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
2021-09-11 10:21:07	ga_ls7e_ard_3-2-0_111067_2021-09-11_final
2021-09-12 09:29:24	ga_ls7e_ard_3-2-0_102077_2021-09-11_final
2021-09-13 08:36:29	ga_ls7e_ard_3-2-0_093084_2021-09-12_final
2021-09-13 10:12:34	ga_ls7e_ard_3-2-0_109077_2021-09-13_final
2021-09-24 08:14:34	ga_ls7e_ard_3-2-0_090078_2021-09-23_final
2021-09-29 10:08:20	ga_ls7e_ard_3-2-0_109070_2021-09-29_final
2021-10-01 09:57:00	ga_ls7e_ard_3-2-0_107073_2021-10-01_final
2021-10-03 08:09:35	ga_ls7e_ard_3-2-0_089083_2021-10-02_final
2021-10-08 10:06:10	ga_ls7e_ard_3-2-0_108082_2021-10-08_final
2021-10-10 09:51:38	ga_ls7e_ard_3-2-0_106077_2021-10-10_final
2021-10-13 08:47:23	ga_ls7e_ard_3-2-0_095087_2021-10-12_final
2021-10-13 10:23:52	ga_ls7e_ard_3-2-0_111081_2021-10-13_final
2021-10-15 08:29:39	ga_ls7e_ard_3-2-0_093074_2021-10-14_final
2021-10-15 10:07:20	ga_ls7e_ard_3-2-0_109071_2021-10-15_final
2021-10-15 10:07:44	ga_ls7e_ard_3-2-0_109072_2021-10-15_final
2021-10-16 09:12:26	ga_ls7e_ard_3-2-0_100073_2021-10-15_final
2021-10-16 09:13:37	ga_ls7e_ard_3-2-0_100076_2021-10-15_final
2021-10-17 09:58:23	ga_ls7e_ard_3-2-0_107080_2021-10-17_final
2021-10-18 10:41:10	ga_ls7e_ard_3-2-0_114079_2021-10-18_final
2021-10-20 08:47:45	ga_ls7e_ard_3-2-0_096074_2021-10-19_final
2021-10-21 09:29:19	ga_ls7e_ard_3-2-0_103070_2021-10-20_final
2021-10-22 10:17:16	ga_ls7e_ard_3-2-0_110082_2021-10-22_final
2021-10-23 09:19:58	ga_ls7e_ard_3-2-0_101078_2021-10-22_final
2021-10-24 08:25:51	ga_ls7e_ard_3-2-0_092082_2021-10-23_final
2021-10-26 08:13:19	ga_ls7e_ard_3-2-0_090082_2021-10-25_final
2021-10-31 08:32:11	ga_ls7e_ard_3-2-0_093084_2021-10-30_final
2021-11-03 09:01:36	ga_ls7e_ard_3-2-0_098081_2021-11-02_final
2021-11-05 08:45:52	ga_ls7e_ard_3-2-0_096073_2021-11-04_final
2021-11-05 08:49:03	ga_ls7e_ard_3-2-0_096081_2021-11-04_final
2021-11-06 09:30:14	ga_ls7e_ard_3-2-0_103076_2021-11-06_final
2021-11-07 08:37:42	ga_ls7e_ard_3-2-0_094084_2021-11-06_final
2021-11-09 09:58:03	ga_ls7e_ard_3-2-0_108069_2021-11-09_final
2021-11-14 10:21:17	ga_ls7e_ard_3-2-1_111082_2021-11-14_final
2021-11-16 08:30:15	ga_ls7e_ard_3-2-1_093083_2021-11-15_final
2021-11-18 08:16:54	ga_ls7e_ard_3-2-1_091081_2021-11-17_final
2021-11-18 09:52:11	ga_ls7e_ard_3-2-1_107072_2021-11-18_final
2021-11-18 09:52:35	ga_ls7e_ard_3-2-1_107073_2021-11-18_final
2021-11-21 08:48:18	ga_ls7e_ard_3-2-1_096083_2021-11-20_final
2021-11-24 09:16:06	ga_ls7e_ard_3-2-1_101076_2021-11-23_final
2021-11-25 10:00:28	ga_ls7e_ard_3-2-1_108079_2021-11-25_final
2021-11-30 10:20:09	ga_ls7e_ard_3-2-1_111083_2021-11-30_final
2021-12-05 08:58:33	ga_ls7e_ard_3-2-1_098081_2021-12-04_final
2021-12-07 10:24:28	ga_ls7e_ard_3-2-1_112080_2021-12-07_final
2021-12-08 09:27:58	ga_ls7e_ard_3-2-1_103078_2021-12-07_final
2021-12-09 08:31:51	ga_ls7e_ard_3-2-1_094077_2021-12-08_final
2021-12-11 08:21:18	ga_ls7e_ard_3-2-1_092082_2021-12-10_final
2021-12-13 09:46:49	ga_ls7e_ard_3-2-1_106080_2021-12-13_final
2021-12-16 08:39:45	ga_ls7e_ard_3-2-1_095083_2021-12-15_final
2021-12-17 09:20:31	ga_ls7e_ard_3-2-1_102077_2021-12-16_final
2021-12-18 08:26:48	ga_ls7e_ard_3-2-1_093082_2021-12-17_final
2021-12-21 08:57:25	ga_ls7e_ard_3-2-1_098082_2021-12-20_final
2021-12-25 10:10:22	ga_ls7e_ard_3-2-1_110080_2021-12-25_final
2021-12-30 08:47:08	ga_ls7e_ard_3-2-1_097074_2021-12-29_final
2021-12-31 09:29:06	ga_ls7e_ard_3-2-1_104071_2021-12-30_final
2022-01-01 08:37:22	ga_ls7e_ard_3-2-1_095081_2021-12-31_final
2022-01-02 09:17:44	ga_ls7e_ard_3-2-1_102074_2022-01-01_final
2022-01-04 09:07:33	ga_ls7e_ard_3-2-1_100080_2022-01-03_final
2022-01-05 09:50:19	ga_ls7e_ard_3-2-1_107079_2022-01-05_final
2022-01-06 10:33:05	ga_ls7e_ard_3-2-1_114078_2022-01-06_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-10 08:32:19	ga_ls7e_ard_3-2-1_094086_2022-01-09_final
2022-01-12 08:17:22	ga_ls7e_ard_3-2-1_092080_2022-01-11_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-17 08:33:27	ga_ls7e_ard_3-2-1_095075_2022-01-16_final
2022-01-17 10:14:19	ga_ls7e_ard_3-2-1_111080_2022-01-17_final
2022-01-20 09:06:27	ga_ls7e_ard_3-2-1_100081_2022-01-19_final
2022-01-21 09:46:25	ga_ls7e_ard_3-2-1_107073_2022-01-21_final
2022-01-22 08:51:54	ga_ls7e_ard_3-2-1_098076_2022-01-21_final
2022-01-22 10:31:35	ga_ls7e_ard_3-2-1_114078_2022-01-22_final
2022-01-23 09:35:52	ga_ls7e_ard_3-2-1_105078_2022-01-23_final
2022-01-23 09:36:15	ga_ls7e_ard_3-2-1_105079_2022-01-23_final
2022-01-31 10:26:06	ga_ls7e_ard_3-2-1_113082_2022-01-31_final
2022-02-03 09:16:38	ga_ls7e_ard_3-2-1_102079_2022-02-02_final
2022-02-09 08:39:44	ga_ls7e_ard_3-2-1_096081_2022-02-08_final
2022-02-14 08:57:45	ga_ls7e_ard_3-2-1_099081_2022-02-13_final
2022-02-15 08:02:01	ga_ls7e_ard_3-2-1_090081_2022-02-14_final
2022-02-16 10:24:27	ga_ls7e_ard_3-2-1_113082_2022-02-16_final
2022-02-19 09:13:48	ga_ls7e_ard_3-2-1_102076_2022-02-18_final
2022-02-20 08:17:18	ga_ls7e_ard_3-2-1_093074_2022-02-19_final
2022-02-20 09:58:58	ga_ls7e_ard_3-2-1_109081_2022-02-20_final
2022-02-21 09:00:51	ga_ls7e_ard_3-2-1_100075_2022-02-20_final
2022-02-21 09:02:51	ga_ls7e_ard_3-2-1_100080_2022-02-20_final
2022-02-22 08:06:44	ga_ls7e_ard_3-2-1_091079_2022-02-21_final
2022-02-25 08:35:22	ga_ls7e_ard_3-2-1_096074_2022-02-24_final
2022-03-01 08:11:51	ga_ls7e_ard_3-2-1_092078_2022-02-28_final
2022-03-01 09:51:56	ga_ls7e_ard_3-2-1_108081_2022-03-01_final
2022-03-02 08:53:01	ga_ls7e_ard_3-2-1_099073_2022-03-01_final
2022-03-02 08:54:13	ga_ls7e_ard_3-2-1_099076_2022-03-01_final
2022-03-03 07:59:42	ga_ls7e_ard_3-2-1_090079_2022-03-02_final
2022-03-08 08:19:20	ga_ls7e_ard_3-2-1_093083_2022-03-07_final
2022-03-11 08:45:57	ga_ls7e_ard_3-2-1_098073_2022-03-10_final
2022-03-12 09:29:06	ga_ls7e_ard_3-2-1_105073_2022-03-11_final
2022-03-12 09:32:18	ga_ls7e_ard_3-2-1_105081_2022-03-12_final
2022-03-19 09:34:59	ga_ls7e_ard_3-2-1_106074_2022-03-19_final
2022-03-20 08:38:28	ga_ls7e_ard_3-2-1_097072_2022-03-19_final
2022-03-24 08:14:10	ga_ls7e_ard_3-2-1_093074_2022-03-23_final
2022-03-27 10:25:16	ga_ls7e_ard_3-2-1_114078_2022-03-27_final
2022-03-31 10:01:22	ga_ls7e_ard_3-2-1_110081_2022-03-31_final
2022-04-05 08:40:31	ga_ls7e_ard_3-2-1_097081_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years