Search ga_ls7e_ard_3 across September 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
2018-09-19 09:47:50	ga_ls7e_ard_3-0-0_095081_2018-09-19_final
2018-09-19 09:48:14	ga_ls7e_ard_3-0-0_095082_2018-09-19_final
2018-09-19 09:48:38	ga_ls7e_ard_3-0-0_095083_2018-09-19_final
2018-09-19 09:49:01	ga_ls7e_ard_3-0-0_095084_2018-09-19_final
2018-09-19 09:49:49	ga_ls7e_ard_3-0-0_095086_2018-09-19_final
2018-09-19 09:50:13	ga_ls7e_ard_3-0-0_095087_2018-09-19_final
2018-09-19 11:21:07	ga_ls7e_ard_3-0-0_111067_2018-09-19_final
2018-09-19 11:21:31	ga_ls7e_ard_3-0-0_111068_2018-09-19_final
2018-09-19 11:22:43	ga_ls7e_ard_3-0-0_111071_2018-09-19_final
2018-09-19 11:23:07	ga_ls7e_ard_3-0-0_111072_2018-09-19_final
2018-09-19 11:23:31	ga_ls7e_ard_3-0-0_111073_2018-09-19_final
2018-09-19 11:23:55	ga_ls7e_ard_3-0-0_111074_2018-09-19_final
2018-09-19 11:24:19	ga_ls7e_ard_3-0-0_111075_2018-09-19_final
2018-09-19 11:24:43	ga_ls7e_ard_3-0-0_111076_2018-09-19_final
2018-09-19 11:25:07	ga_ls7e_ard_3-0-0_111077_2018-09-19_final
2018-09-19 11:25:31	ga_ls7e_ard_3-0-0_111078_2018-09-19_final
2018-09-19 11:25:55	ga_ls7e_ard_3-0-0_111079_2018-09-19_final
2018-09-19 11:26:19	ga_ls7e_ard_3-0-0_111080_2018-09-19_final
2018-09-19 11:26:43	ga_ls7e_ard_3-0-0_111081_2018-09-19_final
2018-09-19 11:27:07	ga_ls7e_ard_3-1-0_111082_2018-09-19_final
2018-09-19 11:27:30	ga_ls7e_ard_3-0-0_111083_2018-09-19_final
2018-09-19 11:27:54	ga_ls7e_ard_3-0-0_111084_2018-09-19_final
2018-09-20 10:25:53	ga_ls7e_ard_3-0-0_102068_2018-09-20_final
2018-09-20 10:26:17	ga_ls7e_ard_3-0-0_102069_2018-09-20_final
2018-09-20 10:26:41	ga_ls7e_ard_3-0-0_102070_2018-09-20_final
2018-09-20 10:27:04	ga_ls7e_ard_3-0-0_102071_2018-09-20_final
2018-09-20 10:27:28	ga_ls7e_ard_3-0-0_102072_2018-09-20_final
2018-09-20 10:27:52	ga_ls7e_ard_3-0-0_102073_2018-09-20_final
2018-09-20 10:28:16	ga_ls7e_ard_3-0-0_102074_2018-09-20_final
2018-09-20 10:28:40	ga_ls7e_ard_3-0-0_102075_2018-09-20_final
2018-09-20 10:29:28	ga_ls7e_ard_3-0-0_102077_2018-09-20_final
2018-09-20 10:29:52	ga_ls7e_ard_3-0-0_102078_2018-09-20_final
2018-09-20 10:30:16	ga_ls7e_ard_3-0-0_102079_2018-09-20_final
2018-09-20 10:30:40	ga_ls7e_ard_3-0-0_102080_2018-09-20_final
2018-09-21 09:32:38	ga_ls7e_ard_3-0-0_093074_2018-09-21_final
2018-09-21 09:33:02	ga_ls7e_ard_3-0-0_093075_2018-09-21_final
2018-09-21 09:33:26	ga_ls7e_ard_3-0-0_093076_2018-09-21_final
2018-09-21 09:33:49	ga_ls7e_ard_3-0-0_093077_2018-09-21_final
2018-09-21 09:34:13	ga_ls7e_ard_3-0-0_093078_2018-09-21_final
2018-09-21 09:34:37	ga_ls7e_ard_3-0-0_093079_2018-09-21_final
2018-09-21 09:35:01	ga_ls7e_ard_3-0-0_093080_2018-09-21_final
2018-09-21 09:35:25	ga_ls7e_ard_3-0-0_093081_2018-09-21_final
2018-09-21 09:35:49	ga_ls7e_ard_3-0-0_093082_2018-09-21_final
2018-09-21 09:36:13	ga_ls7e_ard_3-1-0_093083_2018-09-21_final
2018-09-21 09:36:37	ga_ls7e_ard_3-0-0_093084_2018-09-21_final
2018-09-21 09:37:01	ga_ls7e_ard_3-0-0_093085_2018-09-21_final
2018-09-21 09:37:25	ga_ls7e_ard_3-0-0_093086_2018-09-21_final
2018-09-21 09:37:49	ga_ls7e_ard_3-1-0_093087_2018-09-21_final
2018-09-21 09:38:13	ga_ls7e_ard_3-0-0_093088_2018-09-21_final
2018-09-21 11:09:55	ga_ls7e_ard_3-0-0_109070_2018-09-21_final
2018-09-21 11:10:19	ga_ls7e_ard_3-0-0_109071_2018-09-21_final
2018-09-21 11:10:43	ga_ls7e_ard_3-0-0_109072_2018-09-21_final
2018-09-21 11:11:07	ga_ls7e_ard_3-0-0_109073_2018-09-21_final
2018-09-21 11:11:31	ga_ls7e_ard_3-0-0_109074_2018-09-21_final
2018-09-21 11:11:54	ga_ls7e_ard_3-0-0_109075_2018-09-21_final
2018-09-21 11:12:18	ga_ls7e_ard_3-0-0_109076_2018-09-21_final
2018-09-21 11:12:42	ga_ls7e_ard_3-0-0_109077_2018-09-21_final
2018-09-21 11:13:06	ga_ls7e_ard_3-0-0_109078_2018-09-21_final
2018-09-21 11:13:30	ga_ls7e_ard_3-0-0_109079_2018-09-21_final
2018-09-21 11:13:54	ga_ls7e_ard_3-0-0_109080_2018-09-21_final
2018-09-21 11:14:18	ga_ls7e_ard_3-1-0_109081_2018-09-21_final
2018-09-21 11:14:42	ga_ls7e_ard_3-0-0_109082_2018-09-21_final
2018-09-21 11:15:06	ga_ls7e_ard_3-0-0_109083_2018-09-21_final
2018-09-21 11:15:30	ga_ls7e_ard_3-0-0_109084_2018-09-21_final
2018-09-22 10:14:40	ga_ls7e_ard_3-0-0_100071_2018-09-22_final
2018-09-22 10:15:04	ga_ls7e_ard_3-0-0_100072_2018-09-22_final
2018-09-22 10:15:28	ga_ls7e_ard_3-0-0_100073_2018-09-22_final
2018-09-22 10:15:52	ga_ls7e_ard_3-0-0_100074_2018-09-22_final
2018-09-22 10:16:16	ga_ls7e_ard_3-0-0_100075_2018-09-22_final
2018-09-22 10:16:40	ga_ls7e_ard_3-0-0_100076_2018-09-22_final
2018-09-22 10:17:04	ga_ls7e_ard_3-0-0_100077_2018-09-22_final
2018-09-22 10:17:28	ga_ls7e_ard_3-0-0_100078_2018-09-22_final
2018-09-22 10:17:52	ga_ls7e_ard_3-0-0_100079_2018-09-22_final
2018-09-22 10:18:16	ga_ls7e_ard_3-0-0_100080_2018-09-22_final
2018-09-22 10:18:39	ga_ls7e_ard_3-0-0_100081_2018-09-22_final
2018-09-22 10:19:03	ga_ls7e_ard_3-0-0_100082_2018-09-22_final
2018-09-22 10:19:27	ga_ls7e_ard_3-0-0_100083_2018-09-22_final
2018-09-22 10:19:51	ga_ls7e_ard_3-0-0_100084_2018-09-22_final
2018-09-30 09:26:38	ga_ls7e_ard_3-0-0_092075_2018-09-29_final
2018-09-30 09:27:02	ga_ls7e_ard_3-0-0_092076_2018-09-29_final
2018-09-30 09:27:26	ga_ls7e_ard_3-0-0_092077_2018-09-29_final
2018-09-30 09:27:50	ga_ls7e_ard_3-0-0_092078_2018-09-29_final
2018-09-30 09:28:14	ga_ls7e_ard_3-0-0_092079_2018-09-29_final
2018-09-30 09:28:38	ga_ls7e_ard_3-0-0_092080_2018-09-29_final
2018-09-30 09:29:02	ga_ls7e_ard_3-0-0_092081_2018-09-29_final
2018-09-30 09:29:26	ga_ls7e_ard_3-0-0_092082_2018-09-29_final
2018-09-30 09:30:14	ga_ls7e_ard_3-0-0_092084_2018-09-30_final
2018-09-30 09:30:37	ga_ls7e_ard_3-0-0_092085_2018-09-30_final
2018-09-30 09:31:01	ga_ls7e_ard_3-0-0_092086_2018-09-30_final
2018-09-30 09:31:25	ga_ls7e_ard_3-0-0_092087_2018-09-30_final
2018-09-30 11:03:07	ga_ls7e_ard_3-0-0_108069_2018-09-30_final
2018-09-30 11:03:31	ga_ls7e_ard_3-0-0_108070_2018-09-30_final
2018-09-30 11:03:55	ga_ls7e_ard_3-1-0_108071_2018-09-30_final
2018-09-30 11:04:19	ga_ls7e_ard_3-0-0_108072_2018-09-30_final
2018-09-30 11:04:43	ga_ls7e_ard_3-0-0_108073_2018-09-30_final
2018-09-30 11:05:07	ga_ls7e_ard_3-0-0_108074_2018-09-30_final
2018-09-30 11:05:31	ga_ls7e_ard_3-0-0_108075_2018-09-30_final
2018-09-30 11:06:19	ga_ls7e_ard_3-0-0_108077_2018-09-30_final
2018-09-30 11:06:43	ga_ls7e_ard_3-0-0_108078_2018-09-30_final
2018-09-30 11:07:07	ga_ls7e_ard_3-0-0_108079_2018-09-30_final

Return to ga_ls7e_ard_3 across September 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

September

All days