Search ga_ls7e_ard_3 across September 2017

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
2017-09-04 09:25:53	ga_ls7e_ard_3-0-0_091076_2017-09-03_final
2017-09-04 09:26:17	ga_ls7e_ard_3-0-0_091077_2017-09-03_final
2017-09-04 09:26:41	ga_ls7e_ard_3-0-0_091078_2017-09-03_final
2017-09-04 09:27:05	ga_ls7e_ard_3-0-0_091079_2017-09-03_final
2017-09-04 09:27:29	ga_ls7e_ard_3-0-0_091080_2017-09-03_final
2017-09-04 09:27:53	ga_ls7e_ard_3-0-0_091081_2017-09-03_final
2017-09-04 09:28:17	ga_ls7e_ard_3-0-0_091082_2017-09-03_final
2017-09-04 09:28:41	ga_ls7e_ard_3-0-0_091083_2017-09-03_final
2017-09-04 09:29:05	ga_ls7e_ard_3-0-0_091084_2017-09-03_final
2017-09-04 09:29:29	ga_ls7e_ard_3-0-0_091085_2017-09-03_final
2017-09-04 09:30:17	ga_ls7e_ard_3-0-0_091087_2017-09-04_final
2017-09-04 09:30:41	ga_ls7e_ard_3-0-0_091088_2017-09-04_final
2017-09-06 09:13:55	ga_ls7e_ard_3-0-0_089077_2017-09-05_final
2017-09-06 09:14:19	ga_ls7e_ard_3-0-0_089078_2017-09-05_final
2017-09-06 09:14:43	ga_ls7e_ard_3-0-0_089079_2017-09-05_final
2017-09-06 09:15:07	ga_ls7e_ard_3-0-0_089080_2017-09-05_final
2017-09-06 09:15:31	ga_ls7e_ard_3-1-0_089081_2017-09-05_final
2017-09-06 09:15:55	ga_ls7e_ard_3-0-0_089082_2017-09-05_final
2017-09-06 09:16:19	ga_ls7e_ard_3-0-0_089083_2017-09-05_final
2017-09-06 09:16:43	ga_ls7e_ard_3-0-0_089084_2017-09-05_final
2017-09-06 09:17:07	ga_ls7e_ard_3-0-0_089085_2017-09-05_final
2017-09-06 09:17:31	ga_ls7e_ard_3-0-0_089086_2017-09-05_final
2017-09-20 09:25:51	ga_ls7e_ard_3-0-0_091076_2017-09-19_final
2017-09-20 09:26:15	ga_ls7e_ard_3-0-0_091077_2017-09-19_final
2017-09-20 09:26:39	ga_ls7e_ard_3-0-0_091078_2017-09-19_final
2017-09-20 09:27:03	ga_ls7e_ard_3-0-0_091079_2017-09-19_final
2017-09-20 09:27:27	ga_ls7e_ard_3-0-0_091080_2017-09-19_final
2017-09-20 09:27:51	ga_ls7e_ard_3-0-0_091081_2017-09-19_final
2017-09-20 09:28:15	ga_ls7e_ard_3-0-0_091082_2017-09-19_final
2017-09-20 09:28:39	ga_ls7e_ard_3-0-0_091083_2017-09-19_final
2017-09-20 09:29:03	ga_ls7e_ard_3-0-0_091084_2017-09-19_final
2017-09-20 09:29:27	ga_ls7e_ard_3-0-0_091085_2017-09-19_final
2017-09-20 09:30:14	ga_ls7e_ard_3-0-0_091087_2017-09-20_final
2017-09-20 09:30:38	ga_ls7e_ard_3-0-0_091088_2017-09-20_final
2017-09-20 09:31:02	ga_ls7e_ard_3-0-0_091089_2017-09-20_final
2017-09-20 09:31:26	ga_ls7e_ard_3-0-0_091090_2017-09-20_final
2017-09-20 11:02:20	ga_ls7e_ard_3-0-0_107070_2017-09-20_final
2017-09-20 11:02:44	ga_ls7e_ard_3-0-0_107071_2017-09-20_final
2017-09-20 11:03:08	ga_ls7e_ard_3-0-0_107072_2017-09-20_final
2017-09-20 11:03:32	ga_ls7e_ard_3-0-0_107073_2017-09-20_final
2017-09-20 11:03:56	ga_ls7e_ard_3-0-0_107074_2017-09-20_final
2017-09-20 11:04:20	ga_ls7e_ard_3-0-0_107075_2017-09-20_final
2017-09-20 11:04:44	ga_ls7e_ard_3-0-0_107076_2017-09-20_final
2017-09-20 11:05:08	ga_ls7e_ard_3-0-0_107077_2017-09-20_final
2017-09-20 11:05:32	ga_ls7e_ard_3-0-0_107078_2017-09-20_final
2017-09-20 11:05:56	ga_ls7e_ard_3-0-0_107079_2017-09-20_final
2017-09-20 11:06:20	ga_ls7e_ard_3-0-0_107080_2017-09-20_final
2017-09-20 11:06:44	ga_ls7e_ard_3-0-0_107081_2017-09-20_final
2017-09-20 11:07:08	ga_ls7e_ard_3-0-0_107082_2017-09-20_final
2017-09-20 11:07:32	ga_ls7e_ard_3-0-0_107083_2017-09-20_final
2017-09-21 10:05:31	ga_ls7e_ard_3-0-0_098067_2017-09-21_final
2017-09-21 10:05:55	ga_ls7e_ard_3-0-0_098068_2017-09-21_final
2017-09-21 10:06:19	ga_ls7e_ard_3-0-0_098069_2017-09-21_final
2017-09-21 10:06:43	ga_ls7e_ard_3-0-0_098070_2017-09-21_final
2017-09-21 10:07:07	ga_ls7e_ard_3-0-0_098071_2017-09-21_final
2017-09-21 10:07:31	ga_ls7e_ard_3-0-0_098072_2017-09-21_final
2017-09-21 10:07:55	ga_ls7e_ard_3-0-0_098073_2017-09-21_final
2017-09-21 10:08:19	ga_ls7e_ard_3-0-0_098074_2017-09-21_final
2017-09-21 10:08:43	ga_ls7e_ard_3-0-0_098075_2017-09-21_final
2017-09-21 10:09:07	ga_ls7e_ard_3-0-0_098076_2017-09-21_final
2017-09-21 10:09:31	ga_ls7e_ard_3-0-0_098077_2017-09-21_final
2017-09-21 10:09:55	ga_ls7e_ard_3-0-0_098078_2017-09-21_final
2017-09-21 10:10:19	ga_ls7e_ard_3-0-0_098079_2017-09-21_final
2017-09-21 10:10:43	ga_ls7e_ard_3-0-0_098080_2017-09-21_final
2017-09-21 10:11:07	ga_ls7e_ard_3-0-0_098081_2017-09-21_final
2017-09-21 10:11:31	ga_ls7e_ard_3-0-0_098082_2017-09-21_final
2017-09-21 10:11:55	ga_ls7e_ard_3-0-0_098083_2017-09-21_final
2017-09-21 10:12:18	ga_ls7e_ard_3-0-0_098084_2017-09-21_final
2017-09-21 10:12:42	ga_ls7e_ard_3-0-0_098085_2017-09-21_final
2017-09-21 11:47:12	ga_ls7e_ard_3-0-0_114074_2017-09-21_final
2017-09-21 11:47:36	ga_ls7e_ard_3-0-0_114075_2017-09-21_final
2017-09-21 11:48:00	ga_ls7e_ard_3-0-0_114076_2017-09-21_final
2017-09-21 11:48:24	ga_ls7e_ard_3-0-0_114077_2017-09-21_final
2017-09-21 11:48:48	ga_ls7e_ard_3-0-0_114078_2017-09-21_final
2017-09-21 11:49:12	ga_ls7e_ard_3-0-0_114079_2017-09-21_final
2017-09-21 11:49:36	ga_ls7e_ard_3-0-0_114080_2017-09-21_final
2017-09-22 09:14:18	ga_ls7e_ard_3-0-0_089078_2017-09-21_final
2017-09-22 09:14:42	ga_ls7e_ard_3-0-0_089079_2017-09-21_final
2017-09-22 09:15:06	ga_ls7e_ard_3-0-0_089080_2017-09-21_final
2017-09-22 09:15:29	ga_ls7e_ard_3-1-0_089081_2017-09-21_final
2017-09-22 09:15:53	ga_ls7e_ard_3-0-0_089082_2017-09-21_final
2017-09-22 09:16:17	ga_ls7e_ard_3-0-0_089083_2017-09-21_final
2017-09-22 09:16:41	ga_ls7e_ard_3-0-0_089084_2017-09-21_final
2017-09-22 09:17:05	ga_ls7e_ard_3-0-0_089085_2017-09-21_final
2017-09-22 09:17:29	ga_ls7e_ard_3-0-0_089086_2017-09-21_final
2017-09-22 10:49:11	ga_ls7e_ard_3-0-0_105068_2017-09-22_final
2017-09-22 10:49:35	ga_ls7e_ard_3-0-0_105069_2017-09-22_final
2017-09-22 10:49:59	ga_ls7e_ard_3-0-0_105070_2017-09-22_final
2017-09-22 10:50:23	ga_ls7e_ard_3-0-0_105071_2017-09-22_final
2017-09-22 10:50:47	ga_ls7e_ard_3-0-0_105072_2017-09-22_final
2017-09-22 10:51:11	ga_ls7e_ard_3-0-0_105073_2017-09-22_final
2017-09-22 10:51:35	ga_ls7e_ard_3-0-0_105074_2017-09-22_final
2017-09-22 10:51:59	ga_ls7e_ard_3-0-0_105075_2017-09-22_final
2017-09-22 10:52:23	ga_ls7e_ard_3-0-0_105076_2017-09-22_final
2017-09-22 10:52:47	ga_ls7e_ard_3-0-0_105077_2017-09-22_final
2017-09-22 10:53:11	ga_ls7e_ard_3-0-0_105078_2017-09-22_final
2017-09-22 10:53:35	ga_ls7e_ard_3-0-0_105079_2017-09-22_final
2017-09-22 10:53:59	ga_ls7e_ard_3-1-0_105080_2017-09-22_final
2017-09-22 10:54:22	ga_ls7e_ard_3-0-0_105081_2017-09-22_final
2017-09-22 10:54:46	ga_ls7e_ard_3-0-0_105082_2017-09-22_final

Return to ga_ls7e_ard_3 across September 2017 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

2017

September

All days