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
2021-09-08 09:54:28	ga_ls7e_ard_3-2-0_106077_2021-09-08_final
2021-09-09 10:38:03	ga_ls7e_ard_3-2-0_113078_2021-09-09_final
2021-09-10 09:38:45	ga_ls7e_ard_3-2-0_104069_2021-09-10_final
2021-09-25 10:35:49	ga_ls7e_ard_3-2-0_113076_2021-09-25_final
2021-09-26 09:40:30	ga_ls7e_ard_3-2-0_104077_2021-09-26_final
2021-09-28 09:29:10	ga_ls7e_ard_3-2-0_102080_2021-09-27_final
2021-09-29 10:11:56	ga_ls7e_ard_3-2-0_109079_2021-09-29_final
2021-10-08 10:03:46	ga_ls7e_ard_3-2-0_108076_2021-10-08_final
2021-10-14 09:26:34	ga_ls7e_ard_3-2-0_102077_2021-10-13_final
2021-10-15 10:10:32	ga_ls7e_ard_3-2-0_109079_2021-10-15_final
2021-10-15 10:10:56	ga_ls7e_ard_3-2-0_109080_2021-10-15_final
2021-10-20 08:47:21	ga_ls7e_ard_3-2-0_096073_2021-10-19_final
2021-10-20 08:51:20	ga_ls7e_ard_3-2-0_096083_2021-10-19_final
2021-10-21 09:30:55	ga_ls7e_ard_3-2-0_103074_2021-10-21_final
2021-10-21 09:31:43	ga_ls7e_ard_3-2-0_103076_2021-10-21_final
2021-10-21 09:32:31	ga_ls7e_ard_3-2-0_103078_2021-10-21_final
2021-10-23 09:20:22	ga_ls7e_ard_3-2-0_101079_2021-10-22_final
2021-10-30 09:24:18	ga_ls7e_ard_3-2-0_102075_2021-10-29_final
2021-10-31 10:09:04	ga_ls7e_ard_3-2-0_109079_2021-10-31_final
2021-11-04 09:43:58	ga_ls7e_ard_3-2-0_105079_2021-11-04_final
2021-11-05 08:47:04	ga_ls7e_ard_3-2-0_096076_2021-11-04_final
2021-11-07 08:35:43	ga_ls7e_ard_3-2-0_094079_2021-11-06_final
2021-11-13 09:36:56	ga_ls7e_ard_3-2-1_104079_2021-11-13_final
2021-11-14 08:40:01	ga_ls7e_ard_3-2-1_095076_2021-11-13_final
2021-11-14 10:19:17	ga_ls7e_ard_3-2-1_111077_2021-11-14_final
2021-11-21 08:45:06	ga_ls7e_ard_3-2-1_096075_2021-11-20_final
2021-11-22 09:27:52	ga_ls7e_ard_3-2-1_103074_2021-11-21_final
2021-11-26 09:02:46	ga_ls7e_ard_3-2-1_099074_2021-11-25_final
2021-11-27 09:48:44	ga_ls7e_ard_3-2-1_106081_2021-11-27_final
2021-11-30 08:39:40	ga_ls7e_ard_3-2-1_095079_2021-11-29_final
2021-11-30 08:40:04	ga_ls7e_ard_3-2-1_095080_2021-11-29_final
2021-12-05 08:58:57	ga_ls7e_ard_3-2-1_098082_2021-12-04_final
2021-12-08 09:26:46	ga_ls7e_ard_3-2-1_103075_2021-12-07_final
2021-12-08 09:29:34	ga_ls7e_ard_3-2-1_103082_2021-12-07_final
2021-12-10 09:15:49	ga_ls7e_ard_3-2-1_101079_2021-12-09_final
2021-12-10 09:16:37	ga_ls7e_ard_3-2-1_101081_2021-12-09_final
2021-12-16 10:18:14	ga_ls7e_ard_3-2-1_111082_2021-12-16_final
2021-12-25 08:30:18	ga_ls7e_ard_3-2-1_094077_2021-12-24_final
2021-12-25 08:30:42	ga_ls7e_ard_3-2-1_094078_2021-12-24_final
2021-12-30 08:48:20	ga_ls7e_ard_3-2-1_097077_2021-12-29_final
2021-12-30 10:28:01	ga_ls7e_ard_3-2-1_113079_2021-12-30_final
2022-01-01 08:36:34	ga_ls7e_ard_3-2-1_095079_2021-12-31_final
2022-01-01 10:15:27	ga_ls7e_ard_3-2-1_111079_2022-01-01_final
2022-01-08 08:40:28	ga_ls7e_ard_3-2-1_096075_2022-01-07_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-10 08:28:19	ga_ls7e_ard_3-2-1_094076_2022-01-09_final
2022-01-15 10:25:40	ga_ls7e_ard_3-2-1_113077_2022-01-15_final
2022-01-15 10:26:28	ga_ls7e_ard_3-2-1_113079_2022-01-15_final
2022-01-17 10:13:07	ga_ls7e_ard_3-2-1_111077_2022-01-17_final
2022-01-19 10:01:46	ga_ls7e_ard_3-2-1_109080_2022-01-19_final
2022-01-21 09:48:49	ga_ls7e_ard_3-2-1_107079_2022-01-21_final
2022-01-26 10:06:28	ga_ls7e_ard_3-2-1_110078_2022-01-26_final
2022-01-28 08:16:38	ga_ls7e_ard_3-2-1_092082_2022-01-27_final
2022-01-28 09:53:55	ga_ls7e_ard_3-2-1_108078_2022-01-28_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-02-02 10:11:09	ga_ls7e_ard_3-2-1_111076_2022-02-02_final
2022-02-03 09:17:02	ga_ls7e_ard_3-2-1_102080_2022-02-02_final
2022-02-04 08:20:55	ga_ls7e_ard_3-2-1_093079_2022-02-03_final
2022-02-06 09:47:13	ga_ls7e_ard_3-2-1_107079_2022-02-06_final
2022-02-06 09:48:25	ga_ls7e_ard_3-2-1_107082_2022-02-06_final
2022-02-07 08:49:54	ga_ls7e_ard_3-2-1_098075_2022-02-06_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-09 08:38:32	ga_ls7e_ard_3-2-1_096078_2022-02-08_final
2022-02-10 09:22:05	ga_ls7e_ard_3-2-1_103079_2022-02-09_final
2022-02-11 08:25:58	ga_ls7e_ard_3-2-1_094078_2022-02-10_final
2022-02-18 08:32:38	ga_ls7e_ard_3-2-1_095081_2022-02-17_final
2022-02-22 09:46:49	ga_ls7e_ard_3-2-1_107082_2022-02-22_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-25 08:36:09	ga_ls7e_ard_3-2-1_096076_2022-02-24_final
2022-02-26 09:16:56	ga_ls7e_ard_3-2-1_103070_2022-02-25_final
2022-02-26 09:19:19	ga_ls7e_ard_3-2-1_103076_2022-02-25_final
2022-02-27 08:24:00	ga_ls7e_ard_3-2-1_094077_2022-02-26_final
2022-02-28 09:08:22	ga_ls7e_ard_3-2-1_101080_2022-02-27_final
2022-03-03 07:59:42	ga_ls7e_ard_3-2-1_090079_2022-03-02_final
2022-03-04 10:21:20	ga_ls7e_ard_3-2-1_113078_2022-03-04_final
2022-03-05 09:22:26	ga_ls7e_ard_3-2-1_104070_2022-03-04_final
2022-03-06 08:31:06	ga_ls7e_ard_3-2-1_095081_2022-03-05_final
2022-03-06 10:04:47	ga_ls7e_ard_3-2-1_111068_2022-03-06_final
2022-03-06 10:09:11	ga_ls7e_ard_3-2-1_111079_2022-03-06_final
2022-03-07 09:13:04	ga_ls7e_ard_3-2-1_102078_2022-03-06_final
2022-03-07 09:13:52	ga_ls7e_ard_3-2-1_102080_2022-03-06_final
2022-03-09 09:01:18	ga_ls7e_ard_3-2-1_100080_2022-03-08_final
2022-03-12 09:31:06	ga_ls7e_ard_3-2-1_105078_2022-03-12_final
2022-03-14 09:17:20	ga_ls7e_ard_3-2-1_103075_2022-03-13_final
2022-03-15 08:22:49	ga_ls7e_ard_3-2-1_094078_2022-03-14_final
2022-03-17 08:10:39	ga_ls7e_ard_3-2-1_092079_2022-03-16_final
2022-03-18 08:52:12	ga_ls7e_ard_3-2-1_099075_2022-03-17_final
2022-03-22 08:29:07	ga_ls7e_ard_3-2-1_095080_2022-03-21_final
2022-03-27 08:47:59	ga_ls7e_ard_3-2-1_098082_2022-03-26_final
2022-03-28 09:26:46	ga_ls7e_ard_3-2-1_105071_2022-03-27_final
2022-03-29 10:11:55	ga_ls7e_ard_3-2-1_112076_2022-03-29_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-03-30 09:15:48	ga_ls7e_ard_3-2-1_103075_2022-03-29_final
2022-04-04 09:35:03	ga_ls7e_ard_3-2-1_106078_2022-04-04_final
2022-04-05 08:38:08	ga_ls7e_ard_3-2-1_097075_2022-04-04_final
2022-04-05 08:38:32	ga_ls7e_ard_3-2-1_097076_2022-04-04_final
2022-04-05 10:18:12	ga_ls7e_ard_3-2-1_113078_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 09:22:29	ga_ls7e_ard_3-2-1_104078_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