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
2021-11-13 09:36:32	ga_ls7e_ard_3-2-1_104078_2021-11-13_final
2021-11-14 10:21:41	ga_ls7e_ard_3-2-1_111083_2021-11-14_final
2021-11-15 09:23:34	ga_ls7e_ard_3-2-1_102077_2021-11-14_final
2021-11-16 08:30:15	ga_ls7e_ard_3-2-1_093083_2021-11-15_final
2021-11-19 10:38:08	ga_ls7e_ard_3-2-1_114079_2021-11-19_final
2021-11-22 09:26:16	ga_ls7e_ard_3-2-1_103070_2021-11-21_final
2021-11-23 10:12:37	ga_ls7e_ard_3-2-1_110078_2021-11-23_final
2021-11-23 10:13:01	ga_ls7e_ard_3-2-1_110079_2021-11-23_final
2021-11-28 08:53:49	ga_ls7e_ard_3-2-1_097083_2021-11-27_final
2021-11-29 09:32:36	ga_ls7e_ard_3-2-1_104072_2021-11-29_final
2021-11-30 10:20:09	ga_ls7e_ard_3-2-1_111083_2021-11-30_final
2021-12-02 08:27:56	ga_ls7e_ard_3-2-1_093081_2021-12-01_final
2021-12-02 10:06:00	ga_ls7e_ard_3-2-1_109079_2021-12-02_final
2021-12-03 09:08:18	ga_ls7e_ard_3-2-1_100074_2021-12-02_final
2021-12-07 08:44:24	ga_ls7e_ard_3-2-1_096077_2021-12-06_final
2021-12-08 09:28:22	ga_ls7e_ard_3-2-1_103079_2021-12-07_final
2021-12-11 08:20:54	ga_ls7e_ard_3-2-1_092081_2021-12-10_final
2021-12-14 08:51:54	ga_ls7e_ard_3-2-1_097082_2021-12-13_final
2021-12-14 10:30:23	ga_ls7e_ard_3-2-1_113081_2021-12-14_final
2021-12-18 08:24:25	ga_ls7e_ard_3-2-1_093076_2021-12-17_final
2021-12-18 08:26:00	ga_ls7e_ard_3-2-1_093080_2021-12-17_final
2021-12-19 09:07:34	ga_ls7e_ard_3-2-1_100076_2021-12-18_final
2021-12-20 09:49:32	ga_ls7e_ard_3-2-1_107073_2021-12-20_final
2021-12-20 09:53:32	ga_ls7e_ard_3-2-1_107083_2021-12-20_final
2021-12-21 10:34:41	ga_ls7e_ard_3-2-1_114078_2021-12-21_final
2021-12-26 09:15:03	ga_ls7e_ard_3-2-1_101081_2021-12-25_final
2021-12-29 08:05:59	ga_ls7e_ard_3-2-1_090079_2021-12-28_final
2021-12-29 09:44:51	ga_ls7e_ard_3-2-1_106079_2021-12-29_final
2022-01-01 10:17:26	ga_ls7e_ard_3-2-1_111084_2022-01-01_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_final
2022-01-03 09:59:17	ga_ls7e_ard_3-2-1_109070_2022-01-03_final
2022-01-03 10:03:41	ga_ls7e_ard_3-2-1_109081_2022-01-03_final
2022-01-04 09:07:57	ga_ls7e_ard_3-2-1_100081_2022-01-03_final
2022-01-05 08:12:14	ga_ls7e_ard_3-2-1_091081_2022-01-04_final
2022-01-05 09:50:19	ga_ls7e_ard_3-2-1_107079_2022-01-05_final
2022-01-06 08:53:25	ga_ls7e_ard_3-2-1_098076_2022-01-05_final
2022-01-09 09:24:26	ga_ls7e_ard_3-2-1_103077_2022-01-08_final
2022-01-10 08:27:55	ga_ls7e_ard_3-2-1_094075_2022-01-09_final
2022-01-10 08:31:31	ga_ls7e_ard_3-2-1_094084_2022-01-09_final
2022-01-12 09:56:39	ga_ls7e_ard_3-2-1_108081_2022-01-12_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-15 08:48:23	ga_ls7e_ard_3-2-1_097081_2022-01-14_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-19 08:25:17	ga_ls7e_ard_3-2-1_093086_2022-01-18_final
2022-01-21 08:11:08	ga_ls7e_ard_3-2-1_091082_2022-01-20_final
2022-01-21 09:46:01	ga_ls7e_ard_3-2-1_107072_2022-01-21_final
2022-01-22 08:51:54	ga_ls7e_ard_3-2-1_098076_2022-01-21_final
2022-01-22 10:31:11	ga_ls7e_ard_3-2-1_114077_2022-01-22_final
2022-01-23 09:36:15	ga_ls7e_ard_3-2-1_105079_2022-01-23_final
2022-01-25 09:24:06	ga_ls7e_ard_3-2-1_103080_2022-01-24_final
2022-01-26 08:26:23	ga_ls7e_ard_3-2-1_094075_2022-01-25_final
2022-01-26 08:29:35	ga_ls7e_ard_3-2-1_094083_2022-01-25_final
2022-01-26 10:07:40	ga_ls7e_ard_3-2-1_110081_2022-01-26_final
2022-01-28 09:55:30	ga_ls7e_ard_3-2-1_108082_2022-01-28_final
2022-01-29 08:58:11	ga_ls7e_ard_3-2-1_099078_2022-01-28_final
2022-01-29 08:59:23	ga_ls7e_ard_3-2-1_099081_2022-01-28_final
2022-01-30 08:02:52	ga_ls7e_ard_3-2-1_090079_2022-01-29_final
2022-01-30 09:42:09	ga_ls7e_ard_3-2-1_106080_2022-01-30_final
2022-02-04 08:20:31	ga_ls7e_ard_3-2-1_093078_2022-02-03_final
2022-02-04 09:58:59	ga_ls7e_ard_3-2-1_109077_2022-02-04_final
2022-02-07 10:29:35	ga_ls7e_ard_3-2-1_114077_2022-02-07_final
2022-02-08 09:31:28	ga_ls7e_ard_3-2-1_105071_2022-02-08_final
2022-02-09 08:39:44	ga_ls7e_ard_3-2-1_096081_2022-02-08_final
2022-02-10 09:18:54	ga_ls7e_ard_3-2-1_103071_2022-02-09_final
2022-02-10 09:21:41	ga_ls7e_ard_3-2-1_103078_2022-02-09_final
2022-02-15 09:39:18	ga_ls7e_ard_3-2-1_106077_2022-02-15_final
2022-02-17 09:23:57	ga_ls7e_ard_3-2-1_104070_2022-02-16_final
2022-02-19 09:13:24	ga_ls7e_ard_3-2-1_102075_2022-02-18_final
2022-02-20 09:58:58	ga_ls7e_ard_3-2-1_109081_2022-02-20_final
2022-02-22 08:06:21	ga_ls7e_ard_3-2-1_091078_2022-02-21_final
2022-02-23 08:49:06	ga_ls7e_ard_3-2-1_098077_2022-02-22_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-24 09:29:53	ga_ls7e_ard_3-2-1_105071_2022-02-23_final
2022-02-27 08:25:12	ga_ls7e_ard_3-2-1_094080_2022-02-26_final
2022-02-28 09:07:10	ga_ls7e_ard_3-2-1_101077_2022-02-27_final
2022-03-02 10:33:30	ga_ls7e_ard_3-2-1_115077_2022-03-02_final
2022-03-06 10:04:47	ga_ls7e_ard_3-2-1_111068_2022-03-06_final
2022-03-07 09:10:16	ga_ls7e_ard_3-2-1_102071_2022-03-06_final
2022-03-07 09:11:52	ga_ls7e_ard_3-2-1_102075_2022-03-06_final
2022-03-08 08:18:09	ga_ls7e_ard_3-2-1_093080_2022-03-07_final
2022-03-08 09:57:25	ga_ls7e_ard_3-2-1_109081_2022-03-08_final
2022-03-09 09:01:42	ga_ls7e_ard_3-2-1_100081_2022-03-08_final
2022-03-10 08:04:47	ga_ls7e_ard_3-2-1_091078_2022-03-09_final
2022-03-10 09:44:28	ga_ls7e_ard_3-2-1_107080_2022-03-10_final
2022-03-11 08:45:57	ga_ls7e_ard_3-2-1_098073_2022-03-10_final
2022-03-11 10:26:25	ga_ls7e_ard_3-2-1_114077_2022-03-11_final
2022-03-15 10:01:18	ga_ls7e_ard_3-2-1_110077_2022-03-15_final
2022-03-17 09:46:20	ga_ls7e_ard_3-2-1_108071_2022-03-17_final
2022-03-19 09:36:34	ga_ls7e_ard_3-2-1_106078_2022-03-19_final
2022-03-20 08:39:16	ga_ls7e_ard_3-2-1_097074_2022-03-19_final
2022-03-20 08:42:04	ga_ls7e_ard_3-2-1_097081_2022-03-19_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-30 09:16:12	ga_ls7e_ard_3-2-1_103076_2022-03-29_final
2022-03-31 08:19:41	ga_ls7e_ard_3-2-1_094074_2022-03-30_final
2022-03-31 08:22:05	ga_ls7e_ard_3-2-1_094080_2022-03-30_final
2022-03-31 08:22:29	ga_ls7e_ard_3-2-1_094081_2022-03-30_final
2022-04-01 09:03:39	ga_ls7e_ard_3-2-1_101076_2022-03-31_final
2022-04-01 09:05:39	ga_ls7e_ard_3-2-1_101081_2022-03-31_final
2022-04-02 09:45:13	ga_ls7e_ard_3-2-1_108072_2022-04-02_final
2022-04-05 08:37:44	ga_ls7e_ard_3-2-1_097074_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