Search ga_ls7e_ard_3 across November 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
2016-11-04 09:25:55	ga_ls7e_ard_3-0-0_091076_2016-11-03_final
2016-11-04 09:26:19	ga_ls7e_ard_3-0-0_091077_2016-11-03_final
2016-11-04 09:26:43	ga_ls7e_ard_3-0-0_091078_2016-11-03_final
2016-11-04 09:27:07	ga_ls7e_ard_3-0-0_091079_2016-11-03_final
2016-11-04 09:27:31	ga_ls7e_ard_3-0-0_091080_2016-11-03_final
2016-11-04 09:27:55	ga_ls7e_ard_3-0-0_091081_2016-11-03_final
2016-11-04 09:28:19	ga_ls7e_ard_3-0-0_091082_2016-11-03_final
2016-11-04 09:28:43	ga_ls7e_ard_3-0-0_091083_2016-11-03_final
2016-11-04 09:29:07	ga_ls7e_ard_3-0-0_091084_2016-11-03_final
2016-11-04 09:29:31	ga_ls7e_ard_3-0-0_091085_2016-11-03_final
2016-11-08 10:36:51	ga_ls7e_ard_3-0-0_103068_2016-11-08_final
2016-11-08 10:37:15	ga_ls7e_ard_3-0-0_103069_2016-11-08_final
2016-11-08 10:37:39	ga_ls7e_ard_3-0-0_103070_2016-11-08_final
2016-11-08 10:38:03	ga_ls7e_ard_3-0-0_103071_2016-11-08_final
2016-11-08 10:38:27	ga_ls7e_ard_3-0-0_103072_2016-11-08_final
2016-11-08 10:38:51	ga_ls7e_ard_3-0-0_103073_2016-11-08_final
2016-11-08 10:39:15	ga_ls7e_ard_3-0-0_103074_2016-11-08_final
2016-11-08 10:39:39	ga_ls7e_ard_3-0-0_103075_2016-11-08_final
2016-11-08 10:40:03	ga_ls7e_ard_3-0-0_103076_2016-11-08_final
2016-11-08 10:40:27	ga_ls7e_ard_3-0-0_103077_2016-11-08_final
2016-11-08 10:40:51	ga_ls7e_ard_3-0-0_103078_2016-11-08_final
2016-11-08 10:41:15	ga_ls7e_ard_3-0-0_103079_2016-11-08_final
2016-11-08 10:41:39	ga_ls7e_ard_3-0-0_103080_2016-11-08_final
2016-11-08 10:42:03	ga_ls7e_ard_3-0-0_103081_2016-11-08_final
2016-11-09 09:40:50	ga_ls7e_ard_3-1-0_094067_2016-11-09_final
2016-11-09 09:43:13	ga_ls7e_ard_3-0-0_094073_2016-11-09_final
2016-11-09 09:43:37	ga_ls7e_ard_3-0-0_094074_2016-11-09_final
2016-11-09 09:44:01	ga_ls7e_ard_3-0-0_094075_2016-11-09_final
2016-11-09 09:44:25	ga_ls7e_ard_3-0-0_094076_2016-11-09_final
2016-11-09 09:44:49	ga_ls7e_ard_3-0-0_094077_2016-11-09_final
2016-11-09 09:45:13	ga_ls7e_ard_3-0-0_094078_2016-11-09_final
2016-11-09 09:45:37	ga_ls7e_ard_3-0-0_094079_2016-11-09_final
2016-11-09 09:46:01	ga_ls7e_ard_3-0-0_094080_2016-11-09_final
2016-11-09 09:46:25	ga_ls7e_ard_3-0-0_094081_2016-11-09_final
2016-11-09 09:46:49	ga_ls7e_ard_3-0-0_094082_2016-11-09_final
2016-11-09 09:47:13	ga_ls7e_ard_3-0-0_094083_2016-11-09_final
2016-11-09 09:47:37	ga_ls7e_ard_3-0-0_094084_2016-11-09_final
2016-11-09 09:48:01	ga_ls7e_ard_3-0-0_094085_2016-11-09_final
2016-11-09 09:48:24	ga_ls7e_ard_3-0-0_094086_2016-11-09_final
2016-11-09 09:48:48	ga_ls7e_ard_3-0-0_094087_2016-11-09_final
2016-11-09 11:19:43	ga_ls7e_ard_3-0-0_110067_2016-11-09_final
2016-11-09 11:20:54	ga_ls7e_ard_3-0-0_110070_2016-11-09_final
2016-11-09 11:21:18	ga_ls7e_ard_3-0-0_110071_2016-11-09_final
2016-11-09 11:21:42	ga_ls7e_ard_3-1-0_110072_2016-11-09_final
2016-11-09 11:22:06	ga_ls7e_ard_3-0-0_110073_2016-11-09_final
2016-11-09 11:22:30	ga_ls7e_ard_3-0-0_110074_2016-11-09_final
2016-11-09 11:22:54	ga_ls7e_ard_3-0-0_110075_2016-11-09_final
2016-11-09 11:23:18	ga_ls7e_ard_3-0-0_110076_2016-11-09_final
2016-11-09 11:23:42	ga_ls7e_ard_3-0-0_110077_2016-11-09_final
2016-11-09 11:24:06	ga_ls7e_ard_3-0-0_110078_2016-11-09_final
2016-11-09 11:24:30	ga_ls7e_ard_3-0-0_110079_2016-11-09_final
2016-11-09 11:24:54	ga_ls7e_ard_3-0-0_110080_2016-11-09_final
2016-11-09 11:25:18	ga_ls7e_ard_3-0-0_110081_2016-11-09_final
2016-11-09 11:25:42	ga_ls7e_ard_3-0-0_110082_2016-11-09_final
2016-11-09 11:26:06	ga_ls7e_ard_3-0-0_110083_2016-11-09_final
2016-11-10 10:25:40	ga_ls7e_ard_3-0-0_101071_2016-11-10_final
2016-11-10 10:26:04	ga_ls7e_ard_3-0-0_101072_2016-11-10_final
2016-11-10 10:26:28	ga_ls7e_ard_3-0-0_101073_2016-11-10_final
2016-11-10 10:27:16	ga_ls7e_ard_3-1-0_101075_2016-11-10_final
2016-11-10 10:27:40	ga_ls7e_ard_3-0-0_101076_2016-11-10_final
2016-11-10 10:28:28	ga_ls7e_ard_3-0-0_101078_2016-11-10_final
2016-11-10 10:28:52	ga_ls7e_ard_3-0-0_101079_2016-11-10_final
2016-11-10 10:29:16	ga_ls7e_ard_3-0-0_101080_2016-11-10_final
2016-11-10 10:29:40	ga_ls7e_ard_3-0-0_101081_2016-11-10_final
2016-11-10 10:30:04	ga_ls7e_ard_3-0-0_101082_2016-11-10_final
2016-11-11 09:31:38	ga_ls7e_ard_3-0-0_092075_2016-11-11_final
2016-11-11 09:32:02	ga_ls7e_ard_3-0-0_092076_2016-11-11_final
2016-11-11 09:32:26	ga_ls7e_ard_3-0-0_092077_2016-11-11_final
2016-11-11 09:32:50	ga_ls7e_ard_3-0-0_092078_2016-11-11_final
2016-11-11 09:33:14	ga_ls7e_ard_3-0-0_092079_2016-11-11_final
2016-11-11 09:33:38	ga_ls7e_ard_3-0-0_092080_2016-11-11_final
2016-11-11 09:34:02	ga_ls7e_ard_3-0-0_092081_2016-11-11_final
2016-11-11 09:34:26	ga_ls7e_ard_3-0-0_092082_2016-11-11_final
2016-11-11 09:34:50	ga_ls7e_ard_3-0-0_092083_2016-11-11_final
2016-11-11 09:35:14	ga_ls7e_ard_3-0-0_092084_2016-11-11_final
2016-11-11 09:35:38	ga_ls7e_ard_3-0-0_092085_2016-11-11_final
2016-11-11 09:36:02	ga_ls7e_ard_3-0-0_092086_2016-11-11_final
2016-11-11 09:36:26	ga_ls7e_ard_3-0-0_092087_2016-11-11_final
2016-11-11 11:08:08	ga_ls7e_ard_3-0-0_108069_2016-11-11_final
2016-11-11 11:08:32	ga_ls7e_ard_3-0-0_108070_2016-11-11_final
2016-11-11 11:08:56	ga_ls7e_ard_3-1-0_108071_2016-11-11_final
2016-11-11 11:09:19	ga_ls7e_ard_3-0-0_108072_2016-11-11_final
2016-11-11 11:09:43	ga_ls7e_ard_3-0-0_108073_2016-11-11_final
2016-11-11 11:10:07	ga_ls7e_ard_3-0-0_108074_2016-11-11_final
2016-11-11 11:10:31	ga_ls7e_ard_3-1-0_108075_2016-11-11_final
2016-11-11 11:10:55	ga_ls7e_ard_3-0-0_108076_2016-11-11_final
2016-11-11 11:11:19	ga_ls7e_ard_3-0-0_108077_2016-11-11_final
2016-11-11 11:11:43	ga_ls7e_ard_3-0-0_108078_2016-11-11_final
2016-11-11 11:12:07	ga_ls7e_ard_3-0-0_108079_2016-11-11_final
2016-11-11 11:12:31	ga_ls7e_ard_3-0-0_108080_2016-11-11_final
2016-11-11 11:12:55	ga_ls7e_ard_3-0-0_108081_2016-11-11_final
2016-11-11 11:13:19	ga_ls7e_ard_3-1-0_108082_2016-11-11_final
2016-11-11 11:13:43	ga_ls7e_ard_3-0-0_108083_2016-11-11_final
2016-11-11 11:14:07	ga_ls7e_ard_3-0-0_108084_2016-11-11_final
2016-11-12 10:11:42	ga_ls7e_ard_3-0-0_099067_2016-11-12_final
2016-11-12 10:12:06	ga_ls7e_ard_3-0-0_099068_2016-11-12_final
2016-11-12 10:12:30	ga_ls7e_ard_3-0-0_099069_2016-11-12_final
2016-11-12 10:12:54	ga_ls7e_ard_3-0-0_099070_2016-11-12_final
2016-11-12 10:13:18	ga_ls7e_ard_3-0-0_099071_2016-11-12_final
2016-11-12 10:13:42	ga_ls7e_ard_3-0-0_099072_2016-11-12_final

Return to ga_ls7e_ard_3 across November 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

November

All days