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
2020-04-30 10:30:01	ga_ls7e_ard_3-1-0_106075_2020-04-30_final
2020-04-30 10:30:49	ga_ls7e_ard_3-1-0_106077_2020-04-30_final
2020-05-01 09:33:08	ga_ls7e_ard_3-1-0_097072_2020-05-01_final
2020-05-01 09:34:44	ga_ls7e_ard_3-1-0_097076_2020-05-01_final
2020-05-01 09:35:08	ga_ls7e_ard_3-1-0_097077_2020-05-01_final
2020-05-01 09:37:56	ga_ls7e_ard_3-1-0_097084_2020-05-01_final
2020-05-01 11:16:00	ga_ls7e_ard_3-1-0_113082_2020-05-01_final
2020-05-01 11:16:24	ga_ls7e_ard_3-1-0_113083_2020-05-01_final
2020-05-02 10:15:08	ga_ls7e_ard_3-1-0_104069_2020-05-02_final
2020-05-02 10:17:08	ga_ls7e_ard_3-1-0_104074_2020-05-02_final
2020-05-02 10:18:44	ga_ls7e_ard_3-1-0_104078_2020-05-02_final
2020-05-03 09:21:03	ga_ls7e_ard_3-1-0_095073_2020-05-02_final
2020-05-03 09:21:51	ga_ls7e_ard_3-1-0_095075_2020-05-02_final
2020-05-03 09:22:39	ga_ls7e_ard_3-1-0_095077_2020-05-02_final
2020-05-03 09:24:15	ga_ls7e_ard_3-1-0_095081_2020-05-02_final
2020-05-03 09:25:03	ga_ls7e_ard_3-1-0_095083_2020-05-02_final
2020-05-03 09:25:27	ga_ls7e_ard_3-1-0_095084_2020-05-02_final
2020-05-03 10:57:33	ga_ls7e_ard_3-1-0_111067_2020-05-03_final
2020-05-03 11:00:20	ga_ls7e_ard_3-1-0_111074_2020-05-03_final
2020-05-03 11:01:08	ga_ls7e_ard_3-1-0_111076_2020-05-03_final
2020-05-03 11:03:08	ga_ls7e_ard_3-1-0_111081_2020-05-03_final
2020-05-03 11:03:32	ga_ls7e_ard_3-1-0_111082_2020-05-03_final
2020-05-04 10:03:27	ga_ls7e_ard_3-1-0_102071_2020-05-04_final
2020-05-04 10:04:15	ga_ls7e_ard_3-1-0_102073_2020-05-04_final
2020-05-04 10:04:39	ga_ls7e_ard_3-1-0_102074_2020-05-04_final
2020-05-04 10:05:27	ga_ls7e_ard_3-1-0_102076_2020-05-04_final
2020-05-04 10:06:15	ga_ls7e_ard_3-1-0_102078_2020-05-04_final
2020-05-05 10:46:15	ga_ls7e_ard_3-1-0_109070_2020-05-05_final
2020-05-05 10:46:39	ga_ls7e_ard_3-1-0_109071_2020-05-05_final
2020-05-05 10:47:03	ga_ls7e_ard_3-1-0_109072_2020-05-05_final
2020-05-05 10:47:27	ga_ls7e_ard_3-1-0_109073_2020-05-05_final
2020-05-05 10:48:39	ga_ls7e_ard_3-1-0_109076_2020-05-05_final
2020-05-05 10:49:51	ga_ls7e_ard_3-1-0_109079_2020-05-05_final
2020-05-05 10:50:39	ga_ls7e_ard_3-1-0_109081_2020-05-05_final
2020-05-06 09:51:46	ga_ls7e_ard_3-1-0_100073_2020-05-06_final
2020-05-06 09:53:46	ga_ls7e_ard_3-1-0_100078_2020-05-06_final
2020-05-07 10:33:47	ga_ls7e_ard_3-1-0_107070_2020-05-07_final
2020-05-07 10:37:22	ga_ls7e_ard_3-1-0_107079_2020-05-07_final
2020-05-08 09:36:54	ga_ls7e_ard_3-1-0_098067_2020-05-08_final
2020-05-08 09:38:54	ga_ls7e_ard_3-1-0_098072_2020-05-08_final
2020-05-08 09:39:41	ga_ls7e_ard_3-1-0_098074_2020-05-08_final
2020-05-08 09:40:29	ga_ls7e_ard_3-1-0_098076_2020-05-08_final
2020-05-08 09:42:53	ga_ls7e_ard_3-1-0_098082_2020-05-08_final
2020-05-08 11:15:47	ga_ls7e_ard_3-1-0_114067_2020-05-08_final
2020-05-08 11:19:46	ga_ls7e_ard_3-1-0_114077_2020-05-08_final
2020-05-09 10:20:30	ga_ls7e_ard_3-1-0_105068_2020-05-09_final
2020-05-09 10:21:18	ga_ls7e_ard_3-1-0_105070_2020-05-09_final
2020-05-09 10:21:42	ga_ls7e_ard_3-1-0_105071_2020-05-09_final
2020-05-09 10:22:05	ga_ls7e_ard_3-1-0_105072_2020-05-09_final
2020-05-09 10:23:17	ga_ls7e_ard_3-1-0_105075_2020-05-09_final
2020-05-09 10:24:05	ga_ls7e_ard_3-1-0_105077_2020-05-09_final
2020-05-10 09:24:25	ga_ls7e_ard_3-1-0_096067_2020-05-09_final
2020-05-10 09:26:01	ga_ls7e_ard_3-1-0_096071_2020-05-09_final
2020-05-10 09:32:00	ga_ls7e_ard_3-1-0_096086_2020-05-10_final
2020-05-10 11:08:29	ga_ls7e_ard_3-1-0_112080_2020-05-10_final
2020-05-10 11:10:05	ga_ls7e_ard_3-1-0_112084_2020-05-10_final
2020-05-11 10:08:01	ga_ls7e_ard_3-1-0_103068_2020-05-11_final
2020-05-11 10:08:49	ga_ls7e_ard_3-1-0_103070_2020-05-11_final
2020-05-11 10:09:37	ga_ls7e_ard_3-1-0_103072_2020-05-11_final
2020-05-11 10:10:48	ga_ls7e_ard_3-1-0_103075_2020-05-11_final
2020-05-11 10:12:00	ga_ls7e_ard_3-1-0_103078_2020-05-11_final
2020-05-11 10:12:48	ga_ls7e_ard_3-1-0_103080_2020-05-11_final
2020-05-11 10:13:12	ga_ls7e_ard_3-1-0_103081_2020-05-11_final
2020-05-11 10:13:36	ga_ls7e_ard_3-1-0_103082_2020-05-11_final
2020-05-12 10:50:49	ga_ls7e_ard_3-1-0_110067_2020-05-12_final
2020-05-12 10:52:25	ga_ls7e_ard_3-1-0_110071_2020-05-12_final
2020-05-12 10:55:36	ga_ls7e_ard_3-1-0_110079_2020-05-12_final
2020-05-13 09:57:08	ga_ls7e_ard_3-1-0_101072_2020-05-13_final
2020-05-13 09:57:32	ga_ls7e_ard_3-1-0_101073_2020-05-13_final
2020-05-13 09:58:43	ga_ls7e_ard_3-1-0_101076_2020-05-13_final
2020-05-13 09:59:07	ga_ls7e_ard_3-1-0_101077_2020-05-13_final
2020-05-13 10:00:19	ga_ls7e_ard_3-1-0_101080_2020-05-13_final
2020-05-13 10:00:43	ga_ls7e_ard_3-1-0_101081_2020-05-13_final
2020-05-13 10:01:07	ga_ls7e_ard_3-1-0_101082_2020-05-13_final
2020-05-14 10:41:07	ga_ls7e_ard_3-1-0_108074_2020-05-14_final
2020-05-15 09:43:03	ga_ls7e_ard_3-1-0_099068_2020-05-15_final
2020-05-15 09:43:51	ga_ls7e_ard_3-1-0_099070_2020-05-15_final
2020-05-15 09:44:39	ga_ls7e_ard_3-1-0_099072_2020-05-15_final
2020-05-15 09:45:03	ga_ls7e_ard_3-1-0_099073_2020-05-15_final
2020-05-15 09:47:26	ga_ls7e_ard_3-1-0_099079_2020-05-15_final
2020-05-15 09:48:14	ga_ls7e_ard_3-1-0_099081_2020-05-15_final
2020-05-15 09:49:02	ga_ls7e_ard_3-1-0_099083_2020-05-15_final
2020-05-15 11:25:55	ga_ls7e_ard_3-1-0_115078_2020-05-15_final
2020-05-15 11:26:19	ga_ls7e_ard_3-1-0_115079_2020-05-15_final
2020-05-16 10:27:03	ga_ls7e_ard_3-1-0_106070_2020-05-16_final
2020-05-16 10:27:50	ga_ls7e_ard_3-1-0_106072_2020-05-16_final
2020-05-16 10:29:50	ga_ls7e_ard_3-1-0_106077_2020-05-16_final
2020-05-16 10:30:38	ga_ls7e_ard_3-1-0_106079_2020-05-16_final
2020-05-16 10:31:26	ga_ls7e_ard_3-1-0_106081_2020-05-16_final
2020-05-17 09:32:10	ga_ls7e_ard_3-1-0_097072_2020-05-17_final
2020-05-17 09:36:57	ga_ls7e_ard_3-1-0_097084_2020-05-17_final
2020-05-18 10:17:45	ga_ls7e_ard_3-1-0_104078_2020-05-18_final
2020-05-18 10:18:57	ga_ls7e_ard_3-1-0_104081_2020-05-18_final
2020-05-19 09:23:16	ga_ls7e_ard_3-1-0_095081_2020-05-18_final
2020-05-19 09:24:04	ga_ls7e_ard_3-1-0_095083_2020-05-18_final
2020-05-19 09:24:28	ga_ls7e_ard_3-1-0_095084_2020-05-18_final
2020-05-19 10:56:34	ga_ls7e_ard_3-1-0_111067_2020-05-19_final
2020-05-19 11:00:57	ga_ls7e_ard_3-1-0_111078_2020-05-19_final
2020-05-19 11:02:09	ga_ls7e_ard_3-1-0_111081_2020-05-19_final
2020-05-19 11:02:33	ga_ls7e_ard_3-1-0_111082_2020-05-19_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years