	ga_ls7e_ard_3-0-0_113075_2016-07-09_final
2016-07-09 11:41:48	ga_ls7e_ard_3-0-0_113076_2016-07-09_final
2016-07-09 11:42:12	ga_ls7e_ard_3-0-0_113077_2016-07-09_final
2016-07-09 11:43:00	ga_ls7e_ard_3-0-0_113079_2016-07-09_final
2016-07-09 11:43:24	ga_ls7e_ard_3-0-0_113080_2016-07-09_final
2016-07-09 11:43:48	ga_ls7e_ard_3-0-0_113081_2016-07-09_final
2016-07-09 11:44:12	ga_ls7e_ard_3-0-0_113082_2016-07-09_final
2016-07-09 11:44:36	ga_ls7e_ard_3-0-0_113083_2016-07-09_final
2016-07-09 11:45:00	ga_ls7e_ard_3-0-0_113084_2016-07-09_final
2016-07-10 10:42:59	ga_ls7e_ard_3-0-0_104068_2016-07-10_final
2016-07-10 10:43:23	ga_ls7e_ard_3-0-0_104069_2016-07-10_final
2016-07-10 10:43:47	ga_ls7e_ard_3-1-0_104070_2016-07-10_final
2016-07-10 10:44:11	ga_ls7e_ard_3-0-0_104071_2016-07-10_final
2016-07-10 10:44:35	ga_ls7e_ard_3-0-0_104072_2016-07-10_final
2016-07-10 10:44:59	ga_ls7e_ard_3-0-0_104073_2016-07-10_final
2016-07-10 10:45:23	ga_ls7e_ard_3-0-0_104074_2016-07-10_final
2016-07-10 10:45:47	ga_ls7e_ard_3-0-0_104075_2016-07-10_final
2016-07-10 10:46:11	ga_ls7e_ard_3-0-0_104076_2016-07-10_final
2016-07-10 10:46:34	ga_ls7e_ard_3-0-0_104077_2016-07-10_final
2016-07-10 10:46:58	ga_ls7e_ard_3-0-0_104078_2016-07-10_final
2016-07-10 10:47:22	ga_ls7e_ard_3-0-0_104079_2016-07-10_final
2016-07-10 10:47:46	ga_ls7e_ard_3-0-0_104080_2016-07-10_final
2016-07-10 10:48:10	ga_ls7e_ard_3-0-0_104081_2016-07-10_final
2016-07-10 10:48:34	ga_ls7e_ard_3-0-0_104082_2016-07-10_final
2016-07-11 09:46:58	ga_ls7e_ard_3-0-0_095067_2016-07-11_final
2016-07-11 09:48:57	ga_ls7e_ard_3-0-0_095072_2016-07-11_final
2016-07-11 09:49:21	ga_ls7e_ard_3-1-0_095073_2016-07-11_final
2016-07-11 09:49:45	ga_ls7e_ard_3-0-0_095074_2016-07-11_final
2016-07-11 09:50:09	ga_ls7e_ard_3-0-0_095075_2016-07-11_final
2016-07-11 09:50:33	ga_ls7e_ard_3-0-0_095076_2016-07-11_final
2016-07-11 09:50:57	ga_ls7e_ard_3-0-0_095077_2016-07-11_final
2016-07-31 09:25:53	ga_ls7e_ard_3-0-0_091076_2016-07-30_final
2016-07-31 09:26:17	ga_ls7e_ard_3-0-0_091077_2016-07-30_final
2016-07-31 09:26:41	ga_ls7e_ard_3-0-0_091078_2016-07-30_final
2016-07-31 09:27:05	ga_ls7e_ard_3-0-0_091079_2016-07-30_final
2016-07-31 09:27:29	ga_ls7e_ard_3-0-0_091080_2016-07-30_final
2016-07-31 09:27:53	ga_ls7e_ard_3-0-0_091081_2016-07-30_final
2016-07-31 09:28:17	ga_ls7e_ard_3-0-0_091082_2016-07-30_final
2016-07-31 09:28:41	ga_ls7e_ard_3-0-0_091083_2016-07-30_final
2016-07-31 09:29:05	ga_ls7e_ard_3-0-0_091084_2016-07-30_final
2016-07-31 09:29:29	ga_ls7e_ard_3-0-0_091085_2016-07-30_final

Return to ga_ls7e_ard_3 across July 2016 overview

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

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2016

July

All days