Search ga_ls7e_ard_3 across November 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
2018-11-02 11:48:49	ga_ls7e_ard_3-1-0_115077_2018-11-02_final
2018-11-03 09:14:41	ga_ls7e_ard_3-0-0_090078_2018-11-02_final
2018-11-03 09:15:05	ga_ls7e_ard_3-0-0_090079_2018-11-02_final
2018-11-03 09:15:29	ga_ls7e_ard_3-0-0_090080_2018-11-02_final
2018-11-03 09:15:53	ga_ls7e_ard_3-0-0_090081_2018-11-02_final
2018-11-03 09:16:17	ga_ls7e_ard_3-1-0_090082_2018-11-02_final
2018-11-03 09:17:29	ga_ls7e_ard_3-1-0_090085_2018-11-02_final
2018-11-03 09:17:53	ga_ls7e_ard_3-0-0_090086_2018-11-02_final
2018-11-03 09:18:41	ga_ls7e_ard_3-0-0_090088_2018-11-02_final
2018-11-03 10:52:22	ga_ls7e_ard_3-1-0_106075_2018-11-03_final
2018-11-03 10:53:10	ga_ls7e_ard_3-1-0_106077_2018-11-03_final
2018-11-04 09:57:08	ga_ls7e_ard_3-1-0_097076_2018-11-04_final
2018-11-05 10:37:58	ga_ls7e_ard_3-1-0_104070_2018-11-05_final
2018-11-24 09:31:08	ga_ls7e_ard_3-0-0_093074_2018-11-24_final
2018-11-24 09:31:32	ga_ls7e_ard_3-0-0_093075_2018-11-24_final
2018-11-24 09:31:56	ga_ls7e_ard_3-0-0_093076_2018-11-24_final
2018-11-24 09:32:20	ga_ls7e_ard_3-0-0_093077_2018-11-24_final
2018-11-24 09:32:44	ga_ls7e_ard_3-0-0_093078_2018-11-24_final
2018-11-24 09:33:08	ga_ls7e_ard_3-0-0_093079_2018-11-24_final
2018-11-24 09:33:32	ga_ls7e_ard_3-0-0_093080_2018-11-24_final
2018-11-24 09:33:56	ga_ls7e_ard_3-0-0_093081_2018-11-24_final
2018-11-24 09:34:19	ga_ls7e_ard_3-0-0_093082_2018-11-24_final
2018-11-24 09:34:43	ga_ls7e_ard_3-1-0_093083_2018-11-24_final
2018-11-24 09:35:07	ga_ls7e_ard_3-0-0_093084_2018-11-24_final
2018-11-24 09:35:31	ga_ls7e_ard_3-0-0_093085_2018-11-24_final
2018-11-24 09:35:55	ga_ls7e_ard_3-0-0_093086_2018-11-24_final
2018-11-24 11:08:25	ga_ls7e_ard_3-0-0_109070_2018-11-24_final
2018-11-24 11:08:49	ga_ls7e_ard_3-0-0_109071_2018-11-24_final
2018-11-24 11:09:13	ga_ls7e_ard_3-0-0_109072_2018-11-24_final
2018-11-24 11:09:37	ga_ls7e_ard_3-0-0_109073_2018-11-24_final
2018-11-24 11:10:01	ga_ls7e_ard_3-0-0_109074_2018-11-24_final
2018-11-24 11:10:25	ga_ls7e_ard_3-0-0_109075_2018-11-24_final
2018-11-24 11:10:49	ga_ls7e_ard_3-0-0_109076_2018-11-24_final
2018-11-24 11:11:13	ga_ls7e_ard_3-0-0_109077_2018-11-24_final
2018-11-24 11:11:37	ga_ls7e_ard_3-0-0_109078_2018-11-24_final
2018-11-24 11:12:01	ga_ls7e_ard_3-0-0_109079_2018-11-24_final
2018-11-24 11:12:24	ga_ls7e_ard_3-0-0_109080_2018-11-24_final
2018-11-24 11:12:48	ga_ls7e_ard_3-1-0_109081_2018-11-24_final
2018-11-24 11:13:12	ga_ls7e_ard_3-0-0_109082_2018-11-24_final
2018-11-24 11:13:36	ga_ls7e_ard_3-0-0_109083_2018-11-24_final
2018-11-25 10:13:10	ga_ls7e_ard_3-0-0_100071_2018-11-25_final
2018-11-25 10:13:34	ga_ls7e_ard_3-0-0_100072_2018-11-25_final
2018-11-25 10:13:58	ga_ls7e_ard_3-0-0_100073_2018-11-25_final
2018-11-25 10:14:22	ga_ls7e_ard_3-0-0_100074_2018-11-25_final
2018-11-25 10:14:46	ga_ls7e_ard_3-0-0_100075_2018-11-25_final
2018-11-25 10:15:10	ga_ls7e_ard_3-0-0_100076_2018-11-25_final
2018-11-25 10:15:34	ga_ls7e_ard_3-0-0_100077_2018-11-25_final
2018-11-25 10:15:58	ga_ls7e_ard_3-0-0_100078_2018-11-25_final
2018-11-25 10:16:22	ga_ls7e_ard_3-0-0_100079_2018-11-25_final
2018-11-25 10:16:46	ga_ls7e_ard_3-0-0_100080_2018-11-25_final
2018-11-25 10:17:10	ga_ls7e_ard_3-0-0_100081_2018-11-25_final
2018-11-26 09:19:31	ga_ls7e_ard_3-0-0_091076_2018-11-25_final
2018-11-26 09:19:55	ga_ls7e_ard_3-0-0_091077_2018-11-25_final
2018-11-26 09:20:19	ga_ls7e_ard_3-0-0_091078_2018-11-25_final
2018-11-26 09:20:43	ga_ls7e_ard_3-0-0_091079_2018-11-25_final
2018-11-26 09:21:07	ga_ls7e_ard_3-0-0_091080_2018-11-25_final
2018-11-26 09:21:31	ga_ls7e_ard_3-0-0_091081_2018-11-25_final
2018-11-26 09:21:55	ga_ls7e_ard_3-0-0_091082_2018-11-25_final
2018-11-26 09:22:19	ga_ls7e_ard_3-0-0_091083_2018-11-25_final
2018-11-26 09:22:43	ga_ls7e_ard_3-0-0_091084_2018-11-25_final
2018-11-26 09:23:07	ga_ls7e_ard_3-0-0_091085_2018-11-25_final
2018-11-26 09:23:31	ga_ls7e_ard_3-1-0_091086_2018-11-25_final
2018-11-26 09:23:55	ga_ls7e_ard_3-0-0_091087_2018-11-25_final
2018-11-26 09:24:19	ga_ls7e_ard_3-0-0_091088_2018-11-25_final
2018-11-26 09:24:42	ga_ls7e_ard_3-0-0_091089_2018-11-25_final
2018-11-26 09:25:06	ga_ls7e_ard_3-0-0_091090_2018-11-25_final
2018-11-26 10:56:00	ga_ls7e_ard_3-0-0_107070_2018-11-26_final
2018-11-26 10:56:24	ga_ls7e_ard_3-0-0_107071_2018-11-26_final
2018-11-26 10:56:48	ga_ls7e_ard_3-0-0_107072_2018-11-26_final
2018-11-26 10:57:12	ga_ls7e_ard_3-0-0_107073_2018-11-26_final
2018-11-26 10:57:36	ga_ls7e_ard_3-0-0_107074_2018-11-26_final
2018-11-26 10:58:00	ga_ls7e_ard_3-0-0_107075_2018-11-26_final
2018-11-26 10:58:24	ga_ls7e_ard_3-0-0_107076_2018-11-26_final
2018-11-26 10:58:48	ga_ls7e_ard_3-0-0_107077_2018-11-26_final
2018-11-26 10:59:12	ga_ls7e_ard_3-0-0_107078_2018-11-26_final
2018-11-26 10:59:36	ga_ls7e_ard_3-0-0_107079_2018-11-26_final
2018-11-26 11:00:00	ga_ls7e_ard_3-0-0_107080_2018-11-26_final
2018-11-26 11:00:24	ga_ls7e_ard_3-0-0_107081_2018-11-26_final
2018-11-26 11:01:12	ga_ls7e_ard_3-0-0_107083_2018-11-26_final
2018-11-26 11:01:36	ga_ls7e_ard_3-0-0_107084_2018-11-26_final
2018-11-27 09:59:10	ga_ls7e_ard_3-0-0_098067_2018-11-27_final
2018-11-27 09:59:34	ga_ls7e_ard_3-0-0_098068_2018-11-27_final
2018-11-27 09:59:58	ga_ls7e_ard_3-0-0_098069_2018-11-27_final
2018-11-27 10:00:22	ga_ls7e_ard_3-0-0_098070_2018-11-27_final
2018-11-27 10:00:46	ga_ls7e_ard_3-0-0_098071_2018-11-27_final
2018-11-27 10:01:33	ga_ls7e_ard_3-0-0_098073_2018-11-27_final
2018-11-27 10:01:57	ga_ls7e_ard_3-0-0_098074_2018-11-27_final
2018-11-27 10:02:45	ga_ls7e_ard_3-0-0_098076_2018-11-27_final
2018-11-27 10:03:09	ga_ls7e_ard_3-0-0_098077_2018-11-27_final
2018-11-27 10:03:33	ga_ls7e_ard_3-0-0_098078_2018-11-27_final
2018-11-27 10:03:57	ga_ls7e_ard_3-0-0_098079_2018-11-27_final
2018-11-27 10:04:21	ga_ls7e_ard_3-1-0_098080_2018-11-27_final
2018-11-27 10:04:45	ga_ls7e_ard_3-0-0_098081_2018-11-27_final
2018-11-27 11:40:50	ga_ls7e_ard_3-0-0_114074_2018-11-27_final
2018-11-27 11:41:14	ga_ls7e_ard_3-0-0_114075_2018-11-27_final
2018-11-27 11:41:38	ga_ls7e_ard_3-0-0_114076_2018-11-27_final
2018-11-27 11:42:02	ga_ls7e_ard_3-0-0_114077_2018-11-27_final
2018-11-27 11:42:26	ga_ls7e_ard_3-0-0_114078_2018-11-27_final
2018-11-27 11:42:50	ga_ls7e_ard_3-0-0_114079_2018-11-27_final
2018-11-27 11:43:14	ga_ls7e_ard_3-0-0_114080_2018-11-27_final

Return to ga_ls7e_ard_3 across November 2018 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

2018

November

All days