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
2021-03-25 08:23:59	ga_ls7e_ard_3-2-0_089078_2021-03-24_final
2021-09-18 08:49:00	ga_ls7e_ard_3-2-0_096070_2021-09-17_final
2021-09-20 10:20:07	ga_ls7e_ard_3-2-0_110082_2021-09-20_final
2021-10-25 09:04:14	ga_ls7e_ard_3-2-0_099070_2021-10-24_final
2021-11-04 09:41:35	ga_ls7e_ard_3-2-0_105073_2021-11-04_final
2021-11-04 09:45:10	ga_ls7e_ard_3-2-0_105082_2021-11-04_final
2021-11-05 10:25:32	ga_ls7e_ard_3-2-0_112075_2021-11-05_final
2021-11-13 09:33:44	ga_ls7e_ard_3-2-1_104071_2021-11-13_final
2021-11-14 08:42:00	ga_ls7e_ard_3-2-1_095081_2021-11-13_final
2021-11-17 09:11:49	ga_ls7e_ard_3-2-1_100079_2021-11-16_final
2021-11-18 08:19:18	ga_ls7e_ard_3-2-1_091087_2021-11-17_final
2021-11-20 09:40:49	ga_ls7e_ard_3-2-1_105075_2021-11-20_final
2021-11-23 08:32:09	ga_ls7e_ard_3-2-1_094074_2021-11-22_final
2021-12-02 08:26:44	ga_ls7e_ard_3-2-1_093078_2021-12-01_final
2021-12-04 08:16:35	ga_ls7e_ard_3-2-1_091084_2021-12-03_final
2021-12-08 09:24:22	ga_ls7e_ard_3-2-1_103069_2021-12-07_final
2021-12-09 10:09:56	ga_ls7e_ard_3-2-1_110075_2021-12-09_final
2021-12-13 08:11:56	ga_ls7e_ard_3-2-1_090090_2021-12-12_final
2021-12-14 08:52:42	ga_ls7e_ard_3-2-1_097084_2021-12-13_final
2021-12-18 08:23:37	ga_ls7e_ard_3-2-1_093074_2021-12-17_final
2021-12-18 08:24:48	ga_ls7e_ard_3-2-1_093077_2021-12-17_final
2021-12-19 09:08:46	ga_ls7e_ard_3-2-1_100079_2021-12-18_final
2021-12-20 08:12:39	ga_ls7e_ard_3-2-1_091078_2021-12-19_final
2021-12-25 08:30:18	ga_ls7e_ard_3-2-1_094077_2021-12-24_final
2021-12-29 08:10:22	ga_ls7e_ard_3-2-1_090090_2021-12-28_final
2022-01-02 09:19:43	ga_ls7e_ard_3-2-1_102079_2022-01-01_final
2022-01-03 10:02:53	ga_ls7e_ard_3-2-1_109079_2022-01-03_final
2022-01-04 09:07:10	ga_ls7e_ard_3-2-1_100079_2022-01-03_final
2022-01-06 08:54:36	ga_ls7e_ard_3-2-1_098079_2022-01-05_final
2022-01-06 10:33:29	ga_ls7e_ard_3-2-1_114079_2022-01-06_final
2022-01-08 10:20:32	ga_ls7e_ard_3-2-1_112078_2022-01-08_final
2022-01-09 09:25:14	ga_ls7e_ard_3-2-1_103079_2022-01-08_final
2022-01-10 08:28:43	ga_ls7e_ard_3-2-1_094077_2022-01-09_final
2022-01-13 09:00:56	ga_ls7e_ard_3-2-1_099081_2022-01-12_final
2022-01-13 09:01:44	ga_ls7e_ard_3-2-1_099083_2022-01-12_final
2022-01-15 08:49:11	ga_ls7e_ard_3-2-1_097083_2022-01-14_final
2022-01-15 10:25:40	ga_ls7e_ard_3-2-1_113077_2022-01-15_final
2022-01-16 09:26:46	ga_ls7e_ard_3-2-1_104069_2022-01-15_final
2022-01-17 08:35:26	ga_ls7e_ard_3-2-1_095080_2022-01-16_final
2022-01-17 10:14:43	ga_ls7e_ard_3-2-1_111081_2022-01-17_final
2022-01-22 10:31:58	ga_ls7e_ard_3-2-1_114079_2022-01-22_final
2022-01-24 10:18:13	ga_ls7e_ard_3-2-1_112076_2022-01-24_final
2022-01-24 10:19:01	ga_ls7e_ard_3-2-1_112078_2022-01-24_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-25 09:20:07	ga_ls7e_ard_3-2-1_103070_2022-01-24_final
2022-01-26 10:06:28	ga_ls7e_ard_3-2-1_110078_2022-01-26_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-02-03 09:12:38	ga_ls7e_ard_3-2-1_102069_2022-02-02_final
2022-02-06 08:11:08	ga_ls7e_ard_3-2-1_091086_2022-02-05_final
2022-02-09 08:36:56	ga_ls7e_ard_3-2-1_096074_2022-02-08_final
2022-02-11 08:25:58	ga_ls7e_ard_3-2-1_094078_2022-02-10_final
2022-02-11 08:26:46	ga_ls7e_ard_3-2-1_094080_2022-02-10_final
2022-02-15 08:04:01	ga_ls7e_ard_3-2-1_090086_2022-02-14_final
2022-02-17 09:24:45	ga_ls7e_ard_3-2-1_104072_2022-02-16_final
2022-02-18 08:31:02	ga_ls7e_ard_3-2-1_095077_2022-02-17_final
2022-02-18 10:11:07	ga_ls7e_ard_3-2-1_111080_2022-02-18_final
2022-02-18 10:11:31	ga_ls7e_ard_3-2-1_111081_2022-02-18_final
2022-02-20 08:19:41	ga_ls7e_ard_3-2-1_093080_2022-02-19_final
2022-02-20 09:55:22	ga_ls7e_ard_3-2-1_109072_2022-02-20_final
2022-02-22 08:07:32	ga_ls7e_ard_3-2-1_091081_2022-02-21_final
2022-02-22 08:07:56	ga_ls7e_ard_3-2-1_091082_2022-02-21_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-02-24 09:33:28	ga_ls7e_ard_3-2-1_105080_2022-02-24_final
2022-02-25 08:37:45	ga_ls7e_ard_3-2-1_096080_2022-02-24_final
2022-02-25 08:38:09	ga_ls7e_ard_3-2-1_096081_2022-02-24_final
2022-02-27 10:01:41	ga_ls7e_ard_3-2-1_110074_2022-02-27_final
2022-02-27 10:03:41	ga_ls7e_ard_3-2-1_110079_2022-02-27_final
2022-02-27 10:04:29	ga_ls7e_ard_3-2-1_110081_2022-02-27_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-01 09:50:44	ga_ls7e_ard_3-2-1_108078_2022-03-01_final
2022-03-02 10:33:06	ga_ls7e_ard_3-2-1_115076_2022-03-02_final
2022-03-02 10:34:17	ga_ls7e_ard_3-2-1_115079_2022-03-02_final
2022-03-05 09:22:26	ga_ls7e_ard_3-2-1_104070_2022-03-04_final
2022-03-08 09:56:37	ga_ls7e_ard_3-2-1_109079_2022-03-08_final
2022-03-09 08:57:43	ga_ls7e_ard_3-2-1_100071_2022-03-08_final
2022-03-09 09:00:30	ga_ls7e_ard_3-2-1_100078_2022-03-08_final
2022-03-10 08:05:59	ga_ls7e_ard_3-2-1_091081_2022-03-09_final
2022-03-10 09:42:28	ga_ls7e_ard_3-2-1_107075_2022-03-10_final
2022-03-13 08:32:11	ga_ls7e_ard_3-2-1_096070_2022-03-12_final
2022-03-13 10:14:15	ga_ls7e_ard_3-2-1_112078_2022-03-13_final
2022-03-15 10:02:05	ga_ls7e_ard_3-2-1_110079_2022-03-15_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-17 09:49:31	ga_ls7e_ard_3-2-1_108079_2022-03-17_final
2022-03-17 09:49:55	ga_ls7e_ard_3-2-1_108080_2022-03-17_final
2022-03-18 10:31:05	ga_ls7e_ard_3-2-1_115075_2022-03-18_final
2022-03-20 08:41:16	ga_ls7e_ard_3-2-1_097079_2022-03-19_final
2022-03-22 08:29:07	ga_ls7e_ard_3-2-1_095080_2022-03-21_final
2022-03-23 09:10:41	ga_ls7e_ard_3-2-1_102076_2022-03-22_final
2022-03-24 09:54:39	ga_ls7e_ard_3-2-1_109078_2022-03-24_final
2022-03-25 08:59:20	ga_ls7e_ard_3-2-1_100079_2022-03-24_final
2022-03-26 08:05:37	ga_ls7e_ard_3-2-1_091084_2022-03-25_final
2022-03-27 08:43:36	ga_ls7e_ard_3-2-1_098071_2022-03-26_final
2022-03-28 07:52:40	ga_ls7e_ard_3-2-1_089083_2022-03-27_final
2022-03-28 09:25:58	ga_ls7e_ard_3-2-1_105069_2022-03-27_final
2022-03-28 09:26:46	ga_ls7e_ard_3-2-1_105071_2022-03-27_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-31 08:21:17	ga_ls7e_ard_3-2-1_094078_2022-03-30_final
2022-03-31 09:58:58	ga_ls7e_ard_3-2-1_110075_2022-03-31_final
2022-04-02 08:09:56	ga_ls7e_ard_3-2-1_092081_2022-04-01_final
2022-04-03 10:29:10	ga_ls7e_ard_3-2-1_115074_2022-04-03_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