Search ga_ls7e_ard_3 across December 2019

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
2019-12-20 09:22:09	ga_ls7e_ard_3-1-0_094073_2019-12-19_final
2019-12-20 09:22:33	ga_ls7e_ard_3-1-0_094074_2019-12-19_final
2019-12-20 09:22:57	ga_ls7e_ard_3-1-0_094075_2019-12-19_final
2019-12-20 09:23:21	ga_ls7e_ard_3-1-0_094076_2019-12-19_final
2019-12-20 09:23:44	ga_ls7e_ard_3-1-0_094077_2019-12-19_final
2019-12-20 09:24:32	ga_ls7e_ard_3-1-0_094079_2019-12-19_final
2019-12-20 09:24:56	ga_ls7e_ard_3-1-0_094080_2019-12-19_final
2019-12-20 09:25:44	ga_ls7e_ard_3-1-0_094082_2019-12-19_final
2019-12-20 09:26:08	ga_ls7e_ard_3-1-0_094083_2019-12-19_final
2019-12-20 09:26:32	ga_ls7e_ard_3-1-0_094084_2019-12-19_final
2019-12-20 09:26:56	ga_ls7e_ard_3-1-0_094085_2019-12-19_final
2019-12-20 09:27:44	ga_ls7e_ard_3-1-0_094087_2019-12-19_final
2019-12-23 09:50:30	ga_ls7e_ard_3-1-0_099067_2019-12-23_final
2019-12-23 09:50:54	ga_ls7e_ard_3-1-0_099068_2019-12-23_final
2019-12-23 09:51:18	ga_ls7e_ard_3-1-0_099069_2019-12-23_final
2019-12-23 09:51:42	ga_ls7e_ard_3-1-0_099070_2019-12-23_final
2019-12-23 09:52:06	ga_ls7e_ard_3-1-0_099071_2019-12-23_final
2019-12-23 09:52:30	ga_ls7e_ard_3-1-0_099072_2019-12-23_final
2019-12-23 09:52:53	ga_ls7e_ard_3-1-0_099073_2019-12-23_final
2019-12-23 09:53:17	ga_ls7e_ard_3-1-0_099074_2019-12-23_final
2019-12-23 09:53:41	ga_ls7e_ard_3-1-0_099075_2019-12-23_final
2019-12-23 09:54:05	ga_ls7e_ard_3-1-0_099076_2019-12-23_final
2019-12-23 09:54:29	ga_ls7e_ard_3-1-0_099077_2019-12-23_final
2019-12-23 09:54:53	ga_ls7e_ard_3-1-0_099078_2019-12-23_final
2019-12-23 09:55:17	ga_ls7e_ard_3-1-0_099079_2019-12-23_final
2019-12-23 09:55:41	ga_ls7e_ard_3-1-0_099080_2019-12-23_final
2019-12-23 09:56:05	ga_ls7e_ard_3-1-0_099081_2019-12-23_final
2019-12-23 09:56:29	ga_ls7e_ard_3-1-0_099082_2019-12-23_final
2019-12-23 09:56:53	ga_ls7e_ard_3-1-0_099083_2019-12-23_final
2019-12-23 09:57:17	ga_ls7e_ard_3-1-0_099084_2019-12-23_final
2019-12-29 09:16:18	ga_ls7e_ard_3-1-0_093075_2019-12-28_final
2019-12-29 09:16:42	ga_ls7e_ard_3-1-0_093076_2019-12-28_final
2019-12-29 09:17:06	ga_ls7e_ard_3-1-0_093077_2019-12-28_final
2019-12-29 09:17:30	ga_ls7e_ard_3-1-0_093078_2019-12-28_final
2019-12-29 09:17:54	ga_ls7e_ard_3-1-0_093079_2019-12-28_final
2019-12-29 09:18:18	ga_ls7e_ard_3-1-0_093080_2019-12-28_final
2019-12-29 09:18:42	ga_ls7e_ard_3-1-0_093081_2019-12-28_final
2019-12-29 09:19:05	ga_ls7e_ard_3-1-0_093082_2019-12-28_final
2019-12-29 09:19:29	ga_ls7e_ard_3-1-0_093083_2019-12-28_final
2019-12-29 09:19:53	ga_ls7e_ard_3-1-0_093084_2019-12-28_final
2019-12-29 09:20:17	ga_ls7e_ard_3-1-0_093085_2019-12-28_final
2019-12-29 09:20:41	ga_ls7e_ard_3-1-0_093086_2019-12-28_final
2019-12-29 09:21:05	ga_ls7e_ard_3-1-0_093087_2019-12-28_final
2019-12-29 09:21:29	ga_ls7e_ard_3-1-0_093088_2019-12-28_final
2019-12-29 10:53:11	ga_ls7e_ard_3-1-0_109070_2019-12-29_final
2019-12-29 10:53:35	ga_ls7e_ard_3-1-0_109071_2019-12-29_final
2019-12-29 10:53:59	ga_ls7e_ard_3-1-0_109072_2019-12-29_final
2019-12-29 10:54:23	ga_ls7e_ard_3-1-0_109073_2019-12-29_final
2019-12-29 10:54:47	ga_ls7e_ard_3-1-0_109074_2019-12-29_final
2019-12-29 10:55:11	ga_ls7e_ard_3-1-0_109075_2019-12-29_final
2019-12-29 10:55:35	ga_ls7e_ard_3-1-0_109076_2019-12-29_final
2019-12-29 10:55:59	ga_ls7e_ard_3-1-0_109077_2019-12-29_final
2019-12-29 10:56:22	ga_ls7e_ard_3-1-0_109078_2019-12-29_final
2019-12-29 10:56:46	ga_ls7e_ard_3-1-0_109079_2019-12-29_final
2019-12-29 10:57:10	ga_ls7e_ard_3-1-0_109080_2019-12-29_final
2019-12-29 10:57:34	ga_ls7e_ard_3-1-0_109081_2019-12-29_final
2019-12-29 10:57:58	ga_ls7e_ard_3-1-0_109082_2019-12-29_final
2019-12-29 10:58:22	ga_ls7e_ard_3-1-0_109083_2019-12-29_final
2019-12-29 10:58:46	ga_ls7e_ard_3-1-0_109084_2019-12-29_final
2019-12-30 09:57:55	ga_ls7e_ard_3-1-0_100071_2019-12-30_final
2019-12-30 09:58:18	ga_ls7e_ard_3-1-0_100072_2019-12-30_final
2019-12-30 09:58:42	ga_ls7e_ard_3-1-0_100073_2019-12-30_final
2019-12-30 09:59:06	ga_ls7e_ard_3-1-0_100074_2019-12-30_final
2019-12-30 09:59:30	ga_ls7e_ard_3-1-0_100075_2019-12-30_final
2019-12-30 09:59:54	ga_ls7e_ard_3-1-0_100076_2019-12-30_final
2019-12-30 10:00:18	ga_ls7e_ard_3-1-0_100077_2019-12-30_final
2019-12-30 10:00:42	ga_ls7e_ard_3-1-0_100078_2019-12-30_final
2019-12-30 10:01:06	ga_ls7e_ard_3-1-0_100079_2019-12-30_final
2019-12-30 10:01:30	ga_ls7e_ard_3-1-0_100080_2019-12-30_final
2019-12-30 10:01:54	ga_ls7e_ard_3-1-0_100081_2019-12-30_final
2019-12-30 10:02:18	ga_ls7e_ard_3-1-0_100082_2019-12-30_final
2019-12-30 10:02:42	ga_ls7e_ard_3-1-0_100083_2019-12-30_final
2019-12-30 10:03:06	ga_ls7e_ard_3-1-0_100084_2019-12-30_final
2019-12-31 09:04:14	ga_ls7e_ard_3-1-0_091076_2019-12-30_final
2019-12-31 09:04:38	ga_ls7e_ard_3-1-0_091077_2019-12-30_final
2019-12-31 09:05:02	ga_ls7e_ard_3-1-0_091078_2019-12-30_final
2019-12-31 09:05:26	ga_ls7e_ard_3-1-0_091079_2019-12-30_final
2019-12-31 09:05:50	ga_ls7e_ard_3-1-0_091080_2019-12-30_final
2019-12-31 09:06:14	ga_ls7e_ard_3-1-0_091081_2019-12-30_final
2019-12-31 09:06:38	ga_ls7e_ard_3-1-0_091082_2019-12-30_final
2019-12-31 09:07:02	ga_ls7e_ard_3-1-0_091083_2019-12-30_final
2019-12-31 09:07:25	ga_ls7e_ard_3-1-0_091084_2019-12-30_final
2019-12-31 09:07:49	ga_ls7e_ard_3-1-0_091085_2019-12-30_final
2019-12-31 09:09:01	ga_ls7e_ard_3-1-0_091088_2019-12-30_final
2019-12-31 09:09:25	ga_ls7e_ard_3-1-0_091089_2019-12-30_final
2019-12-31 09:09:49	ga_ls7e_ard_3-1-0_091090_2019-12-30_final
2019-12-31 10:40:43	ga_ls7e_ard_3-1-0_107070_2019-12-31_final
2019-12-31 10:41:07	ga_ls7e_ard_3-1-0_107071_2019-12-31_final
2019-12-31 10:41:31	ga_ls7e_ard_3-1-0_107072_2019-12-31_final
2019-12-31 10:41:55	ga_ls7e_ard_3-1-0_107073_2019-12-31_final
2019-12-31 10:42:19	ga_ls7e_ard_3-1-0_107074_2019-12-31_final
2019-12-31 10:42:43	ga_ls7e_ard_3-1-0_107075_2019-12-31_final
2019-12-31 10:43:07	ga_ls7e_ard_3-1-0_107076_2019-12-31_final
2019-12-31 10:43:31	ga_ls7e_ard_3-1-0_107077_2019-12-31_final
2019-12-31 10:43:55	ga_ls7e_ard_3-1-0_107078_2019-12-31_final
2019-12-31 10:44:19	ga_ls7e_ard_3-1-0_107079_2019-12-31_final
2019-12-31 10:44:42	ga_ls7e_ard_3-1-0_107080_2019-12-31_final
2019-12-31 10:45:06	ga_ls7e_ard_3-1-0_107081_2019-12-31_final
2019-12-31 10:45:30	ga_ls7e_ard_3-1-0_107082_2019-12-31_final
2019-12-31 10:45:54	ga_ls7e_ard_3-1-0_107083_2019-12-31_final

Return to ga_ls7e_ard_3 across December 2019 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

2019

December

All days