Search ga_ls7e_ard_3 across June 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
2017-06-01 10:05:30	ga_ls7e_ard_3-0-0_098067_2017-06-01_final
2017-06-01 10:06:42	ga_ls7e_ard_3-0-0_098070_2017-06-01_final
2017-06-01 10:07:06	ga_ls7e_ard_3-0-0_098071_2017-06-01_final
2017-06-01 10:07:30	ga_ls7e_ard_3-0-0_098072_2017-06-01_final
2017-06-01 10:07:54	ga_ls7e_ard_3-0-0_098073_2017-06-01_final
2017-06-01 10:08:18	ga_ls7e_ard_3-0-0_098074_2017-06-01_final
2017-06-01 10:08:42	ga_ls7e_ard_3-0-0_098075_2017-06-01_final
2017-06-01 10:09:06	ga_ls7e_ard_3-0-0_098076_2017-06-01_final
2017-06-01 10:09:30	ga_ls7e_ard_3-0-0_098077_2017-06-01_final
2017-06-01 10:09:54	ga_ls7e_ard_3-0-0_098078_2017-06-01_final
2017-06-01 10:10:17	ga_ls7e_ard_3-0-0_098079_2017-06-01_final
2017-06-01 10:10:41	ga_ls7e_ard_3-0-0_098080_2017-06-01_final
2017-06-01 10:11:05	ga_ls7e_ard_3-0-0_098081_2017-06-01_final
2017-06-01 10:11:29	ga_ls7e_ard_3-0-0_098082_2017-06-01_final
2017-06-01 10:11:53	ga_ls7e_ard_3-0-0_098083_2017-06-01_final
2017-06-01 10:12:17	ga_ls7e_ard_3-0-0_098084_2017-06-01_final
2017-06-01 10:12:41	ga_ls7e_ard_3-0-0_098085_2017-06-01_final
2017-06-01 11:44:23	ga_ls7e_ard_3-0-0_114067_2017-06-01_final
2017-06-01 11:47:11	ga_ls7e_ard_3-0-0_114074_2017-06-01_final
2017-06-01 11:47:35	ga_ls7e_ard_3-0-0_114075_2017-06-01_final
2017-06-01 11:47:59	ga_ls7e_ard_3-0-0_114076_2017-06-01_final
2017-06-01 11:48:23	ga_ls7e_ard_3-0-0_114077_2017-06-01_final
2017-06-01 11:48:47	ga_ls7e_ard_3-0-0_114078_2017-06-01_final
2017-06-01 11:49:11	ga_ls7e_ard_3-0-0_114079_2017-06-01_final
2017-06-01 11:49:34	ga_ls7e_ard_3-0-0_114080_2017-06-01_final
2017-06-01 11:49:58	ga_ls7e_ard_3-0-0_114081_2017-06-01_final
2017-06-02 09:14:16	ga_ls7e_ard_3-0-0_089078_2017-06-01_final
2017-06-02 09:14:40	ga_ls7e_ard_3-0-0_089079_2017-06-01_final
2017-06-02 09:15:04	ga_ls7e_ard_3-0-0_089080_2017-06-01_final
2017-06-02 09:15:28	ga_ls7e_ard_3-1-0_089081_2017-06-01_final
2017-06-02 09:15:52	ga_ls7e_ard_3-0-0_089082_2017-06-01_final
2017-06-02 09:16:16	ga_ls7e_ard_3-0-0_089083_2017-06-01_final
2017-06-02 09:16:40	ga_ls7e_ard_3-0-0_089084_2017-06-01_final
2017-06-02 09:17:04	ga_ls7e_ard_3-0-0_089085_2017-06-01_final
2017-06-02 09:17:28	ga_ls7e_ard_3-0-0_089086_2017-06-01_final
2017-06-02 10:49:10	ga_ls7e_ard_3-0-0_105068_2017-06-02_final
2017-06-02 10:49:34	ga_ls7e_ard_3-0-0_105069_2017-06-02_final
2017-06-02 10:49:58	ga_ls7e_ard_3-0-0_105070_2017-06-02_final
2017-06-02 10:50:22	ga_ls7e_ard_3-0-0_105071_2017-06-02_final
2017-06-02 10:50:46	ga_ls7e_ard_3-0-0_105072_2017-06-02_final
2017-06-02 10:51:10	ga_ls7e_ard_3-0-0_105073_2017-06-02_final
2017-06-02 10:51:34	ga_ls7e_ard_3-0-0_105074_2017-06-02_final
2017-06-02 10:51:58	ga_ls7e_ard_3-0-0_105075_2017-06-02_final
2017-06-02 10:52:22	ga_ls7e_ard_3-0-0_105076_2017-06-02_final
2017-06-02 10:52:46	ga_ls7e_ard_3-0-0_105077_2017-06-02_final
2017-06-02 10:53:10	ga_ls7e_ard_3-0-0_105078_2017-06-02_final
2017-06-02 10:53:33	ga_ls7e_ard_3-0-0_105079_2017-06-02_final
2017-06-02 10:53:57	ga_ls7e_ard_3-1-0_105080_2017-06-02_final
2017-06-02 10:54:21	ga_ls7e_ard_3-0-0_105081_2017-06-02_final
2017-06-02 10:54:45	ga_ls7e_ard_3-0-0_105082_2017-06-02_final
2017-06-03 09:53:09	ga_ls7e_ard_3-0-0_096067_2017-06-03_final
2017-06-03 09:54:21	ga_ls7e_ard_3-0-0_096070_2017-06-03_final
2017-06-03 09:54:45	ga_ls7e_ard_3-0-0_096071_2017-06-03_final
2017-06-03 09:55:09	ga_ls7e_ard_3-0-0_096072_2017-06-03_final
2017-06-03 09:55:33	ga_ls7e_ard_3-0-0_096073_2017-06-03_final
2017-06-03 09:55:57	ga_ls7e_ard_3-0-0_096074_2017-06-03_final
2017-06-03 09:56:21	ga_ls7e_ard_3-0-0_096075_2017-06-03_final
2017-06-03 09:56:45	ga_ls7e_ard_3-0-0_096076_2017-06-03_final
2017-06-03 09:57:09	ga_ls7e_ard_3-0-0_096077_2017-06-03_final
2017-06-03 09:57:32	ga_ls7e_ard_3-0-0_096078_2017-06-03_final
2017-06-03 09:57:56	ga_ls7e_ard_3-0-0_096079_2017-06-03_final
2017-06-03 09:58:20	ga_ls7e_ard_3-0-0_096080_2017-06-03_final
2017-06-03 09:58:44	ga_ls7e_ard_3-0-0_096081_2017-06-03_final
2017-06-03 09:59:08	ga_ls7e_ard_3-0-0_096082_2017-06-03_final
2017-06-03 09:59:32	ga_ls7e_ard_3-0-0_096083_2017-06-03_final
2017-06-03 09:59:56	ga_ls7e_ard_3-0-0_096084_2017-06-03_final
2017-06-03 10:00:20	ga_ls7e_ard_3-0-0_096085_2017-06-03_final
2017-06-03 10:00:44	ga_ls7e_ard_3-1-0_096086_2017-06-03_final
2017-06-03 11:32:02	ga_ls7e_ard_3-0-0_112067_2017-06-03_final
2017-06-03 11:34:50	ga_ls7e_ard_3-0-0_112074_2017-06-03_final
2017-06-03 11:35:14	ga_ls7e_ard_3-0-0_112075_2017-06-03_final
2017-06-03 11:35:38	ga_ls7e_ard_3-0-0_112076_2017-06-03_final
2017-06-03 11:36:02	ga_ls7e_ard_3-0-0_112077_2017-06-03_final
2017-06-03 11:36:26	ga_ls7e_ard_3-0-0_112078_2017-06-03_final
2017-06-03 11:36:50	ga_ls7e_ard_3-1-0_112079_2017-06-03_final
2017-06-03 11:37:13	ga_ls7e_ard_3-0-0_112080_2017-06-03_final
2017-06-03 11:37:37	ga_ls7e_ard_3-0-0_112081_2017-06-03_final
2017-06-03 11:38:01	ga_ls7e_ard_3-0-0_112082_2017-06-03_final
2017-06-03 11:38:25	ga_ls7e_ard_3-0-0_112083_2017-06-03_final
2017-06-04 10:36:49	ga_ls7e_ard_3-0-0_103068_2017-06-04_final
2017-06-04 10:37:13	ga_ls7e_ard_3-0-0_103069_2017-06-04_final
2017-06-04 10:37:37	ga_ls7e_ard_3-0-0_103070_2017-06-04_final
2017-06-04 10:38:01	ga_ls7e_ard_3-0-0_103071_2017-06-04_final
2017-06-04 10:38:25	ga_ls7e_ard_3-0-0_103072_2017-06-04_final
2017-06-04 10:38:49	ga_ls7e_ard_3-0-0_103073_2017-06-04_final
2017-06-04 10:39:13	ga_ls7e_ard_3-0-0_103074_2017-06-04_final
2017-06-04 10:39:37	ga_ls7e_ard_3-0-0_103075_2017-06-04_final
2017-06-04 10:40:01	ga_ls7e_ard_3-0-0_103076_2017-06-04_final
2017-06-04 10:40:25	ga_ls7e_ard_3-0-0_103077_2017-06-04_final
2017-06-04 10:40:48	ga_ls7e_ard_3-0-0_103078_2017-06-04_final
2017-06-04 10:41:12	ga_ls7e_ard_3-0-0_103079_2017-06-04_final
2017-06-04 10:41:36	ga_ls7e_ard_3-0-0_103080_2017-06-04_final
2017-06-04 10:42:00	ga_ls7e_ard_3-0-0_103081_2017-06-04_final
2017-06-04 10:42:24	ga_ls7e_ard_3-0-0_103082_2017-06-04_final
2017-06-05 09:40:48	ga_ls7e_ard_3-1-0_094067_2017-06-05_final
2017-06-14 09:37:27	ga_ls7e_ard_3-0-0_093074_2017-06-14_final
2017-06-14 09:37:51	ga_ls7e_ard_3-0-0_093075_2017-06-14_final
2017-06-14 09:38:15	ga_ls7e_ard_3-0-0_093076_2017-06-14_final
2017-06-14 09:38:39	ga_ls7e_ard_3-0-0_093077_2017-06-14_final
2017-06-14 09:39:03	ga_ls7e_ard_3-0-0_093078_2017-06-14_final

Return to ga_ls7e_ard_3 across June 2017 overview

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

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2017

June

All days