Search ga_ls7e_ard_3 whole collection

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
2022-03-01 09:48:20	ga_ls7e_ard_3-2-1_108072_2022-03-01_final
2022-03-03 09:34:11	ga_ls7e_ard_3-2-1_106068_2022-03-03_final
2022-03-03 09:34:59	ga_ls7e_ard_3-2-1_106070_2022-03-03_final
2022-03-03 09:35:23	ga_ls7e_ard_3-2-1_106071_2022-03-03_final
2022-03-05 09:24:01	ga_ls7e_ard_3-2-1_104074_2022-03-04_final
2022-03-05 09:24:25	ga_ls7e_ard_3-2-1_104075_2022-03-04_final
2022-03-05 09:24:49	ga_ls7e_ard_3-2-1_104076_2022-03-04_final
2022-03-05 09:25:13	ga_ls7e_ard_3-2-1_104077_2022-03-04_final
2022-03-05 09:25:37	ga_ls7e_ard_3-2-1_104078_2022-03-04_final
2022-03-05 09:26:01	ga_ls7e_ard_3-2-1_104079_2022-03-04_final
2022-03-05 09:27:13	ga_ls7e_ard_3-2-1_104082_2022-03-04_final
2022-03-12 09:27:31	ga_ls7e_ard_3-2-1_105069_2022-03-11_final
2022-03-12 09:27:54	ga_ls7e_ard_3-2-1_105070_2022-03-11_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-12 09:28:42	ga_ls7e_ard_3-2-1_105072_2022-03-11_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-12 09:29:30	ga_ls7e_ard_3-2-1_105074_2022-03-11_final
2022-03-12 09:29:54	ga_ls7e_ard_3-2-1_105075_2022-03-11_final
2022-03-12 09:30:18	ga_ls7e_ard_3-2-1_105076_2022-03-12_final
2022-03-12 09:31:06	ga_ls7e_ard_3-2-1_105078_2022-03-12_final
2022-03-12 09:31:30	ga_ls7e_ard_3-2-1_105079_2022-03-12_final
2022-03-12 09:31:54	ga_ls7e_ard_3-2-1_105080_2022-03-12_final
2022-03-12 09:32:18	ga_ls7e_ard_3-2-1_105081_2022-03-12_final
2022-03-12 09:32:42	ga_ls7e_ard_3-2-1_105082_2022-03-12_final
2022-03-14 09:18:32	ga_ls7e_ard_3-2-1_103078_2022-03-13_final
2022-03-14 09:19:20	ga_ls7e_ard_3-2-1_103080_2022-03-13_final
2022-03-17 09:45:56	ga_ls7e_ard_3-2-1_108070_2022-03-17_final
2022-03-17 09:46:20	ga_ls7e_ard_3-2-1_108071_2022-03-17_final
2022-03-17 09:46:44	ga_ls7e_ard_3-2-1_108072_2022-03-17_final
2022-03-17 09:47:08	ga_ls7e_ard_3-2-1_108073_2022-03-17_final
2022-03-19 09:32:35	ga_ls7e_ard_3-2-1_106068_2022-03-19_final
2022-03-19 09:32:59	ga_ls7e_ard_3-2-1_106069_2022-03-19_final
2022-03-19 09:33:23	ga_ls7e_ard_3-2-1_106070_2022-03-19_final
2022-03-19 09:33:47	ga_ls7e_ard_3-2-1_106071_2022-03-19_final
2022-03-19 09:34:11	ga_ls7e_ard_3-2-1_106072_2022-03-19_final
2022-03-19 09:34:35	ga_ls7e_ard_3-2-1_106073_2022-03-19_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-19 09:35:22	ga_ls7e_ard_3-2-1_106075_2022-03-19_final
2022-03-19 09:35:46	ga_ls7e_ard_3-2-1_106076_2022-03-19_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-19 09:36:58	ga_ls7e_ard_3-2-1_106079_2022-03-19_final
2022-03-19 09:37:22	ga_ls7e_ard_3-2-1_106080_2022-03-19_final
2022-03-19 09:37:46	ga_ls7e_ard_3-2-1_106081_2022-03-19_final
2022-03-21 09:22:26	ga_ls7e_ard_3-2-1_104074_2022-03-20_final
2022-03-21 09:22:50	ga_ls7e_ard_3-2-1_104075_2022-03-20_final
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-21 09:24:02	ga_ls7e_ard_3-2-1_104078_2022-03-20_final
2022-03-21 09:24:26	ga_ls7e_ard_3-2-1_104079_2022-03-20_final
2022-03-21 09:24:50	ga_ls7e_ard_3-2-1_104080_2022-03-20_final
2022-03-21 09:25:13	ga_ls7e_ard_3-2-1_104081_2022-03-20_final
2022-03-26 09:38:55	ga_ls7e_ard_3-2-1_107070_2022-03-26_final
2022-03-26 09:39:18	ga_ls7e_ard_3-2-1_107071_2022-03-26_final
2022-03-26 09:39:42	ga_ls7e_ard_3-2-1_107072_2022-03-26_final
2022-03-26 09:40:06	ga_ls7e_ard_3-2-1_107073_2022-03-26_final
2022-03-26 09:40:30	ga_ls7e_ard_3-2-1_107074_2022-03-26_final
2022-03-26 09:40:54	ga_ls7e_ard_3-2-1_107075_2022-03-26_final
2022-03-26 09:41:18	ga_ls7e_ard_3-2-1_107076_2022-03-26_final
2022-03-26 09:41:42	ga_ls7e_ard_3-2-1_107077_2022-03-26_final
2022-03-28 09:25:58	ga_ls7e_ard_3-2-1_105069_2022-03-27_final
2022-03-28 09:26:22	ga_ls7e_ard_3-2-1_105070_2022-03-27_final
2022-03-28 09:26:46	ga_ls7e_ard_3-2-1_105071_2022-03-27_final
2022-03-28 09:27:09	ga_ls7e_ard_3-2-1_105072_2022-03-27_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-28 09:27:57	ga_ls7e_ard_3-2-1_105074_2022-03-27_final
2022-03-28 09:28:21	ga_ls7e_ard_3-2-1_105075_2022-03-27_final
2022-03-28 09:28:45	ga_ls7e_ard_3-2-1_105076_2022-03-27_final
2022-03-28 09:29:09	ga_ls7e_ard_3-2-1_105077_2022-03-27_final
2022-03-28 09:29:33	ga_ls7e_ard_3-2-1_105078_2022-03-27_final
2022-03-28 09:29:57	ga_ls7e_ard_3-2-1_105079_2022-03-27_final
2022-03-30 09:17:00	ga_ls7e_ard_3-2-1_103078_2022-03-29_final
2022-03-30 09:17:24	ga_ls7e_ard_3-2-1_103079_2022-03-29_final
2022-04-02 09:44:01	ga_ls7e_ard_3-2-1_108069_2022-04-02_final
2022-04-02 09:44:25	ga_ls7e_ard_3-2-1_108070_2022-04-02_final
2022-04-02 09:44:49	ga_ls7e_ard_3-2-1_108071_2022-04-02_final
2022-04-02 09:45:13	ga_ls7e_ard_3-2-1_108072_2022-04-02_final
2022-04-02 09:45:37	ga_ls7e_ard_3-2-1_108073_2022-04-02_final
2022-04-04 09:31:03	ga_ls7e_ard_3-2-1_106068_2022-04-04_final
2022-04-04 09:31:27	ga_ls7e_ard_3-2-1_106069_2022-04-04_final
2022-04-04 09:31:51	ga_ls7e_ard_3-2-1_106070_2022-04-04_final
2022-04-04 09:32:15	ga_ls7e_ard_3-2-1_106071_2022-04-04_final
2022-04-04 09:32:39	ga_ls7e_ard_3-2-1_106072_2022-04-04_final
2022-04-04 09:33:03	ga_ls7e_ard_3-2-1_106073_2022-04-04_final
2022-04-04 09:33:27	ga_ls7e_ard_3-2-1_106074_2022-04-04_final
2022-04-04 09:33:51	ga_ls7e_ard_3-2-1_106075_2022-04-04_final
2022-04-04 09:34:15	ga_ls7e_ard_3-2-1_106076_2022-04-04_final
2022-04-04 09:34:39	ga_ls7e_ard_3-2-1_106077_2022-04-04_final
2022-04-04 09:35:03	ga_ls7e_ard_3-2-1_106078_2022-04-04_final
2022-04-04 09:35:27	ga_ls7e_ard_3-2-1_106079_2022-04-04_final
2022-04-04 09:35:51	ga_ls7e_ard_3-2-1_106080_2022-04-04_final
2022-04-04 09:36:15	ga_ls7e_ard_3-2-1_106081_2022-04-04_final
2022-04-06 09:20:53	ga_ls7e_ard_3-2-1_104074_2022-04-05_final
2022-04-06 09:21:17	ga_ls7e_ard_3-2-1_104075_2022-04-05_final
2022-04-06 09:21:41	ga_ls7e_ard_3-2-1_104076_2022-04-05_final
2022-04-06 09:22:05	ga_ls7e_ard_3-2-1_104077_2022-04-05_final
2022-04-06 09:22:29	ga_ls7e_ard_3-2-1_104078_2022-04-05_final
2022-04-06 09:22:53	ga_ls7e_ard_3-2-1_104079_2022-04-05_final
2022-04-06 09:23:17	ga_ls7e_ard_3-2-1_104080_2022-04-05_final
2022-04-06 09:23:41	ga_ls7e_ard_3-2-1_104081_2022-04-05_final

Return to ga_ls7e_ard_3 whole collection 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

All years