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
2020-10-06 09:37:17	ga_ls7e_ard_3-2-0_099076_2020-10-06_final
2021-08-26 08:47:14	ga_ls7e_ard_3-2-0_095076_2021-08-25_final
2021-08-28 10:11:59	ga_ls7e_ard_3-2-0_109072_2021-08-28_final
2021-09-06 08:31:19	ga_ls7e_ard_3-2-0_092085_2021-09-05_final
2021-09-08 09:51:17	ga_ls7e_ard_3-2-0_106069_2021-09-08_final
2021-09-11 10:23:55	ga_ls7e_ard_3-2-0_111074_2021-09-11_final
2021-09-15 08:21:09	ga_ls7e_ard_3-2-0_091077_2021-09-14_final
2021-09-18 08:49:24	ga_ls7e_ard_3-2-0_096071_2021-09-17_final
2021-09-20 10:18:32	ga_ls7e_ard_3-2-0_110078_2021-09-20_final
2021-09-24 09:49:27	ga_ls7e_ard_3-2-0_106068_2021-09-24_final
2021-09-25 08:55:45	ga_ls7e_ard_3-2-0_097073_2021-09-24_final
2021-09-25 08:57:20	ga_ls7e_ard_3-2-0_097077_2021-09-24_final
2021-10-02 10:42:34	ga_ls7e_ard_3-2-0_114079_2021-10-02_final
2021-10-04 08:51:34	ga_ls7e_ard_3-2-0_096080_2021-10-03_final
2021-10-04 10:30:50	ga_ls7e_ard_3-2-0_112081_2021-10-04_final
2021-10-07 09:21:00	ga_ls7e_ard_3-2-0_101077_2021-10-06_final
2021-10-12 09:38:18	ga_ls7e_ard_3-2-0_104075_2021-10-12_final
2021-10-15 10:07:44	ga_ls7e_ard_3-2-0_109072_2021-10-15_final
2021-10-23 09:18:22	ga_ls7e_ard_3-2-0_101074_2021-10-22_final
2021-10-23 09:20:22	ga_ls7e_ard_3-2-0_101079_2021-10-22_final
2021-10-24 10:05:32	ga_ls7e_ard_3-2-0_108084_2021-10-24_final
2021-10-25 09:09:25	ga_ls7e_ard_3-2-0_099083_2021-10-24_final
2021-10-28 09:38:27	ga_ls7e_ard_3-2-0_104079_2021-10-28_final
2021-10-30 09:26:18	ga_ls7e_ard_3-2-0_102080_2021-10-29_final
2021-11-04 09:39:59	ga_ls7e_ard_3-2-0_105069_2021-11-04_final
2021-11-05 10:25:56	ga_ls7e_ard_3-2-0_112076_2021-11-05_final
2021-11-07 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-09 10:01:38	ga_ls7e_ard_3-2-0_108078_2021-11-09_final
2021-11-11 09:45:05	ga_ls7e_ard_3-2-0_106068_2021-11-11_final
2021-11-14 08:38:49	ga_ls7e_ard_3-2-1_095073_2021-11-13_final
2021-11-14 10:20:53	ga_ls7e_ard_3-2-1_111081_2021-11-14_final
2021-11-21 08:49:30	ga_ls7e_ard_3-2-1_096086_2021-11-20_final
2021-11-23 10:12:37	ga_ls7e_ard_3-2-1_110078_2021-11-23_final
2021-11-27 09:46:20	ga_ls7e_ard_3-2-1_106075_2021-11-27_final
2021-11-28 08:53:01	ga_ls7e_ard_3-2-1_097081_2021-11-27_final
2021-11-28 10:30:42	ga_ls7e_ard_3-2-1_113078_2021-11-28_final
2021-11-30 08:39:40	ga_ls7e_ard_3-2-1_095079_2021-11-29_final
2021-11-30 10:16:57	ga_ls7e_ard_3-2-1_111075_2021-11-30_final
2021-12-01 09:20:03	ga_ls7e_ard_3-2-1_102072_2021-11-30_final
2021-12-03 09:08:42	ga_ls7e_ard_3-2-1_100075_2021-12-02_final
2021-12-08 09:24:22	ga_ls7e_ard_3-2-1_103069_2021-12-07_final
2021-12-11 08:20:54	ga_ls7e_ard_3-2-1_092081_2021-12-10_final
2021-12-12 09:01:40	ga_ls7e_ard_3-2-1_099075_2021-12-11_final
2021-12-14 08:49:31	ga_ls7e_ard_3-2-1_097076_2021-12-13_final
2021-12-14 08:51:31	ga_ls7e_ard_3-2-1_097081_2021-12-13_final
2021-12-16 08:38:33	ga_ls7e_ard_3-2-1_095080_2021-12-15_final
2021-12-16 08:40:33	ga_ls7e_ard_3-2-1_095085_2021-12-15_final
2021-12-16 10:16:38	ga_ls7e_ard_3-2-1_111078_2021-12-16_final
2021-12-17 09:20:31	ga_ls7e_ard_3-2-1_102077_2021-12-16_final
2021-12-19 09:07:10	ga_ls7e_ard_3-2-1_100075_2021-12-18_final
2021-12-29 09:44:51	ga_ls7e_ard_3-2-1_106079_2021-12-29_final
2022-01-01 08:39:22	ga_ls7e_ard_3-2-1_095086_2021-12-31_final
2022-01-10 08:32:43	ga_ls7e_ard_3-2-1_094087_2022-01-09_final
2022-01-12 09:54:39	ga_ls7e_ard_3-2-1_108076_2022-01-12_final
2022-01-15 08:47:35	ga_ls7e_ard_3-2-1_097079_2022-01-14_final
2022-01-15 10:26:04	ga_ls7e_ard_3-2-1_113078_2022-01-15_final
2022-01-17 10:15:31	ga_ls7e_ard_3-2-1_111083_2022-01-17_final
2022-01-21 08:10:20	ga_ls7e_ard_3-2-1_091080_2022-01-20_final
2022-01-21 08:13:08	ga_ls7e_ard_3-2-1_091087_2022-01-20_final
2022-01-24 10:20:13	ga_ls7e_ard_3-2-1_112081_2022-01-24_final
2022-01-27 09:10:45	ga_ls7e_ard_3-2-1_101078_2022-01-26_final
2022-01-29 09:00:35	ga_ls7e_ard_3-2-1_099084_2022-01-28_final
2022-01-31 08:44:50	ga_ls7e_ard_3-2-1_097076_2022-01-30_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-02-02 10:13:57	ga_ls7e_ard_3-2-1_111083_2022-02-02_final
2022-02-07 08:51:54	ga_ls7e_ard_3-2-1_098080_2022-02-06_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-11 10:06:03	ga_ls7e_ard_3-2-1_110081_2022-02-11_final
2022-02-11 10:06:27	ga_ls7e_ard_3-2-1_110082_2022-02-11_final
2022-02-14 08:58:33	ga_ls7e_ard_3-2-1_099083_2022-02-13_final
2022-02-17 09:27:33	ga_ls7e_ard_3-2-1_104079_2022-02-16_final
2022-02-17 09:28:21	ga_ls7e_ard_3-2-1_104081_2022-02-16_final
2022-02-18 08:33:50	ga_ls7e_ard_3-2-1_095084_2022-02-17_final
2022-02-18 10:08:19	ga_ls7e_ard_3-2-1_111073_2022-02-18_final
2022-02-19 09:11:49	ga_ls7e_ard_3-2-1_102071_2022-02-18_final
2022-02-22 08:11:08	ga_ls7e_ard_3-2-1_091090_2022-02-21_final
2022-02-23 08:46:43	ga_ls7e_ard_3-2-1_098071_2022-02-22_final
2022-02-23 10:27:11	ga_ls7e_ard_3-2-1_114075_2022-02-23_final
2022-02-23 10:29:35	ga_ls7e_ard_3-2-1_114081_2022-02-23_final
2022-02-26 09:20:07	ga_ls7e_ard_3-2-1_103078_2022-02-25_final
2022-02-27 08:26:48	ga_ls7e_ard_3-2-1_094084_2022-02-26_final
2022-02-28 09:06:22	ga_ls7e_ard_3-2-1_101075_2022-02-27_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-01 09:49:56	ga_ls7e_ard_3-2-1_108076_2022-03-01_final
2022-03-02 10:33:30	ga_ls7e_ard_3-2-1_115077_2022-03-02_final
2022-03-04 10:20:32	ga_ls7e_ard_3-2-1_113076_2022-03-04_final
2022-03-05 09:22:50	ga_ls7e_ard_3-2-1_104071_2022-03-04_final
2022-03-10 09:42:04	ga_ls7e_ard_3-2-1_107074_2022-03-10_final
2022-03-11 08:48:44	ga_ls7e_ard_3-2-1_098080_2022-03-10_final
2022-03-11 10:27:13	ga_ls7e_ard_3-2-1_114079_2022-03-11_final
2022-03-20 10:20:08	ga_ls7e_ard_3-2-1_113079_2022-03-20_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-24 08:18:34	ga_ls7e_ard_3-2-1_093085_2022-03-23_final
2022-03-26 09:44:06	ga_ls7e_ard_3-2-1_107083_2022-03-26_final
2022-03-27 08:45:11	ga_ls7e_ard_3-2-1_098075_2022-03-26_final
2022-03-29 08:31:51	ga_ls7e_ard_3-2-1_096073_2022-03-28_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-03-29 08:35:50	ga_ls7e_ard_3-2-1_096083_2022-03-28_final
2022-03-30 09:14:36	ga_ls7e_ard_3-2-1_103072_2022-03-29_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