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
2021-09-20 08:38:27	ga_ls7e_ard_3-2-0_094075_2021-09-19_final
2021-09-25 08:56:56	ga_ls7e_ard_3-2-0_097076_2021-09-24_final
2021-09-25 08:57:44	ga_ls7e_ard_3-2-0_097078_2021-09-24_final
2021-09-29 08:31:04	ga_ls7e_ard_3-2-0_093074_2021-09-28_final
2021-10-02 09:01:42	ga_ls7e_ard_3-2-0_098074_2021-10-01_final
2021-10-03 09:43:17	ga_ls7e_ard_3-2-0_105070_2021-10-03_final
2021-10-06 10:17:54	ga_ls7e_ard_3-2-0_110080_2021-10-06_final
2021-10-07 09:20:36	ga_ls7e_ard_3-2-0_101076_2021-10-06_final
2021-10-08 10:04:34	ga_ls7e_ard_3-2-0_108078_2021-10-08_final
2021-10-10 08:15:09	ga_ls7e_ard_3-2-0_090083_2021-10-09_final
2021-10-11 08:57:31	ga_ls7e_ard_3-2-0_097081_2021-10-10_final
2021-10-11 10:34:24	ga_ls7e_ard_3-2-0_113076_2021-10-11_final
2021-10-12 09:39:06	ga_ls7e_ard_3-2-0_104077_2021-10-12_final
2021-10-12 09:40:42	ga_ls7e_ard_3-2-0_104081_2021-10-12_final
2021-10-20 08:50:32	ga_ls7e_ard_3-2-0_096081_2021-10-19_final
2021-10-20 10:27:25	ga_ls7e_ard_3-2-0_112076_2021-10-20_final
2021-10-20 10:28:37	ga_ls7e_ard_3-2-0_112079_2021-10-20_final
2021-10-21 09:31:43	ga_ls7e_ard_3-2-0_103076_2021-10-21_final
2021-10-22 08:37:12	ga_ls7e_ard_3-2-0_094079_2021-10-21_final
2021-10-23 09:20:46	ga_ls7e_ard_3-2-0_101080_2021-10-22_final
2021-10-24 08:24:15	ga_ls7e_ard_3-2-0_092078_2021-10-23_final
2021-10-26 09:50:12	ga_ls7e_ard_3-2-0_106077_2021-10-26_final
2021-10-28 09:35:39	ga_ls7e_ard_3-2-0_104072_2021-10-28_final
2021-10-28 09:37:15	ga_ls7e_ard_3-2-0_104076_2021-10-28_final
2021-10-30 09:23:07	ga_ls7e_ard_3-2-0_102072_2021-10-29_final
2021-11-05 08:47:28	ga_ls7e_ard_3-2-0_096077_2021-11-04_final
2021-11-05 08:49:27	ga_ls7e_ard_3-2-0_096082_2021-11-04_final
2021-11-09 10:00:50	ga_ls7e_ard_3-2-0_108076_2021-11-09_final
2021-11-10 10:45:12	ga_ls7e_ard_3-2-0_115079_2021-11-10_final
2021-11-13 09:36:56	ga_ls7e_ard_3-2-1_104079_2021-11-13_final
2021-11-14 08:41:37	ga_ls7e_ard_3-2-1_095080_2021-11-13_final
2021-11-14 10:19:41	ga_ls7e_ard_3-2-1_111078_2021-11-14_final
2021-11-16 08:29:27	ga_ls7e_ard_3-2-1_093081_2021-11-15_final
2021-11-16 10:07:08	ga_ls7e_ard_3-2-1_109078_2021-11-16_final
2021-11-21 08:47:54	ga_ls7e_ard_3-2-1_096082_2021-11-20_final
2021-11-22 09:26:40	ga_ls7e_ard_3-2-1_103071_2021-11-21_final
2021-11-28 10:30:42	ga_ls7e_ard_3-2-1_113078_2021-11-28_final
2021-11-29 09:36:11	ga_ls7e_ard_3-2-1_104081_2021-11-29_final
2021-12-02 08:29:07	ga_ls7e_ard_3-2-1_093084_2021-12-01_final
2021-12-06 09:38:31	ga_ls7e_ard_3-2-1_105073_2021-12-06_final
2021-12-07 08:43:36	ga_ls7e_ard_3-2-1_096075_2021-12-06_final
2021-12-09 08:32:39	ga_ls7e_ard_3-2-1_094079_2021-12-08_final
2021-12-09 10:11:08	ga_ls7e_ard_3-2-1_110078_2021-12-09_final
2021-12-09 10:11:32	ga_ls7e_ard_3-2-1_110079_2021-12-09_final
2021-12-12 09:02:04	ga_ls7e_ard_3-2-1_099076_2021-12-11_final
2021-12-14 08:49:55	ga_ls7e_ard_3-2-1_097077_2021-12-13_final
2021-12-16 08:36:58	ga_ls7e_ard_3-2-1_095076_2021-12-15_final
2021-12-16 10:16:14	ga_ls7e_ard_3-2-1_111077_2021-12-16_final
2021-12-16 10:17:02	ga_ls7e_ard_3-2-1_111079_2021-12-16_final
2021-12-18 10:00:54	ga_ls7e_ard_3-2-1_109070_2021-12-18_final
2021-12-18 10:01:41	ga_ls7e_ard_3-2-1_109072_2021-12-18_final
2021-12-19 09:07:10	ga_ls7e_ard_3-2-1_100075_2021-12-18_final
2021-12-23 10:21:20	ga_ls7e_ard_3-2-1_112076_2021-12-23_final
2021-12-25 08:32:18	ga_ls7e_ard_3-2-1_094082_2021-12-24_final
2022-01-06 08:52:13	ga_ls7e_ard_3-2-1_098073_2022-01-05_final
2022-01-09 09:22:50	ga_ls7e_ard_3-2-1_103073_2022-01-08_final
2022-01-11 09:11:29	ga_ls7e_ard_3-2-1_101076_2022-01-10_final
2022-01-13 08:58:08	ga_ls7e_ard_3-2-1_099074_2022-01-12_final
2022-01-13 08:58:32	ga_ls7e_ard_3-2-1_099075_2022-01-12_final
2022-01-13 10:37:01	ga_ls7e_ard_3-2-1_115074_2022-01-13_final
2022-01-15 10:26:28	ga_ls7e_ard_3-2-1_113079_2022-01-15_final
2022-01-17 10:13:55	ga_ls7e_ard_3-2-1_111079_2022-01-17_final
2022-01-21 09:49:37	ga_ls7e_ard_3-2-1_107081_2022-01-21_final
2022-01-21 09:50:01	ga_ls7e_ard_3-2-1_107082_2022-01-21_final
2022-01-24 08:40:09	ga_ls7e_ard_3-2-1_096078_2022-01-23_final
2022-01-24 10:17:49	ga_ls7e_ard_3-2-1_112075_2022-01-24_final
2022-01-24 10:18:37	ga_ls7e_ard_3-2-1_112077_2022-01-24_final
2022-01-26 10:06:28	ga_ls7e_ard_3-2-1_110078_2022-01-26_final
2022-01-27 09:09:57	ga_ls7e_ard_3-2-1_101076_2022-01-26_final
2022-01-29 10:36:40	ga_ls7e_ard_3-2-1_115077_2022-01-29_final
2022-02-02 08:36:40	ga_ls7e_ard_3-2-1_095087_2022-02-01_final
2022-02-02 10:11:09	ga_ls7e_ard_3-2-1_111076_2022-02-02_final
2022-02-02 10:12:45	ga_ls7e_ard_3-2-1_111080_2022-02-02_final
2022-02-04 08:20:07	ga_ls7e_ard_3-2-1_093077_2022-02-03_final
2022-02-04 08:22:30	ga_ls7e_ard_3-2-1_093083_2022-02-03_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-08 09:34:15	ga_ls7e_ard_3-2-1_105078_2022-02-08_final
2022-02-09 08:38:32	ga_ls7e_ard_3-2-1_096078_2022-02-08_final
2022-02-09 10:18:13	ga_ls7e_ard_3-2-1_112080_2022-02-09_final
2022-02-10 09:19:42	ga_ls7e_ard_3-2-1_103073_2022-02-09_final
2022-02-14 08:54:33	ga_ls7e_ard_3-2-1_099073_2022-02-13_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-17 09:24:21	ga_ls7e_ard_3-2-1_104071_2022-02-16_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-18 08:31:50	ga_ls7e_ard_3-2-1_095079_2022-02-17_final
2022-02-20 08:19:41	ga_ls7e_ard_3-2-1_093080_2022-02-19_final
2022-02-20 08:20:05	ga_ls7e_ard_3-2-1_093081_2022-02-19_final
2022-02-25 08:34:58	ga_ls7e_ard_3-2-1_096073_2022-02-24_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-04 08:42:51	ga_ls7e_ard_3-2-1_097079_2022-03-03_final
2022-03-05 09:24:01	ga_ls7e_ard_3-2-1_104074_2022-03-04_final
2022-03-06 10:07:59	ga_ls7e_ard_3-2-1_111076_2022-03-06_final
2022-03-06 10:08:47	ga_ls7e_ard_3-2-1_111078_2022-03-06_final
2022-03-07 09:10:40	ga_ls7e_ard_3-2-1_102072_2022-03-06_final
2022-03-08 09:56:37	ga_ls7e_ard_3-2-1_109079_2022-03-08_final
2022-03-17 08:11:27	ga_ls7e_ard_3-2-1_092081_2022-03-16_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-29 08:34:38	ga_ls7e_ard_3-2-1_096080_2022-03-28_final
2022-04-03 08:49:54	ga_ls7e_ard_3-2-1_099073_2022-04-02_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