Search ga_ls7e_ard_3 across May 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
2017-05-03 10:36:42	ga_ls7e_ard_3-0-0_103068_2017-05-03_final
2017-05-03 10:37:06	ga_ls7e_ard_3-0-0_103069_2017-05-03_final
2017-05-03 10:37:30	ga_ls7e_ard_3-0-0_103070_2017-05-03_final
2017-05-03 10:37:54	ga_ls7e_ard_3-0-0_103071_2017-05-03_final
2017-05-03 10:38:18	ga_ls7e_ard_3-0-0_103072_2017-05-03_final
2017-05-03 10:38:42	ga_ls7e_ard_3-0-0_103073_2017-05-03_final
2017-05-03 10:39:05	ga_ls7e_ard_3-0-0_103074_2017-05-03_final
2017-05-03 10:39:29	ga_ls7e_ard_3-0-0_103075_2017-05-03_final
2017-05-03 10:39:53	ga_ls7e_ard_3-0-0_103076_2017-05-03_final
2017-05-03 10:40:17	ga_ls7e_ard_3-0-0_103077_2017-05-03_final
2017-05-03 10:40:41	ga_ls7e_ard_3-0-0_103078_2017-05-03_final
2017-05-03 10:41:05	ga_ls7e_ard_3-0-0_103079_2017-05-03_final
2017-05-03 10:41:29	ga_ls7e_ard_3-0-0_103080_2017-05-03_final
2017-05-03 10:41:53	ga_ls7e_ard_3-0-0_103081_2017-05-03_final
2017-05-03 10:42:17	ga_ls7e_ard_3-0-0_103082_2017-05-03_final
2017-05-04 09:40:41	ga_ls7e_ard_3-1-0_094067_2017-05-04_final
2017-05-04 09:43:04	ga_ls7e_ard_3-0-0_094073_2017-05-04_final
2017-05-04 09:43:28	ga_ls7e_ard_3-0-0_094074_2017-05-04_final
2017-05-04 09:43:52	ga_ls7e_ard_3-0-0_094075_2017-05-04_final
2017-05-04 09:44:16	ga_ls7e_ard_3-0-0_094076_2017-05-04_final
2017-05-04 09:44:40	ga_ls7e_ard_3-0-0_094077_2017-05-04_final
2017-05-04 09:45:04	ga_ls7e_ard_3-0-0_094078_2017-05-04_final
2017-05-04 09:45:28	ga_ls7e_ard_3-0-0_094079_2017-05-04_final
2017-05-04 09:45:52	ga_ls7e_ard_3-0-0_094080_2017-05-04_final
2017-05-04 09:46:16	ga_ls7e_ard_3-0-0_094081_2017-05-04_final
2017-05-04 09:46:40	ga_ls7e_ard_3-0-0_094082_2017-05-04_final
2017-05-04 09:47:04	ga_ls7e_ard_3-1-0_094083_2017-05-04_final
2017-05-04 09:47:28	ga_ls7e_ard_3-0-0_094084_2017-05-04_final
2017-05-04 09:47:52	ga_ls7e_ard_3-0-0_094085_2017-05-04_final
2017-05-04 09:48:16	ga_ls7e_ard_3-0-0_094086_2017-05-04_final
2017-05-04 09:48:40	ga_ls7e_ard_3-0-0_094087_2017-05-04_final
2017-05-05 10:25:32	ga_ls7e_ard_3-0-0_101071_2017-05-05_final
2017-05-05 10:25:56	ga_ls7e_ard_3-0-0_101072_2017-05-05_final
2017-05-05 10:26:20	ga_ls7e_ard_3-0-0_101073_2017-05-05_final
2017-05-05 10:26:44	ga_ls7e_ard_3-0-0_101074_2017-05-05_final
2017-05-05 10:27:08	ga_ls7e_ard_3-1-0_101075_2017-05-05_final
2017-05-05 10:27:32	ga_ls7e_ard_3-0-0_101076_2017-05-05_final
2017-05-05 10:27:56	ga_ls7e_ard_3-0-0_101077_2017-05-05_final
2017-05-05 10:28:20	ga_ls7e_ard_3-0-0_101078_2017-05-05_final
2017-05-05 10:28:44	ga_ls7e_ard_3-0-0_101079_2017-05-05_final
2017-05-05 10:29:08	ga_ls7e_ard_3-0-0_101080_2017-05-05_final
2017-05-05 10:29:32	ga_ls7e_ard_3-0-0_101081_2017-05-05_final
2017-05-05 10:29:56	ga_ls7e_ard_3-0-0_101082_2017-05-05_final
2017-05-05 10:30:20	ga_ls7e_ard_3-0-0_101083_2017-05-05_final
2017-05-06 09:31:31	ga_ls7e_ard_3-0-0_092075_2017-05-06_final
2017-05-06 09:31:55	ga_ls7e_ard_3-0-0_092076_2017-05-06_final
2017-05-06 09:32:19	ga_ls7e_ard_3-0-0_092077_2017-05-06_final
2017-05-06 09:32:43	ga_ls7e_ard_3-0-0_092078_2017-05-06_final
2017-05-06 09:33:07	ga_ls7e_ard_3-0-0_092079_2017-05-06_final
2017-05-06 09:33:31	ga_ls7e_ard_3-0-0_092080_2017-05-06_final
2017-05-06 09:33:55	ga_ls7e_ard_3-0-0_092081_2017-05-06_final
2017-05-06 09:34:19	ga_ls7e_ard_3-0-0_092082_2017-05-06_final
2017-05-06 09:34:43	ga_ls7e_ard_3-0-0_092083_2017-05-06_final
2017-05-06 09:35:07	ga_ls7e_ard_3-0-0_092084_2017-05-06_final
2017-05-06 09:35:31	ga_ls7e_ard_3-0-0_092085_2017-05-06_final
2017-05-06 09:35:55	ga_ls7e_ard_3-0-0_092086_2017-05-06_final
2017-05-06 09:36:19	ga_ls7e_ard_3-0-0_092087_2017-05-06_final
2017-05-06 11:08:01	ga_ls7e_ard_3-0-0_108069_2017-05-06_final
2017-05-06 11:08:24	ga_ls7e_ard_3-0-0_108070_2017-05-06_final
2017-05-30 10:19:27	ga_ls7e_ard_3-0-0_100071_2017-05-30_final
2017-05-30 10:19:51	ga_ls7e_ard_3-0-0_100072_2017-05-30_final
2017-05-30 10:20:15	ga_ls7e_ard_3-0-0_100073_2017-05-30_final
2017-05-30 10:20:39	ga_ls7e_ard_3-0-0_100074_2017-05-30_final
2017-05-30 10:21:03	ga_ls7e_ard_3-0-0_100075_2017-05-30_final
2017-05-30 10:21:27	ga_ls7e_ard_3-0-0_100076_2017-05-30_final
2017-05-30 10:21:51	ga_ls7e_ard_3-0-0_100077_2017-05-30_final
2017-05-30 10:22:14	ga_ls7e_ard_3-0-0_100078_2017-05-30_final
2017-05-30 10:22:38	ga_ls7e_ard_3-0-0_100079_2017-05-30_final
2017-05-30 10:23:02	ga_ls7e_ard_3-0-0_100080_2017-05-30_final
2017-05-30 10:23:26	ga_ls7e_ard_3-1-0_100081_2017-05-30_final
2017-05-30 10:23:50	ga_ls7e_ard_3-0-0_100082_2017-05-30_final
2017-05-30 10:24:14	ga_ls7e_ard_3-0-0_100083_2017-05-30_final
2017-05-30 10:24:38	ga_ls7e_ard_3-0-0_100084_2017-05-30_final
2017-05-31 09:25:50	ga_ls7e_ard_3-0-0_091076_2017-05-30_final
2017-05-31 09:26:14	ga_ls7e_ard_3-0-0_091077_2017-05-30_final
2017-05-31 09:26:37	ga_ls7e_ard_3-0-0_091078_2017-05-30_final
2017-05-31 09:27:01	ga_ls7e_ard_3-0-0_091079_2017-05-30_final
2017-05-31 09:27:25	ga_ls7e_ard_3-0-0_091080_2017-05-30_final
2017-05-31 09:27:49	ga_ls7e_ard_3-0-0_091081_2017-05-30_final
2017-05-31 09:28:13	ga_ls7e_ard_3-0-0_091082_2017-05-30_final
2017-05-31 09:28:37	ga_ls7e_ard_3-0-0_091083_2017-05-30_final
2017-05-31 09:29:01	ga_ls7e_ard_3-0-0_091084_2017-05-30_final
2017-05-31 09:29:25	ga_ls7e_ard_3-0-0_091085_2017-05-30_final
2017-05-31 09:30:13	ga_ls7e_ard_3-0-0_091087_2017-05-31_final
2017-05-31 09:30:37	ga_ls7e_ard_3-0-0_091088_2017-05-31_final
2017-05-31 09:31:01	ga_ls7e_ard_3-0-0_091089_2017-05-31_final
2017-05-31 11:02:19	ga_ls7e_ard_3-0-0_107070_2017-05-31_final
2017-05-31 11:02:43	ga_ls7e_ard_3-0-0_107071_2017-05-31_final
2017-05-31 11:03:07	ga_ls7e_ard_3-0-0_107072_2017-05-31_final
2017-05-31 11:03:31	ga_ls7e_ard_3-0-0_107073_2017-05-31_final
2017-05-31 11:03:55	ga_ls7e_ard_3-0-0_107074_2017-05-31_final
2017-05-31 11:04:19	ga_ls7e_ard_3-0-0_107075_2017-05-31_final
2017-05-31 11:04:43	ga_ls7e_ard_3-0-0_107076_2017-05-31_final
2017-05-31 11:05:07	ga_ls7e_ard_3-0-0_107077_2017-05-31_final
2017-05-31 11:05:31	ga_ls7e_ard_3-0-0_107078_2017-05-31_final
2017-05-31 11:05:54	ga_ls7e_ard_3-0-0_107079_2017-05-31_final
2017-05-31 11:06:18	ga_ls7e_ard_3-0-0_107080_2017-05-31_final
2017-05-31 11:06:42	ga_ls7e_ard_3-0-0_107081_2017-05-31_final
2017-05-31 11:07:06	ga_ls7e_ard_3-0-0_107082_2017-05-31_final
2017-05-31 11:07:30	ga_ls7e_ard_3-0-0_107083_2017-05-31_final

Return to ga_ls7e_ard_3 across May 2017 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2017

May

All days