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
2018-04-01 10:03:55	ga_ls7e_ard_3-0-0_098067_2018-04-01_final
2018-04-01 10:04:43	ga_ls7e_ard_3-0-0_098069_2018-04-01_final
2018-04-01 10:05:07	ga_ls7e_ard_3-0-0_098070_2018-04-01_final
2018-04-01 10:05:31	ga_ls7e_ard_3-0-0_098071_2018-04-01_final
2018-04-01 10:05:55	ga_ls7e_ard_3-0-0_098072_2018-04-01_final
2018-04-01 10:06:19	ga_ls7e_ard_3-0-0_098073_2018-04-01_final
2018-04-01 10:06:43	ga_ls7e_ard_3-0-0_098074_2018-04-01_final
2018-04-01 10:07:07	ga_ls7e_ard_3-0-0_098075_2018-04-01_final
2018-04-01 10:07:30	ga_ls7e_ard_3-0-0_098076_2018-04-01_final
2018-04-01 10:07:54	ga_ls7e_ard_3-0-0_098077_2018-04-01_final
2018-04-01 10:08:18	ga_ls7e_ard_3-0-0_098078_2018-04-01_final
2018-04-01 10:08:42	ga_ls7e_ard_3-0-0_098079_2018-04-01_final
2018-04-01 10:09:06	ga_ls7e_ard_3-0-0_098080_2018-04-01_final
2018-04-01 10:09:30	ga_ls7e_ard_3-0-0_098081_2018-04-01_final
2018-04-01 10:09:54	ga_ls7e_ard_3-0-0_098082_2018-04-01_final
2018-04-01 10:10:18	ga_ls7e_ard_3-0-0_098083_2018-04-01_final
2018-04-01 10:10:42	ga_ls7e_ard_3-0-0_098084_2018-04-01_final
2018-04-01 10:11:06	ga_ls7e_ard_3-0-0_098085_2018-04-01_final
2018-04-01 11:42:48	ga_ls7e_ard_3-0-0_114067_2018-04-01_final
2018-04-01 11:45:36	ga_ls7e_ard_3-0-0_114074_2018-04-01_final
2018-04-01 11:46:00	ga_ls7e_ard_3-0-0_114075_2018-04-01_final
2018-04-01 11:46:24	ga_ls7e_ard_3-0-0_114076_2018-04-01_final
2018-04-01 11:46:47	ga_ls7e_ard_3-0-0_114077_2018-04-01_final
2018-04-01 11:47:11	ga_ls7e_ard_3-0-0_114078_2018-04-01_final
2018-04-01 11:47:35	ga_ls7e_ard_3-0-0_114079_2018-04-01_final
2018-04-01 11:47:59	ga_ls7e_ard_3-0-0_114080_2018-04-01_final
2018-04-01 11:48:23	ga_ls7e_ard_3-0-0_114081_2018-04-01_final
2018-04-02 09:12:40	ga_ls7e_ard_3-0-0_089078_2018-04-01_final
2018-04-02 09:13:04	ga_ls7e_ard_3-0-0_089079_2018-04-01_final
2018-04-02 09:13:28	ga_ls7e_ard_3-0-0_089080_2018-04-01_final
2018-04-02 09:13:52	ga_ls7e_ard_3-1-0_089081_2018-04-01_final
2018-04-02 09:14:16	ga_ls7e_ard_3-0-0_089082_2018-04-01_final
2018-04-02 09:14:40	ga_ls7e_ard_3-0-0_089083_2018-04-01_final
2018-04-02 09:15:04	ga_ls7e_ard_3-0-0_089084_2018-04-01_final
2018-04-02 09:15:28	ga_ls7e_ard_3-0-0_089085_2018-04-01_final
2018-04-02 09:15:52	ga_ls7e_ard_3-0-0_089086_2018-04-01_final
2018-04-02 10:47:34	ga_ls7e_ard_3-0-0_105068_2018-04-02_final
2018-04-02 10:47:58	ga_ls7e_ard_3-0-0_105069_2018-04-02_final
2018-04-02 10:48:22	ga_ls7e_ard_3-0-0_105070_2018-04-02_final
2018-04-02 10:48:46	ga_ls7e_ard_3-0-0_105071_2018-04-02_final
2018-04-02 10:49:10	ga_ls7e_ard_3-0-0_105072_2018-04-02_final
2018-04-02 10:49:33	ga_ls7e_ard_3-0-0_105073_2018-04-02_final
2018-04-02 10:49:57	ga_ls7e_ard_3-0-0_105074_2018-04-02_final
2018-04-02 10:50:21	ga_ls7e_ard_3-0-0_105075_2018-04-02_final
2018-04-02 10:50:45	ga_ls7e_ard_3-0-0_105076_2018-04-02_final
2018-04-02 10:51:09	ga_ls7e_ard_3-0-0_105077_2018-04-02_final
2018-04-02 10:51:33	ga_ls7e_ard_3-0-0_105078_2018-04-02_final
2018-04-02 10:51:57	ga_ls7e_ard_3-0-0_105079_2018-04-02_final
2018-04-02 10:52:21	ga_ls7e_ard_3-1-0_105080_2018-04-02_final
2018-04-02 10:52:45	ga_ls7e_ard_3-0-0_105081_2018-04-02_final
2018-04-02 10:53:09	ga_ls7e_ard_3-0-0_105082_2018-04-02_final
2018-04-03 09:51:32	ga_ls7e_ard_3-0-0_096067_2018-04-03_final
2018-04-03 09:52:43	ga_ls7e_ard_3-0-0_096070_2018-04-03_final
2018-04-03 09:53:07	ga_ls7e_ard_3-0-0_096071_2018-04-03_final
2018-04-03 09:53:31	ga_ls7e_ard_3-0-0_096072_2018-04-03_final
2018-04-03 09:53:55	ga_ls7e_ard_3-0-0_096073_2018-04-03_final
2018-04-03 09:54:19	ga_ls7e_ard_3-0-0_096074_2018-04-03_final
2018-04-03 09:54:43	ga_ls7e_ard_3-0-0_096075_2018-04-03_final
2018-04-03 09:55:07	ga_ls7e_ard_3-0-0_096076_2018-04-03_final
2018-04-03 09:55:31	ga_ls7e_ard_3-0-0_096077_2018-04-03_final
2018-04-03 09:55:55	ga_ls7e_ard_3-0-0_096078_2018-04-03_final
2018-04-03 09:56:19	ga_ls7e_ard_3-0-0_096079_2018-04-03_final
2018-04-03 09:56:43	ga_ls7e_ard_3-0-0_096080_2018-04-03_final
2018-04-03 09:57:07	ga_ls7e_ard_3-0-0_096081_2018-04-03_final
2018-04-03 09:57:31	ga_ls7e_ard_3-0-0_096082_2018-04-03_final
2018-04-03 09:57:55	ga_ls7e_ard_3-0-0_096083_2018-04-03_final
2018-04-03 09:58:19	ga_ls7e_ard_3-0-0_096084_2018-04-03_final
2018-04-03 09:58:43	ga_ls7e_ard_3-0-0_096085_2018-04-03_final
2018-04-03 11:33:12	ga_ls7e_ard_3-1-0_112074_2018-04-03_final
2018-04-03 11:33:36	ga_ls7e_ard_3-0-0_112075_2018-04-03_final
2018-04-03 11:34:00	ga_ls7e_ard_3-0-0_112076_2018-04-03_final
2018-04-03 11:34:24	ga_ls7e_ard_3-0-0_112077_2018-04-03_final
2018-04-03 11:34:48	ga_ls7e_ard_3-0-0_112078_2018-04-03_final
2018-04-03 11:35:12	ga_ls7e_ard_3-0-0_112079_2018-04-03_final
2018-04-03 11:35:36	ga_ls7e_ard_3-0-0_112080_2018-04-03_final
2018-04-03 11:36:00	ga_ls7e_ard_3-0-0_112081_2018-04-03_final
2018-04-03 11:36:24	ga_ls7e_ard_3-0-0_112082_2018-04-03_final
2018-04-03 11:36:48	ga_ls7e_ard_3-0-0_112083_2018-04-03_final
2018-04-03 11:37:12	ga_ls7e_ard_3-0-0_112084_2018-04-03_final
2018-04-05 09:39:08	ga_ls7e_ard_3-0-0_094067_2018-04-05_final
2018-04-05 09:41:32	ga_ls7e_ard_3-0-0_094073_2018-04-05_final
2018-04-05 09:41:56	ga_ls7e_ard_3-0-0_094074_2018-04-05_final
2018-04-05 09:42:20	ga_ls7e_ard_3-0-0_094075_2018-04-05_final
2018-04-05 09:42:44	ga_ls7e_ard_3-0-0_094076_2018-04-05_final
2018-04-05 09:43:08	ga_ls7e_ard_3-0-0_094077_2018-04-05_final
2018-04-05 09:43:31	ga_ls7e_ard_3-0-0_094078_2018-04-05_final
2018-04-05 09:43:55	ga_ls7e_ard_3-0-0_094079_2018-04-05_final
2018-04-07 09:30:20	ga_ls7e_ard_3-0-0_092076_2018-04-07_final
2018-04-07 09:30:44	ga_ls7e_ard_3-0-0_092077_2018-04-07_final
2018-04-07 09:31:08	ga_ls7e_ard_3-0-0_092078_2018-04-07_final
2018-04-07 09:31:32	ga_ls7e_ard_3-0-0_092079_2018-04-07_final
2018-04-07 09:31:56	ga_ls7e_ard_3-0-0_092080_2018-04-07_final
2018-04-07 09:32:20	ga_ls7e_ard_3-0-0_092081_2018-04-07_final
2018-04-07 09:32:44	ga_ls7e_ard_3-0-0_092082_2018-04-07_final
2018-04-07 09:33:08	ga_ls7e_ard_3-0-0_092083_2018-04-07_final
2018-04-07 09:33:32	ga_ls7e_ard_3-0-0_092084_2018-04-07_final
2018-04-07 09:33:56	ga_ls7e_ard_3-0-0_092085_2018-04-07_final
2018-04-07 09:34:20	ga_ls7e_ard_3-0-0_092086_2018-04-07_final
2018-04-07 09:34:44	ga_ls7e_ard_3-0-0_092087_2018-04-07_final
2018-04-07 09:35:07	ga_ls7e_ard_3-0-0_092088_2018-04-07_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

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2018

April

All days