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
2016-07-03 10:36:49	ga_ls7e_ard_3-0-0_103068_2016-07-03_final
2016-07-03 10:37:13	ga_ls7e_ard_3-0-0_103069_2016-07-03_final
2016-07-03 10:37:37	ga_ls7e_ard_3-0-0_103070_2016-07-03_final
2016-07-03 10:38:01	ga_ls7e_ard_3-0-0_103071_2016-07-03_final
2016-07-03 10:38:24	ga_ls7e_ard_3-0-0_103072_2016-07-03_final
2016-07-03 10:38:48	ga_ls7e_ard_3-0-0_103073_2016-07-03_final
2016-07-03 10:39:12	ga_ls7e_ard_3-0-0_103074_2016-07-03_final
2016-07-03 10:39:36	ga_ls7e_ard_3-0-0_103075_2016-07-03_final
2016-07-03 10:40:00	ga_ls7e_ard_3-0-0_103076_2016-07-03_final
2016-07-03 10:40:24	ga_ls7e_ard_3-0-0_103077_2016-07-03_final
2016-07-03 10:40:48	ga_ls7e_ard_3-0-0_103078_2016-07-03_final
2016-07-03 10:41:12	ga_ls7e_ard_3-0-0_103079_2016-07-03_final
2016-07-03 10:41:36	ga_ls7e_ard_3-0-0_103080_2016-07-03_final
2016-07-03 10:42:00	ga_ls7e_ard_3-0-0_103081_2016-07-03_final
2016-07-03 10:42:24	ga_ls7e_ard_3-0-0_103082_2016-07-03_final
2016-07-04 09:40:47	ga_ls7e_ard_3-1-0_094067_2016-07-04_final
2016-07-04 09:45:11	ga_ls7e_ard_3-0-0_094078_2016-07-04_final
2016-07-04 09:45:35	ga_ls7e_ard_3-0-0_094079_2016-07-04_final
2016-07-04 09:45:59	ga_ls7e_ard_3-0-0_094080_2016-07-04_final
2016-07-04 09:46:23	ga_ls7e_ard_3-0-0_094081_2016-07-04_final
2016-07-04 09:46:47	ga_ls7e_ard_3-0-0_094082_2016-07-04_final
2016-07-04 11:19:40	ga_ls7e_ard_3-0-0_110067_2016-07-04_final
2016-07-04 11:20:52	ga_ls7e_ard_3-0-0_110070_2016-07-04_final
2016-07-04 11:21:16	ga_ls7e_ard_3-0-0_110071_2016-07-04_final
2016-07-04 11:21:40	ga_ls7e_ard_3-1-0_110072_2016-07-04_final
2016-07-04 11:22:04	ga_ls7e_ard_3-0-0_110073_2016-07-04_final
2016-07-04 11:22:28	ga_ls7e_ard_3-0-0_110074_2016-07-04_final
2016-07-04 11:24:04	ga_ls7e_ard_3-0-0_110078_2016-07-04_final
2016-07-04 11:24:28	ga_ls7e_ard_3-0-0_110079_2016-07-04_final
2016-07-04 11:25:40	ga_ls7e_ard_3-0-0_110082_2016-07-04_final
2016-07-04 11:26:04	ga_ls7e_ard_3-0-0_110083_2016-07-04_final
2016-07-04 11:26:27	ga_ls7e_ard_3-0-0_110084_2016-07-04_final
2016-07-05 10:25:39	ga_ls7e_ard_3-0-0_101071_2016-07-05_final
2016-07-05 10:26:03	ga_ls7e_ard_3-0-0_101072_2016-07-05_final
2016-07-05 10:26:27	ga_ls7e_ard_3-0-0_101073_2016-07-05_final
2016-07-05 10:26:51	ga_ls7e_ard_3-0-0_101074_2016-07-05_final
2016-07-05 10:27:15	ga_ls7e_ard_3-1-0_101075_2016-07-05_final
2016-07-05 10:27:38	ga_ls7e_ard_3-0-0_101076_2016-07-05_final
2016-07-05 10:28:02	ga_ls7e_ard_3-0-0_101077_2016-07-05_final
2016-07-05 10:28:26	ga_ls7e_ard_3-0-0_101078_2016-07-05_final
2016-07-05 10:28:50	ga_ls7e_ard_3-0-0_101079_2016-07-05_final
2016-07-05 10:29:14	ga_ls7e_ard_3-0-0_101080_2016-07-05_final
2016-07-05 10:29:38	ga_ls7e_ard_3-0-0_101081_2016-07-05_final
2016-07-05 10:30:02	ga_ls7e_ard_3-0-0_101082_2016-07-05_final
2016-07-05 10:30:26	ga_ls7e_ard_3-0-0_101083_2016-07-05_final
2016-07-06 09:31:37	ga_ls7e_ard_3-0-0_092075_2016-07-06_final
2016-07-06 09:32:01	ga_ls7e_ard_3-0-0_092076_2016-07-06_final
2016-07-06 09:32:25	ga_ls7e_ard_3-0-0_092077_2016-07-06_final
2016-07-06 09:32:49	ga_ls7e_ard_3-0-0_092078_2016-07-06_final
2016-07-06 09:33:13	ga_ls7e_ard_3-0-0_092079_2016-07-06_final
2016-07-06 09:33:37	ga_ls7e_ard_3-0-0_092080_2016-07-06_final
2016-07-06 09:34:01	ga_ls7e_ard_3-0-0_092081_2016-07-06_final
2016-07-06 09:35:13	ga_ls7e_ard_3-0-0_092084_2016-07-06_final
2016-07-06 09:35:37	ga_ls7e_ard_3-0-0_092085_2016-07-06_final
2016-07-06 09:36:49	ga_ls7e_ard_3-0-0_092088_2016-07-06_final
2016-07-06 09:37:12	ga_ls7e_ard_3-0-0_092089_2016-07-06_final
2016-07-06 11:08:07	ga_ls7e_ard_3-0-0_108069_2016-07-06_final
2016-07-06 11:08:31	ga_ls7e_ard_3-0-0_108070_2016-07-06_final
2016-07-06 11:08:54	ga_ls7e_ard_3-0-0_108071_2016-07-06_final
2016-07-06 11:09:18	ga_ls7e_ard_3-0-0_108072_2016-07-06_final
2016-07-06 11:09:42	ga_ls7e_ard_3-0-0_108073_2016-07-06_final
2016-07-06 11:10:06	ga_ls7e_ard_3-0-0_108074_2016-07-06_final
2016-07-06 11:10:30	ga_ls7e_ard_3-1-0_108075_2016-07-06_final
2016-07-06 11:13:18	ga_ls7e_ard_3-0-0_108082_2016-07-06_final
2016-07-06 11:13:42	ga_ls7e_ard_3-0-0_108083_2016-07-06_final
2016-07-06 11:14:06	ga_ls7e_ard_3-0-0_108084_2016-07-06_final
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
2016-07-08 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
2016-07-09 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

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2016

July

All days