Search ga_ls7e_ard_3 across April 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
2018-04-10 11:40:52	ga_ls7e_ard_3-0-0_113078_2018-04-10_final
2018-04-10 11:41:16	ga_ls7e_ard_3-0-0_113079_2018-04-10_final
2018-04-10 11:41:40	ga_ls7e_ard_3-0-0_113080_2018-04-10_final
2018-04-10 11:42:52	ga_ls7e_ard_3-0-0_113083_2018-04-10_final
2018-04-10 11:43:16	ga_ls7e_ard_3-0-0_113084_2018-04-10_final
2018-04-11 10:41:14	ga_ls7e_ard_3-0-0_104068_2018-04-11_final
2018-04-11 10:41:38	ga_ls7e_ard_3-0-0_104069_2018-04-11_final
2018-04-11 10:42:02	ga_ls7e_ard_3-1-0_104070_2018-04-11_final
2018-04-11 10:42:26	ga_ls7e_ard_3-0-0_104071_2018-04-11_final
2018-04-11 10:42:50	ga_ls7e_ard_3-0-0_104072_2018-04-11_final
2018-04-11 10:43:14	ga_ls7e_ard_3-0-0_104073_2018-04-11_final
2018-04-11 10:43:38	ga_ls7e_ard_3-0-0_104074_2018-04-11_final
2018-04-11 10:44:02	ga_ls7e_ard_3-0-0_104075_2018-04-11_final
2018-04-11 10:44:26	ga_ls7e_ard_3-0-0_104076_2018-04-11_final
2018-04-11 10:44:50	ga_ls7e_ard_3-0-0_104077_2018-04-11_final
2018-04-11 10:45:14	ga_ls7e_ard_3-0-0_104078_2018-04-11_final
2018-04-11 10:45:38	ga_ls7e_ard_3-1-0_104079_2018-04-11_final
2018-04-11 10:46:02	ga_ls7e_ard_3-0-0_104080_2018-04-11_final
2018-04-11 10:46:26	ga_ls7e_ard_3-0-0_104081_2018-04-11_final
2018-04-11 10:46:50	ga_ls7e_ard_3-0-0_104082_2018-04-11_final
2018-04-12 09:47:12	ga_ls7e_ard_3-0-0_095072_2018-04-12_final
2018-04-12 09:48:00	ga_ls7e_ard_3-0-0_095074_2018-04-12_final
2018-04-12 09:48:48	ga_ls7e_ard_3-0-0_095076_2018-04-12_final
2018-04-12 09:49:12	ga_ls7e_ard_3-0-0_095077_2018-04-12_final
2018-04-12 09:49:36	ga_ls7e_ard_3-0-0_095078_2018-04-12_final
2018-04-12 09:50:00	ga_ls7e_ard_3-1-0_095079_2018-04-12_final
2018-04-12 09:50:23	ga_ls7e_ard_3-0-0_095080_2018-04-12_final
2018-04-12 09:50:47	ga_ls7e_ard_3-0-0_095081_2018-04-12_final
2018-04-12 09:51:11	ga_ls7e_ard_3-0-0_095082_2018-04-12_final
2018-04-12 09:51:35	ga_ls7e_ard_3-0-0_095083_2018-04-12_final
2018-04-12 09:51:59	ga_ls7e_ard_3-0-0_095084_2018-04-12_final
2018-04-12 09:52:23	ga_ls7e_ard_3-0-0_095085_2018-04-12_final
2018-04-12 09:52:47	ga_ls7e_ard_3-0-0_095086_2018-04-12_final
2018-04-12 09:53:11	ga_ls7e_ard_3-0-0_095087_2018-04-12_final
2018-04-12 11:24:05	ga_ls7e_ard_3-0-0_111067_2018-04-12_final
2018-04-12 11:24:29	ga_ls7e_ard_3-0-0_111068_2018-04-12_final
2018-04-12 11:25:41	ga_ls7e_ard_3-0-0_111071_2018-04-12_final
2018-04-12 11:26:05	ga_ls7e_ard_3-0-0_111072_2018-04-12_final
2018-04-12 11:26:29	ga_ls7e_ard_3-0-0_111073_2018-04-12_final
2018-04-12 11:26:53	ga_ls7e_ard_3-0-0_111074_2018-04-12_final
2018-04-12 11:27:17	ga_ls7e_ard_3-0-0_111075_2018-04-12_final
2018-04-12 11:27:41	ga_ls7e_ard_3-0-0_111076_2018-04-12_final
2018-04-12 11:28:05	ga_ls7e_ard_3-0-0_111077_2018-04-12_final
2018-04-12 11:28:53	ga_ls7e_ard_3-0-0_111079_2018-04-12_final
2018-04-12 11:29:16	ga_ls7e_ard_3-0-0_111080_2018-04-12_final
2018-04-12 11:29:40	ga_ls7e_ard_3-0-0_111081_2018-04-12_final
2018-04-12 11:30:04	ga_ls7e_ard_3-1-0_111082_2018-04-12_final
2018-04-12 11:30:28	ga_ls7e_ard_3-0-0_111083_2018-04-12_final
2018-04-26 09:58:07	ga_ls7e_ard_3-0-0_097069_2018-04-26_final
2018-04-26 09:58:31	ga_ls7e_ard_3-0-0_097070_2018-04-26_final
2018-04-26 09:58:55	ga_ls7e_ard_3-0-0_097071_2018-04-26_final
2018-04-26 09:59:19	ga_ls7e_ard_3-0-0_097072_2018-04-26_final
2018-04-26 09:59:43	ga_ls7e_ard_3-0-0_097073_2018-04-26_final
2018-04-26 10:00:07	ga_ls7e_ard_3-0-0_097074_2018-04-26_final
2018-04-26 10:00:31	ga_ls7e_ard_3-0-0_097075_2018-04-26_final
2018-04-26 10:00:55	ga_ls7e_ard_3-0-0_097076_2018-04-26_final
2018-04-26 10:01:19	ga_ls7e_ard_3-0-0_097077_2018-04-26_final
2018-04-26 10:01:43	ga_ls7e_ard_3-0-0_097078_2018-04-26_final
2018-04-26 10:02:07	ga_ls7e_ard_3-0-0_097079_2018-04-26_final
2018-04-26 10:02:31	ga_ls7e_ard_3-0-0_097080_2018-04-26_final
2018-04-26 10:02:54	ga_ls7e_ard_3-0-0_097081_2018-04-26_final
2018-04-26 10:03:18	ga_ls7e_ard_3-0-0_097082_2018-04-26_final
2018-04-26 10:03:42	ga_ls7e_ard_3-0-0_097083_2018-04-26_final
2018-04-26 10:04:06	ga_ls7e_ard_3-0-0_097084_2018-04-26_final
2018-04-26 10:04:30	ga_ls7e_ard_3-0-0_097085_2018-04-26_final
2018-04-26 11:36:12	ga_ls7e_ard_3-0-0_113067_2018-04-26_final
2018-04-26 11:39:00	ga_ls7e_ard_3-0-0_113074_2018-04-26_final
2018-04-26 11:39:24	ga_ls7e_ard_3-0-0_113075_2018-04-26_final
2018-04-26 11:39:48	ga_ls7e_ard_3-0-0_113076_2018-04-26_final
2018-04-26 11:40:12	ga_ls7e_ard_3-0-0_113077_2018-04-26_final
2018-04-26 11:40:36	ga_ls7e_ard_3-0-0_113078_2018-04-26_final
2018-04-26 11:41:00	ga_ls7e_ard_3-0-0_113079_2018-04-26_final
2018-04-26 11:41:24	ga_ls7e_ard_3-1-0_113080_2018-04-26_final
2018-04-26 11:41:47	ga_ls7e_ard_3-0-0_113081_2018-04-26_final
2018-04-26 11:42:11	ga_ls7e_ard_3-0-0_113082_2018-04-26_final
2018-04-26 11:42:35	ga_ls7e_ard_3-0-0_113083_2018-04-26_final
2018-04-26 11:42:59	ga_ls7e_ard_3-0-0_113084_2018-04-26_final
2018-04-27 10:40:58	ga_ls7e_ard_3-0-0_104068_2018-04-27_final
2018-04-27 10:41:22	ga_ls7e_ard_3-0-0_104069_2018-04-27_final
2018-04-27 10:41:46	ga_ls7e_ard_3-1-0_104070_2018-04-27_final
2018-04-27 10:42:10	ga_ls7e_ard_3-0-0_104071_2018-04-27_final
2018-04-27 10:42:34	ga_ls7e_ard_3-0-0_104072_2018-04-27_final
2018-04-27 10:42:57	ga_ls7e_ard_3-0-0_104073_2018-04-27_final
2018-04-27 10:43:21	ga_ls7e_ard_3-0-0_104074_2018-04-27_final
2018-04-27 10:43:45	ga_ls7e_ard_3-0-0_104075_2018-04-27_final
2018-04-27 10:44:09	ga_ls7e_ard_3-0-0_104076_2018-04-27_final
2018-04-27 10:44:33	ga_ls7e_ard_3-0-0_104077_2018-04-27_final
2018-04-27 10:44:57	ga_ls7e_ard_3-0-0_104078_2018-04-27_final
2018-04-27 10:45:21	ga_ls7e_ard_3-0-0_104079_2018-04-27_final
2018-04-27 10:45:45	ga_ls7e_ard_3-0-0_104080_2018-04-27_final
2018-04-27 10:46:09	ga_ls7e_ard_3-0-0_104081_2018-04-27_final
2018-04-27 10:46:33	ga_ls7e_ard_3-0-0_104082_2018-04-27_final
2018-04-28 09:46:55	ga_ls7e_ard_3-0-0_095072_2018-04-28_final
2018-04-28 09:47:19	ga_ls7e_ard_3-1-0_095073_2018-04-28_final
2018-04-28 09:47:43	ga_ls7e_ard_3-0-0_095074_2018-04-28_final
2018-04-28 09:48:07	ga_ls7e_ard_3-0-0_095075_2018-04-28_final
2018-04-28 09:48:31	ga_ls7e_ard_3-0-0_095076_2018-04-28_final
2018-04-28 09:48:55	ga_ls7e_ard_3-0-0_095077_2018-04-28_final
2018-04-28 09:49:19	ga_ls7e_ard_3-0-0_095078_2018-04-28_final
2018-04-28 09:49:43	ga_ls7e_ard_3-1-0_095079_2018-04-28_final

Return to ga_ls7e_ard_3 across April 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

April

All days