Search ga_ls7e_ard_3 across August 2018

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
2018-08-22 09:24:54	ga_ls7e_ard_3-0-0_091084_2018-08-21_final
2018-08-22 09:25:18	ga_ls7e_ard_3-0-0_091085_2018-08-21_final
2018-08-22 09:25:42	ga_ls7e_ard_3-1-0_091086_2018-08-21_final
2018-08-22 09:26:06	ga_ls7e_ard_3-0-0_091087_2018-08-21_final
2018-08-24 09:10:07	ga_ls7e_ard_3-0-0_089078_2018-08-23_final
2018-08-24 09:10:31	ga_ls7e_ard_3-0-0_089079_2018-08-23_final
2018-08-24 09:10:55	ga_ls7e_ard_3-0-0_089080_2018-08-23_final
2018-08-24 09:11:18	ga_ls7e_ard_3-1-0_089081_2018-08-23_final
2018-08-24 09:11:42	ga_ls7e_ard_3-0-0_089082_2018-08-23_final
2018-08-24 09:12:06	ga_ls7e_ard_3-0-0_089083_2018-08-23_final
2018-08-24 09:12:30	ga_ls7e_ard_3-0-0_089084_2018-08-23_final
2018-08-24 09:12:54	ga_ls7e_ard_3-0-0_089085_2018-08-23_final
2018-08-24 09:13:18	ga_ls7e_ard_3-0-0_089086_2018-08-23_final
2018-08-26 10:32:36	ga_ls7e_ard_3-0-0_103068_2018-08-26_final
2018-08-26 10:33:00	ga_ls7e_ard_3-0-0_103069_2018-08-26_final
2018-08-26 10:33:24	ga_ls7e_ard_3-0-0_103070_2018-08-26_final
2018-08-26 10:33:48	ga_ls7e_ard_3-0-0_103071_2018-08-26_final
2018-08-26 10:34:12	ga_ls7e_ard_3-0-0_103072_2018-08-26_final
2018-08-26 10:34:36	ga_ls7e_ard_3-0-0_103073_2018-08-26_final
2018-08-26 10:35:00	ga_ls7e_ard_3-0-0_103074_2018-08-26_final
2018-08-26 10:35:24	ga_ls7e_ard_3-0-0_103075_2018-08-26_final
2018-08-26 10:35:48	ga_ls7e_ard_3-0-0_103076_2018-08-26_final
2018-08-26 10:36:12	ga_ls7e_ard_3-0-0_103077_2018-08-26_final
2018-08-26 10:36:36	ga_ls7e_ard_3-0-0_103078_2018-08-26_final
2018-08-26 10:36:59	ga_ls7e_ard_3-0-0_103079_2018-08-26_final
2018-08-26 10:37:23	ga_ls7e_ard_3-0-0_103080_2018-08-26_final
2018-08-26 10:37:47	ga_ls7e_ard_3-0-0_103081_2018-08-26_final
2018-08-26 10:38:11	ga_ls7e_ard_3-0-0_103082_2018-08-26_final
2018-08-27 09:36:34	ga_ls7e_ard_3-1-0_094067_2018-08-27_final
2018-08-27 09:38:57	ga_ls7e_ard_3-0-0_094073_2018-08-27_final
2018-08-27 09:39:21	ga_ls7e_ard_3-0-0_094074_2018-08-27_final
2018-08-27 09:39:45	ga_ls7e_ard_3-0-0_094075_2018-08-27_final
2018-08-27 09:40:09	ga_ls7e_ard_3-0-0_094076_2018-08-27_final
2018-08-27 09:40:33	ga_ls7e_ard_3-0-0_094077_2018-08-27_final
2018-08-27 09:40:57	ga_ls7e_ard_3-0-0_094078_2018-08-27_final
2018-08-27 09:41:21	ga_ls7e_ard_3-0-0_094079_2018-08-27_final
2018-08-27 09:41:45	ga_ls7e_ard_3-0-0_094080_2018-08-27_final
2018-08-27 09:42:09	ga_ls7e_ard_3-0-0_094081_2018-08-27_final
2018-08-27 09:42:33	ga_ls7e_ard_3-0-0_094082_2018-08-27_final
2018-08-27 09:42:57	ga_ls7e_ard_3-0-0_094083_2018-08-27_final
2018-08-27 09:43:21	ga_ls7e_ard_3-0-0_094084_2018-08-27_final
2018-08-27 09:43:45	ga_ls7e_ard_3-0-0_094085_2018-08-27_final
2018-08-27 09:44:09	ga_ls7e_ard_3-0-0_094086_2018-08-27_final
2018-08-27 09:44:33	ga_ls7e_ard_3-0-0_094087_2018-08-27_final
2018-08-27 11:15:27	ga_ls7e_ard_3-0-0_110067_2018-08-27_final
2018-08-27 11:16:38	ga_ls7e_ard_3-0-0_110070_2018-08-27_final
2018-08-27 11:17:02	ga_ls7e_ard_3-0-0_110071_2018-08-27_final
2018-08-27 11:17:26	ga_ls7e_ard_3-1-0_110072_2018-08-27_final
2018-08-27 11:17:50	ga_ls7e_ard_3-0-0_110073_2018-08-27_final
2018-08-27 11:18:14	ga_ls7e_ard_3-0-0_110074_2018-08-27_final
2018-08-27 11:18:38	ga_ls7e_ard_3-0-0_110075_2018-08-27_final
2018-08-27 11:19:02	ga_ls7e_ard_3-0-0_110076_2018-08-27_final
2018-08-27 11:19:26	ga_ls7e_ard_3-0-0_110077_2018-08-27_final
2018-08-27 11:19:50	ga_ls7e_ard_3-0-0_110078_2018-08-27_final
2018-08-27 11:20:14	ga_ls7e_ard_3-0-0_110079_2018-08-27_final
2018-08-27 11:20:38	ga_ls7e_ard_3-0-0_110080_2018-08-27_final
2018-08-27 11:21:02	ga_ls7e_ard_3-0-0_110081_2018-08-27_final
2018-08-27 11:21:26	ga_ls7e_ard_3-0-0_110082_2018-08-27_final
2018-08-27 11:21:50	ga_ls7e_ard_3-0-0_110083_2018-08-27_final
2018-08-27 11:22:14	ga_ls7e_ard_3-0-0_110084_2018-08-27_final
2018-08-28 10:21:24	ga_ls7e_ard_3-0-0_101071_2018-08-28_final
2018-08-28 10:21:48	ga_ls7e_ard_3-0-0_101072_2018-08-28_final
2018-08-28 10:22:12	ga_ls7e_ard_3-0-0_101073_2018-08-28_final
2018-08-28 10:22:36	ga_ls7e_ard_3-0-0_101074_2018-08-28_final
2018-08-28 10:23:00	ga_ls7e_ard_3-1-0_101075_2018-08-28_final
2018-08-28 10:23:24	ga_ls7e_ard_3-0-0_101076_2018-08-28_final
2018-08-28 10:23:47	ga_ls7e_ard_3-0-0_101077_2018-08-28_final
2018-08-28 10:24:11	ga_ls7e_ard_3-0-0_101078_2018-08-28_final
2018-08-28 10:24:35	ga_ls7e_ard_3-0-0_101079_2018-08-28_final
2018-08-28 10:24:59	ga_ls7e_ard_3-0-0_101080_2018-08-28_final
2018-08-28 10:25:23	ga_ls7e_ard_3-0-0_101081_2018-08-28_final
2018-08-28 10:25:47	ga_ls7e_ard_3-0-0_101082_2018-08-28_final
2018-08-28 10:26:11	ga_ls7e_ard_3-0-0_101083_2018-08-28_final
2018-08-29 09:27:21	ga_ls7e_ard_3-0-0_092075_2018-08-28_final
2018-08-29 09:27:45	ga_ls7e_ard_3-0-0_092076_2018-08-28_final
2018-08-29 09:28:09	ga_ls7e_ard_3-0-0_092077_2018-08-28_final
2018-08-29 09:28:33	ga_ls7e_ard_3-0-0_092078_2018-08-28_final
2018-08-29 09:28:57	ga_ls7e_ard_3-0-0_092079_2018-08-28_final
2018-08-29 09:29:21	ga_ls7e_ard_3-0-0_092080_2018-08-28_final
2018-08-29 09:29:45	ga_ls7e_ard_3-0-0_092081_2018-08-28_final
2018-08-29 09:30:33	ga_ls7e_ard_3-0-0_092083_2018-08-29_final
2018-08-29 09:30:57	ga_ls7e_ard_3-0-0_092084_2018-08-29_final
2018-08-29 09:31:21	ga_ls7e_ard_3-0-0_092085_2018-08-29_final
2018-08-29 09:31:45	ga_ls7e_ard_3-0-0_092086_2018-08-29_final
2018-08-29 09:32:08	ga_ls7e_ard_3-0-0_092087_2018-08-29_final
2018-08-29 09:32:32	ga_ls7e_ard_3-0-0_092088_2018-08-29_final
2018-08-29 09:32:56	ga_ls7e_ard_3-0-0_092089_2018-08-29_final
2018-08-29 11:03:50	ga_ls7e_ard_3-0-0_108069_2018-08-29_final
2018-08-29 11:04:14	ga_ls7e_ard_3-0-0_108070_2018-08-29_final
2018-08-29 11:04:38	ga_ls7e_ard_3-1-0_108071_2018-08-29_final
2018-08-29 11:05:02	ga_ls7e_ard_3-0-0_108072_2018-08-29_final
2018-08-29 11:05:26	ga_ls7e_ard_3-0-0_108073_2018-08-29_final
2018-08-29 11:05:50	ga_ls7e_ard_3-0-0_108074_2018-08-29_final
2018-08-29 11:06:14	ga_ls7e_ard_3-1-0_108075_2018-08-29_final
2018-08-29 11:06:38	ga_ls7e_ard_3-0-0_108076_2018-08-29_final
2018-08-29 11:07:02	ga_ls7e_ard_3-0-0_108077_2018-08-29_final
2018-08-29 11:07:26	ga_ls7e_ard_3-0-0_108078_2018-08-29_final
2018-08-29 11:08:38	ga_ls7e_ard_3-0-0_108081_2018-08-29_final
2018-08-29 11:09:02	ga_ls7e_ard_3-0-0_108082_2018-08-29_final
2018-08-29 11:09:26	ga_ls7e_ard_3-0-0_108083_2018-08-29_final

Return to ga_ls7e_ard_3 across August 2018 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

2018

August

All days