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
2017-04-11 09:40:44	ga_ls7e_ard_3-1-0_093083_2017-04-11_final
2017-04-11 11:18:50	ga_ls7e_ard_3-1-0_109081_2017-04-11_final
2017-04-12 10:23:13	ga_ls7e_ard_3-1-0_100081_2017-04-12_final
2017-04-13 09:29:36	ga_ls7e_ard_3-1-0_091086_2017-04-12_final
2017-06-30 09:37:53	ga_ls7e_ard_3-0-0_093075_2017-06-30_final
2017-06-30 09:38:17	ga_ls7e_ard_3-0-0_093076_2017-06-30_final
2017-06-30 09:38:41	ga_ls7e_ard_3-0-0_093077_2017-06-30_final
2017-06-30 09:39:05	ga_ls7e_ard_3-0-0_093078_2017-06-30_final
2017-06-30 09:39:29	ga_ls7e_ard_3-0-0_093079_2017-06-30_final
2017-06-30 09:39:53	ga_ls7e_ard_3-0-0_093080_2017-06-30_final
2017-06-30 09:40:17	ga_ls7e_ard_3-0-0_093081_2017-06-30_final
2017-06-30 09:40:41	ga_ls7e_ard_3-0-0_093082_2017-06-30_final
2017-06-30 09:41:05	ga_ls7e_ard_3-1-0_093083_2017-06-30_final
2017-06-30 09:41:29	ga_ls7e_ard_3-0-0_093084_2017-06-30_final
2017-06-30 09:41:53	ga_ls7e_ard_3-0-0_093085_2017-06-30_final
2017-06-30 09:42:17	ga_ls7e_ard_3-0-0_093086_2017-06-30_final
2017-06-30 09:42:41	ga_ls7e_ard_3-0-0_093087_2017-06-30_final
2017-06-30 09:43:05	ga_ls7e_ard_3-0-0_093088_2017-06-30_final
2017-06-30 11:14:47	ga_ls7e_ard_3-0-0_109070_2017-06-30_final
2017-06-30 11:15:11	ga_ls7e_ard_3-0-0_109071_2017-06-30_final
2017-06-30 11:15:35	ga_ls7e_ard_3-0-0_109072_2017-06-30_final
2017-06-30 11:15:59	ga_ls7e_ard_3-0-0_109073_2017-06-30_final
2017-06-30 11:16:23	ga_ls7e_ard_3-0-0_109074_2017-06-30_final
2017-06-30 11:16:46	ga_ls7e_ard_3-0-0_109075_2017-06-30_final
2017-06-30 11:17:10	ga_ls7e_ard_3-0-0_109076_2017-06-30_final
2017-06-30 11:17:34	ga_ls7e_ard_3-0-0_109077_2017-06-30_final
2017-06-30 11:17:58	ga_ls7e_ard_3-0-0_109078_2017-06-30_final
2017-06-30 11:18:22	ga_ls7e_ard_3-0-0_109079_2017-06-30_final
2017-06-30 11:18:46	ga_ls7e_ard_3-0-0_109080_2017-06-30_final
2017-06-30 11:19:10	ga_ls7e_ard_3-1-0_109081_2017-06-30_final
2017-06-30 11:19:34	ga_ls7e_ard_3-0-0_109082_2017-06-30_final
2017-06-30 11:19:58	ga_ls7e_ard_3-0-0_109083_2017-06-30_final
2017-06-30 11:20:22	ga_ls7e_ard_3-0-0_109084_2017-06-30_final
2017-07-01 10:19:33	ga_ls7e_ard_3-0-0_100071_2017-07-01_final
2017-07-01 10:19:57	ga_ls7e_ard_3-0-0_100072_2017-07-01_final
2017-07-01 10:20:21	ga_ls7e_ard_3-0-0_100073_2017-07-01_final
2017-07-01 10:20:45	ga_ls7e_ard_3-0-0_100074_2017-07-01_final
2017-07-01 10:21:09	ga_ls7e_ard_3-0-0_100075_2017-07-01_final
2017-07-01 10:21:33	ga_ls7e_ard_3-0-0_100076_2017-07-01_final
2017-07-01 10:21:57	ga_ls7e_ard_3-0-0_100077_2017-07-01_final
2017-07-01 10:22:21	ga_ls7e_ard_3-0-0_100078_2017-07-01_final
2017-07-01 10:22:45	ga_ls7e_ard_3-0-0_100079_2017-07-01_final
2017-07-01 10:23:09	ga_ls7e_ard_3-0-0_100080_2017-07-01_final
2017-07-01 10:23:33	ga_ls7e_ard_3-0-0_100081_2017-07-01_final
2017-07-01 10:23:57	ga_ls7e_ard_3-0-0_100082_2017-07-01_final
2017-07-01 10:24:21	ga_ls7e_ard_3-0-0_100083_2017-07-01_final
2017-07-01 10:24:45	ga_ls7e_ard_3-0-0_100084_2017-07-01_final
2017-07-02 09:25:56	ga_ls7e_ard_3-0-0_091076_2017-07-01_final
2017-07-02 09:26:20	ga_ls7e_ard_3-0-0_091077_2017-07-01_final
2017-07-02 09:26:44	ga_ls7e_ard_3-0-0_091078_2017-07-01_final
2017-07-02 09:27:08	ga_ls7e_ard_3-0-0_091079_2017-07-01_final
2017-07-02 09:27:32	ga_ls7e_ard_3-0-0_091080_2017-07-01_final
2017-07-02 09:27:56	ga_ls7e_ard_3-0-0_091081_2017-07-01_final
2017-07-02 09:28:20	ga_ls7e_ard_3-0-0_091082_2017-07-01_final
2017-07-02 09:28:44	ga_ls7e_ard_3-0-0_091083_2017-07-01_final
2017-07-02 09:29:07	ga_ls7e_ard_3-0-0_091084_2017-07-01_final
2017-07-02 09:29:31	ga_ls7e_ard_3-0-0_091085_2017-07-01_final
2017-07-02 09:29:55	ga_ls7e_ard_3-1-0_091086_2017-07-01_final
2017-07-02 09:30:19	ga_ls7e_ard_3-0-0_091087_2017-07-02_final
2017-07-02 09:30:43	ga_ls7e_ard_3-0-0_091088_2017-07-02_final
2017-07-02 09:31:31	ga_ls7e_ard_3-0-0_091090_2017-07-02_final
2017-07-02 11:02:25	ga_ls7e_ard_3-0-0_107070_2017-07-02_final
2017-07-02 11:02:49	ga_ls7e_ard_3-0-0_107071_2017-07-02_final
2017-07-02 11:03:13	ga_ls7e_ard_3-0-0_107072_2017-07-02_final
2017-07-02 11:03:37	ga_ls7e_ard_3-0-0_107073_2017-07-02_final
2017-07-02 11:04:01	ga_ls7e_ard_3-0-0_107074_2017-07-02_final
2017-07-02 11:04:25	ga_ls7e_ard_3-0-0_107075_2017-07-02_final
2017-07-02 11:04:49	ga_ls7e_ard_3-0-0_107076_2017-07-02_final
2017-07-02 11:05:13	ga_ls7e_ard_3-0-0_107077_2017-07-02_final
2017-07-02 11:05:37	ga_ls7e_ard_3-0-0_107078_2017-07-02_final
2017-07-02 11:06:01	ga_ls7e_ard_3-0-0_107079_2017-07-02_final
2017-07-02 11:06:25	ga_ls7e_ard_3-0-0_107080_2017-07-02_final
2017-07-02 11:06:49	ga_ls7e_ard_3-0-0_107081_2017-07-02_final
2017-07-02 11:07:13	ga_ls7e_ard_3-0-0_107082_2017-07-02_final
2017-07-02 11:07:37	ga_ls7e_ard_3-0-0_107083_2017-07-02_final
2017-07-02 11:08:01	ga_ls7e_ard_3-0-0_107084_2017-07-02_final
2017-07-03 10:06:00	ga_ls7e_ard_3-0-0_098068_2017-07-03_final
2017-07-03 10:06:24	ga_ls7e_ard_3-0-0_098069_2017-07-03_final
2017-07-03 10:06:48	ga_ls7e_ard_3-0-0_098070_2017-07-03_final
2017-07-03 10:07:12	ga_ls7e_ard_3-0-0_098071_2017-07-03_final
2017-07-03 10:07:36	ga_ls7e_ard_3-0-0_098072_2017-07-03_final
2017-07-03 10:08:00	ga_ls7e_ard_3-0-0_098073_2017-07-03_final
2017-07-03 10:08:24	ga_ls7e_ard_3-0-0_098074_2017-07-03_final
2017-07-03 10:08:48	ga_ls7e_ard_3-0-0_098075_2017-07-03_final
2017-07-03 10:09:12	ga_ls7e_ard_3-0-0_098076_2017-07-03_final
2017-07-03 10:09:36	ga_ls7e_ard_3-0-0_098077_2017-07-03_final
2017-07-03 10:10:00	ga_ls7e_ard_3-0-0_098078_2017-07-03_final
2017-07-03 10:10:24	ga_ls7e_ard_3-0-0_098079_2017-07-03_final
2017-07-03 10:10:47	ga_ls7e_ard_3-0-0_098080_2017-07-03_final
2017-07-03 10:11:11	ga_ls7e_ard_3-0-0_098081_2017-07-03_final
2017-07-03 10:11:35	ga_ls7e_ard_3-0-0_098082_2017-07-03_final
2017-07-03 10:11:59	ga_ls7e_ard_3-0-0_098083_2017-07-03_final
2017-07-03 10:12:23	ga_ls7e_ard_3-0-0_098084_2017-07-03_final
2017-07-03 11:44:29	ga_ls7e_ard_3-0-0_114067_2017-07-03_final
2017-07-03 11:47:17	ga_ls7e_ard_3-0-0_114074_2017-07-03_final
2017-07-03 11:47:41	ga_ls7e_ard_3-0-0_114075_2017-07-03_final
2017-07-03 11:48:05	ga_ls7e_ard_3-0-0_114076_2017-07-03_final
2017-07-03 11:48:29	ga_ls7e_ard_3-0-0_114077_2017-07-03_final
2017-07-03 11:48:53	ga_ls7e_ard_3-0-0_114078_2017-07-03_final
2017-07-03 11:49:17	ga_ls7e_ard_3-0-0_114079_2017-07-03_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

GA Collection 3

USGS Products

Collection 2 NBAR

Collection 2 NBAR Tiled

Pixel Quality

Collection 2 Level1

Tidal

Water Observations

Fractional Cover

Sentinel 2

Ingested Pixel Quality

Geomedians

TMAD

Telemetry data

Summary

Other Products

2017

All months