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
2021-09-06 10:09:24	ga_ls7e_ard_3-2-0_108083_2021-09-06_final
2021-09-07 09:13:42	ga_ls7e_ard_3-2-0_099083_2021-09-06_final
2021-09-07 10:50:11	ga_ls7e_ard_3-2-0_115077_2021-09-07_final
2021-09-10 09:38:45	ga_ls7e_ard_3-2-0_104069_2021-09-10_final
2021-09-13 10:11:23	ga_ls7e_ard_3-2-0_109074_2021-09-13_final
2021-09-13 10:11:46	ga_ls7e_ard_3-2-0_109075_2021-09-13_final
2021-09-20 10:18:32	ga_ls7e_ard_3-2-0_110078_2021-09-20_final
2021-09-26 09:37:19	ga_ls7e_ard_3-2-0_104069_2021-09-26_final
2021-10-02 09:01:18	ga_ls7e_ard_3-2-0_098073_2021-10-01_final
2021-10-02 10:42:10	ga_ls7e_ard_3-2-0_114078_2021-10-02_final
2021-10-10 09:52:02	ga_ls7e_ard_3-2-0_106078_2021-10-10_final
2021-10-12 09:37:54	ga_ls7e_ard_3-2-0_104074_2021-10-12_final
2021-10-14 09:24:34	ga_ls7e_ard_3-2-0_102072_2021-10-13_final
2021-10-15 10:12:07	ga_ls7e_ard_3-2-0_109083_2021-10-15_final
2021-10-23 09:21:10	ga_ls7e_ard_3-2-0_101081_2021-10-22_final
2021-10-25 09:08:13	ga_ls7e_ard_3-2-0_099080_2021-10-24_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-27 08:53:17	ga_ls7e_ard_3-2-0_097074_2021-10-26_final
2021-10-27 10:34:10	ga_ls7e_ard_3-2-0_113079_2021-10-27_final
2021-10-30 09:22:19	ga_ls7e_ard_3-2-0_102070_2021-10-29_final
2021-10-30 09:23:54	ga_ls7e_ard_3-2-0_102074_2021-10-29_final
2021-11-03 10:39:41	ga_ls7e_ard_3-2-0_114079_2021-11-03_final
2021-11-04 09:44:22	ga_ls7e_ard_3-2-0_105080_2021-11-04_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-10 10:43:36	ga_ls7e_ard_3-2-0_115075_2021-11-10_final
2021-11-10 10:44:24	ga_ls7e_ard_3-2-0_115077_2021-11-10_final
2021-11-12 08:49:46	ga_ls7e_ard_3-2-0_097069_2021-11-11_final
2021-11-12 08:50:10	ga_ls7e_ard_3-2-0_097070_2021-11-11_final
2021-11-13 09:36:32	ga_ls7e_ard_3-2-1_104078_2021-11-13_final
2021-11-14 10:20:53	ga_ls7e_ard_3-2-1_111081_2021-11-14_final
2021-11-18 09:52:59	ga_ls7e_ard_3-2-1_107074_2021-11-18_final
2021-11-21 08:43:07	ga_ls7e_ard_3-2-1_096070_2021-11-20_final
2021-11-22 09:26:40	ga_ls7e_ard_3-2-1_103071_2021-11-21_final
2021-11-23 08:33:45	ga_ls7e_ard_3-2-1_094078_2021-11-22_final
2021-11-23 10:09:50	ga_ls7e_ard_3-2-1_110071_2021-11-23_final
2021-11-28 08:49:02	ga_ls7e_ard_3-2-1_097071_2021-11-27_final
2021-11-28 10:30:42	ga_ls7e_ard_3-2-1_113078_2021-11-28_final
2021-11-28 10:31:54	ga_ls7e_ard_3-2-1_113081_2021-11-28_final
2021-11-30 08:37:17	ga_ls7e_ard_3-2-1_095073_2021-11-29_final
2021-11-30 08:39:40	ga_ls7e_ard_3-2-1_095079_2021-11-29_final
2021-12-01 09:18:51	ga_ls7e_ard_3-2-1_102069_2021-11-30_final
2021-12-06 09:38:07	ga_ls7e_ard_3-2-1_105072_2021-12-06_final
2021-12-07 08:48:00	ga_ls7e_ard_3-2-1_096086_2021-12-06_final
2021-12-09 10:11:08	ga_ls7e_ard_3-2-1_110078_2021-12-09_final
2021-12-11 08:20:30	ga_ls7e_ard_3-2-1_092080_2021-12-10_final
2021-12-11 09:56:11	ga_ls7e_ard_3-2-1_108072_2021-12-11_final
2021-12-11 09:57:23	ga_ls7e_ard_3-2-1_108075_2021-12-11_final
2021-12-14 08:48:43	ga_ls7e_ard_3-2-1_097074_2021-12-13_final
2021-12-16 10:16:14	ga_ls7e_ard_3-2-1_111077_2021-12-16_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-22 09:39:22	ga_ls7e_ard_3-2-1_105079_2021-12-22_final
2021-12-23 10:24:08	ga_ls7e_ard_3-2-1_112083_2021-12-23_final
2021-12-24 09:27:37	ga_ls7e_ard_3-2-1_103081_2021-12-23_final
2021-12-25 10:07:11	ga_ls7e_ard_3-2-1_110072_2021-12-25_final
2021-12-26 09:12:40	ga_ls7e_ard_3-2-1_101075_2021-12-25_final
2021-12-27 09:56:13	ga_ls7e_ard_3-2-1_108076_2021-12-27_final
2021-12-29 09:41:40	ga_ls7e_ard_3-2-1_106071_2021-12-29_final
2021-12-29 09:43:15	ga_ls7e_ard_3-2-1_106075_2021-12-29_final
2022-01-08 08:40:04	ga_ls7e_ard_3-2-1_096074_2022-01-07_final
2022-01-13 08:59:44	ga_ls7e_ard_3-2-1_099078_2022-01-12_final
2022-01-15 08:43:36	ga_ls7e_ard_3-2-1_097069_2022-01-14_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-17 08:33:03	ga_ls7e_ard_3-2-1_095074_2022-01-16_final
2022-01-17 10:15:55	ga_ls7e_ard_3-2-1_111084_2022-01-17_final
2022-01-21 09:47:37	ga_ls7e_ard_3-2-1_107076_2022-01-21_final
2022-01-23 09:36:15	ga_ls7e_ard_3-2-1_105079_2022-01-23_final
2022-01-28 08:14:14	ga_ls7e_ard_3-2-1_092076_2022-01-27_final
2022-01-29 09:00:35	ga_ls7e_ard_3-2-1_099084_2022-01-28_final
2022-02-06 08:12:20	ga_ls7e_ard_3-2-1_091089_2022-02-05_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-08 09:34:39	ga_ls7e_ard_3-2-1_105079_2022-02-08_final
2022-02-10 09:22:53	ga_ls7e_ard_3-2-1_103081_2022-02-09_final
2022-02-11 10:06:50	ga_ls7e_ard_3-2-1_110083_2022-02-11_final
2022-02-14 08:55:45	ga_ls7e_ard_3-2-1_099076_2022-02-13_final
2022-02-15 09:40:06	ga_ls7e_ard_3-2-1_106079_2022-02-15_final
2022-02-20 09:54:35	ga_ls7e_ard_3-2-1_109070_2022-02-20_final
2022-02-23 08:47:31	ga_ls7e_ard_3-2-1_098073_2022-02-22_final
2022-02-23 08:48:19	ga_ls7e_ard_3-2-1_098075_2022-02-22_final
2022-02-25 08:35:46	ga_ls7e_ard_3-2-1_096075_2022-02-24_final
2022-03-02 10:32:42	ga_ls7e_ard_3-2-1_115075_2022-03-02_final
2022-03-10 08:08:23	ga_ls7e_ard_3-2-1_091087_2022-03-09_final
2022-03-10 08:08:47	ga_ls7e_ard_3-2-1_091088_2022-03-09_final
2022-03-11 08:44:21	ga_ls7e_ard_3-2-1_098069_2022-03-10_final
2022-03-11 08:48:44	ga_ls7e_ard_3-2-1_098080_2022-03-10_final
2022-03-12 09:28:18	ga_ls7e_ard_3-2-1_105071_2022-03-11_final
2022-03-18 08:51:01	ga_ls7e_ard_3-2-1_099072_2022-03-17_final
2022-03-18 08:51:25	ga_ls7e_ard_3-2-1_099073_2022-03-17_final
2022-03-20 10:20:56	ga_ls7e_ard_3-2-1_113081_2022-03-20_final
2022-03-23 09:09:29	ga_ls7e_ard_3-2-1_102073_2022-03-22_final
2022-03-24 08:18:34	ga_ls7e_ard_3-2-1_093085_2022-03-23_final
2022-03-25 08:56:32	ga_ls7e_ard_3-2-1_100072_2022-03-24_final
2022-03-27 08:44:00	ga_ls7e_ard_3-2-1_098072_2022-03-26_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-27 08:45:35	ga_ls7e_ard_3-2-1_098076_2022-03-26_final
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 10:14:43	ga_ls7e_ard_3-2-1_112083_2022-03-29_final
2022-04-01 09:04:27	ga_ls7e_ard_3-2-1_101078_2022-03-31_final
2022-04-02 08:07:56	ga_ls7e_ard_3-2-1_092076_2022-04-01_final
2022-04-03 08:49:30	ga_ls7e_ard_3-2-1_099072_2022-04-02_final
2022-04-05 08:40:08	ga_ls7e_ard_3-2-1_097080_2022-04-04_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