Search ga_ls7e_ard_3 across 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
2017-01-04 10:30:20	ga_ls7e_ard_3-0-0_102068_2017-01-04_final
2017-01-04 10:30:44	ga_ls7e_ard_3-1-0_102069_2017-01-04_final
2017-01-04 10:31:08	ga_ls7e_ard_3-0-0_102070_2017-01-04_final
2017-01-04 10:31:32	ga_ls7e_ard_3-0-0_102071_2017-01-04_final
2017-01-04 10:31:56	ga_ls7e_ard_3-0-0_102072_2017-01-04_final
2017-01-04 10:33:07	ga_ls7e_ard_3-0-0_102075_2017-01-04_final
2017-01-04 10:33:31	ga_ls7e_ard_3-0-0_102076_2017-01-04_final
2017-01-04 10:33:55	ga_ls7e_ard_3-0-0_102077_2017-01-04_final
2017-01-04 10:34:19	ga_ls7e_ard_3-0-0_102078_2017-01-04_final
2017-01-04 10:34:43	ga_ls7e_ard_3-0-0_102079_2017-01-04_final
2017-01-04 10:35:07	ga_ls7e_ard_3-0-0_102080_2017-01-04_final
2017-01-04 10:35:31	ga_ls7e_ard_3-0-0_102081_2017-01-04_final
2017-01-04 10:35:55	ga_ls7e_ard_3-0-0_102082_2017-01-04_final
2017-01-05 09:37:06	ga_ls7e_ard_3-0-0_093074_2017-01-05_final
2017-01-05 09:37:30	ga_ls7e_ard_3-0-0_093075_2017-01-05_final
2017-01-05 09:38:41	ga_ls7e_ard_3-0-0_093078_2017-01-05_final
2017-01-05 09:39:05	ga_ls7e_ard_3-0-0_093079_2017-01-05_final
2017-01-05 09:39:29	ga_ls7e_ard_3-0-0_093080_2017-01-05_final
2017-01-05 09:39:53	ga_ls7e_ard_3-0-0_093081_2017-01-05_final
2017-01-05 09:40:17	ga_ls7e_ard_3-0-0_093082_2017-01-05_final
2017-01-05 09:40:41	ga_ls7e_ard_3-0-0_093083_2017-01-05_final
2017-01-05 09:41:05	ga_ls7e_ard_3-0-0_093084_2017-01-05_final
2017-01-05 09:41:29	ga_ls7e_ard_3-0-0_093085_2017-01-05_final
2017-01-05 09:41:53	ga_ls7e_ard_3-0-0_093086_2017-01-05_final
2017-01-05 09:42:17	ga_ls7e_ard_3-1-0_093087_2017-01-05_final
2017-01-05 09:42:41	ga_ls7e_ard_3-0-0_093088_2017-01-05_final
2017-01-05 11:14:23	ga_ls7e_ard_3-0-0_109070_2017-01-05_final
2017-01-05 11:16:47	ga_ls7e_ard_3-0-0_109076_2017-01-05_final
2017-01-05 11:17:10	ga_ls7e_ard_3-0-0_109077_2017-01-05_final
2017-01-05 11:17:34	ga_ls7e_ard_3-0-0_109078_2017-01-05_final
2017-01-05 11:17:58	ga_ls7e_ard_3-0-0_109079_2017-01-05_final
2017-01-05 11:18:22	ga_ls7e_ard_3-0-0_109080_2017-01-05_final
2017-01-06 10:19:57	ga_ls7e_ard_3-0-0_100073_2017-01-06_final
2017-01-06 10:20:21	ga_ls7e_ard_3-0-0_100074_2017-01-06_final
2017-01-06 10:20:45	ga_ls7e_ard_3-0-0_100075_2017-01-06_final
2017-01-06 10:21:09	ga_ls7e_ard_3-0-0_100076_2017-01-06_final
2017-01-06 10:21:33	ga_ls7e_ard_3-0-0_100077_2017-01-06_final
2017-01-06 10:21:56	ga_ls7e_ard_3-0-0_100078_2017-01-06_final
2017-01-06 10:22:20	ga_ls7e_ard_3-0-0_100079_2017-01-06_final
2017-01-06 10:22:44	ga_ls7e_ard_3-0-0_100080_2017-01-06_final
2017-01-06 10:23:08	ga_ls7e_ard_3-0-0_100081_2017-01-06_final
2017-01-06 10:23:32	ga_ls7e_ard_3-0-0_100082_2017-01-06_final
2017-01-06 10:23:56	ga_ls7e_ard_3-0-0_100083_2017-01-06_final
2017-01-06 10:24:20	ga_ls7e_ard_3-0-0_100084_2017-01-06_final
2017-01-07 09:26:43	ga_ls7e_ard_3-0-0_091079_2017-01-06_final
2017-01-07 09:27:06	ga_ls7e_ard_3-0-0_091080_2017-01-06_final
2017-01-07 09:27:30	ga_ls7e_ard_3-0-0_091081_2017-01-06_final
2017-01-07 09:27:54	ga_ls7e_ard_3-0-0_091082_2017-01-06_final
2017-01-07 09:28:18	ga_ls7e_ard_3-0-0_091083_2017-01-06_final
2017-01-07 09:28:42	ga_ls7e_ard_3-0-0_091084_2017-01-06_final
2017-01-07 09:29:06	ga_ls7e_ard_3-0-0_091085_2017-01-06_final
2017-01-07 09:29:30	ga_ls7e_ard_3-1-0_091086_2017-01-06_final
2017-01-07 09:29:54	ga_ls7e_ard_3-1-0_091087_2017-01-06_final
2017-01-07 09:30:18	ga_ls7e_ard_3-0-0_091088_2017-01-07_final
2017-01-07 09:30:42	ga_ls7e_ard_3-0-0_091089_2017-01-07_final
2017-01-07 09:31:06	ga_ls7e_ard_3-0-0_091090_2017-01-07_final
2017-01-07 11:02:00	ga_ls7e_ard_3-0-0_107070_2017-01-07_final
2017-01-07 11:02:24	ga_ls7e_ard_3-0-0_107071_2017-01-07_final
2017-01-07 11:02:48	ga_ls7e_ard_3-0-0_107072_2017-01-07_final
2017-01-07 11:03:12	ga_ls7e_ard_3-0-0_107073_2017-01-07_final
2017-01-07 11:03:36	ga_ls7e_ard_3-0-0_107074_2017-01-07_final
2017-01-07 11:06:23	ga_ls7e_ard_3-0-0_107081_2017-01-07_final
2017-01-07 11:06:47	ga_ls7e_ard_3-0-0_107082_2017-01-07_final
2017-01-07 11:07:11	ga_ls7e_ard_3-0-0_107083_2017-01-07_final
2017-01-07 11:07:35	ga_ls7e_ard_3-0-0_107084_2017-01-07_final
2017-01-08 10:05:34	ga_ls7e_ard_3-0-0_098068_2017-01-08_final
2017-01-08 10:05:58	ga_ls7e_ard_3-0-0_098069_2017-01-08_final
2017-01-08 10:07:58	ga_ls7e_ard_3-0-0_098074_2017-01-08_final
2017-01-08 10:08:22	ga_ls7e_ard_3-0-0_098075_2017-01-08_final
2017-01-08 10:08:46	ga_ls7e_ard_3-0-0_098076_2017-01-08_final
2017-01-08 10:09:10	ga_ls7e_ard_3-0-0_098077_2017-01-08_final
2017-01-08 10:09:34	ga_ls7e_ard_3-0-0_098078_2017-01-08_final
2017-01-08 10:09:58	ga_ls7e_ard_3-0-0_098079_2017-01-08_final
2017-01-08 10:10:22	ga_ls7e_ard_3-1-0_098080_2017-01-08_final
2017-01-08 10:10:45	ga_ls7e_ard_3-0-0_098081_2017-01-08_final
2017-01-08 10:11:09	ga_ls7e_ard_3-0-0_098082_2017-01-08_final
2017-01-08 10:11:57	ga_ls7e_ard_3-0-0_098084_2017-01-08_final
2017-01-08 10:12:21	ga_ls7e_ard_3-0-0_098085_2017-01-08_final
2017-01-08 11:46:51	ga_ls7e_ard_3-0-0_114074_2017-01-08_final
2017-01-08 11:47:15	ga_ls7e_ard_3-0-0_114075_2017-01-08_final
2017-01-08 11:47:39	ga_ls7e_ard_3-0-0_114076_2017-01-08_final
2017-01-08 11:48:03	ga_ls7e_ard_3-0-0_114077_2017-01-08_final
2017-01-08 11:48:27	ga_ls7e_ard_3-0-0_114078_2017-01-08_final
2017-01-08 11:48:51	ga_ls7e_ard_3-0-0_114079_2017-01-08_final
2017-01-08 11:49:15	ga_ls7e_ard_3-0-0_114080_2017-01-08_final
2017-01-09 10:48:49	ga_ls7e_ard_3-0-0_105068_2017-01-09_final
2017-01-09 10:49:13	ga_ls7e_ard_3-0-0_105069_2017-01-09_final
2017-01-09 10:49:37	ga_ls7e_ard_3-0-0_105070_2017-01-09_final
2017-01-09 10:50:01	ga_ls7e_ard_3-0-0_105071_2017-01-09_final
2017-01-09 10:50:25	ga_ls7e_ard_3-0-0_105072_2017-01-09_final
2017-01-09 10:50:49	ga_ls7e_ard_3-0-0_105073_2017-01-09_final
2017-01-09 10:51:13	ga_ls7e_ard_3-0-0_105074_2017-01-09_final
2017-01-09 10:51:37	ga_ls7e_ard_3-0-0_105075_2017-01-09_final
2017-01-09 10:52:01	ga_ls7e_ard_3-0-0_105076_2017-01-09_final
2017-01-09 10:52:25	ga_ls7e_ard_3-0-0_105077_2017-01-09_final
2017-01-09 10:52:49	ga_ls7e_ard_3-0-0_105078_2017-01-09_final
2017-01-09 10:53:13	ga_ls7e_ard_3-0-0_105079_2017-01-09_final
2017-01-09 10:54:00	ga_ls7e_ard_3-0-0_105081_2017-01-09_final
2017-01-09 10:54:24	ga_ls7e_ard_3-0-0_105082_2017-01-09_final
2017-01-10 09:53:59	ga_ls7e_ard_3-0-0_096070_2017-01-10_final

Return to ga_ls7e_ard_3 across 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

All months