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
2021-09-18 08:53:47	ga_ls7e_ard_3-2-0_096082_2021-09-17_final
2021-10-26 08:14:07	ga_ls7e_ard_3-2-0_090084_2021-10-25_final
2021-10-26 08:14:31	ga_ls7e_ard_3-2-0_090085_2021-10-25_final
2021-10-26 09:51:23	ga_ls7e_ard_3-2-0_106080_2021-10-26_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
2021-11-18 09:55:22	ga_ls7e_ard_3-2-1_107080_2021-11-18_final
2021-11-19 10:37:20	ga_ls7e_ard_3-2-1_114077_2021-11-19_final
2021-11-21 08:44:42	ga_ls7e_ard_3-2-1_096074_2021-11-20_final
2021-11-29 09:34:59	ga_ls7e_ard_3-2-1_104078_2021-11-29_final
2021-12-07 08:45:36	ga_ls7e_ard_3-2-1_096080_2021-12-06_final
2021-12-09 08:34:15	ga_ls7e_ard_3-2-1_094083_2021-12-08_final
2021-12-09 10:11:08	ga_ls7e_ard_3-2-1_110078_2021-12-09_final
2021-12-10 09:13:49	ga_ls7e_ard_3-2-1_101074_2021-12-09_final
2021-12-11 09:57:47	ga_ls7e_ard_3-2-1_108076_2021-12-11_final
2021-12-13 09:46:25	ga_ls7e_ard_3-2-1_106079_2021-12-13_final
2021-12-14 08:51:54	ga_ls7e_ard_3-2-1_097082_2021-12-13_final
2021-12-14 08:52:42	ga_ls7e_ard_3-2-1_097084_2021-12-13_final
2021-12-17 09:16:56	ga_ls7e_ard_3-2-1_102068_2021-12-16_final
2021-12-17 09:20:31	ga_ls7e_ard_3-2-1_102077_2021-12-16_final
2021-12-17 09:22:31	ga_ls7e_ard_3-2-1_102082_2021-12-16_final
2021-12-20 09:53:08	ga_ls7e_ard_3-2-1_107082_2021-12-20_final
2021-12-21 08:53:49	ga_ls7e_ard_3-2-1_098073_2021-12-20_final
2021-12-21 08:54:13	ga_ls7e_ard_3-2-1_098074_2021-12-20_final
2021-12-22 09:39:22	ga_ls7e_ard_3-2-1_105079_2021-12-22_final
2021-12-23 08:45:39	ga_ls7e_ard_3-2-1_096084_2021-12-22_final
2021-12-23 10:21:20	ga_ls7e_ard_3-2-1_112076_2021-12-23_final
2021-12-25 10:11:10	ga_ls7e_ard_3-2-1_110082_2021-12-25_final
2021-12-25 10:11:34	ga_ls7e_ard_3-2-1_110083_2021-12-25_final
2021-12-29 08:09:58	ga_ls7e_ard_3-2-1_090089_2021-12-28_final
2022-01-01 08:34:58	ga_ls7e_ard_3-2-1_095075_2021-12-31_final
2022-01-01 08:38:10	ga_ls7e_ard_3-2-1_095083_2021-12-31_final
2022-01-01 10:17:03	ga_ls7e_ard_3-2-1_111083_2022-01-01_final
2022-01-03 08:26:00	ga_ls7e_ard_3-2-1_093084_2022-01-02_final
2022-01-06 08:52:13	ga_ls7e_ard_3-2-1_098073_2022-01-05_final
2022-01-06 08:53:01	ga_ls7e_ard_3-2-1_098075_2022-01-05_final
2022-01-07 09:35:23	ga_ls7e_ard_3-2-1_105073_2022-01-07_final
2022-01-09 09:26:26	ga_ls7e_ard_3-2-1_103082_2022-01-08_final
2022-01-10 10:06:24	ga_ls7e_ard_3-2-1_110074_2022-01-10_final
2022-01-12 09:53:03	ga_ls7e_ard_3-2-1_108072_2022-01-12_final
2022-01-14 08:06:25	ga_ls7e_ard_3-2-1_090084_2022-01-13_final
2022-01-15 08:47:59	ga_ls7e_ard_3-2-1_097080_2022-01-14_final
2022-01-17 10:12:43	ga_ls7e_ard_3-2-1_111076_2022-01-17_final
2022-01-19 08:21:41	ga_ls7e_ard_3-2-1_093077_2022-01-18_final
2022-01-20 09:05:39	ga_ls7e_ard_3-2-1_100079_2022-01-19_final
2022-01-25 09:22:54	ga_ls7e_ard_3-2-1_103077_2022-01-24_final
2022-01-26 08:27:11	ga_ls7e_ard_3-2-1_094077_2022-01-25_final
2022-01-27 09:10:45	ga_ls7e_ard_3-2-1_101078_2022-01-26_final
2022-01-27 09:11:09	ga_ls7e_ard_3-2-1_101079_2022-01-26_final
2022-01-29 08:59:23	ga_ls7e_ard_3-2-1_099081_2022-01-28_final
2022-01-30 09:42:57	ga_ls7e_ard_3-2-1_106082_2022-01-30_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-02-02 08:32:40	ga_ls7e_ard_3-2-1_095077_2022-02-01_final
2022-02-04 08:23:18	ga_ls7e_ard_3-2-1_093085_2022-02-03_final
2022-02-05 09:02:04	ga_ls7e_ard_3-2-1_100074_2022-02-04_final
2022-02-07 08:52:42	ga_ls7e_ard_3-2-1_098082_2022-02-06_final
2022-02-07 10:30:23	ga_ls7e_ard_3-2-1_114079_2022-02-07_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-09 08:37:20	ga_ls7e_ard_3-2-1_096075_2022-02-08_final
2022-02-10 09:18:54	ga_ls7e_ard_3-2-1_103071_2022-02-09_final
2022-02-10 09:22:29	ga_ls7e_ard_3-2-1_103080_2022-02-09_final
2022-02-11 08:27:10	ga_ls7e_ard_3-2-1_094081_2022-02-10_final
2022-02-11 08:27:34	ga_ls7e_ard_3-2-1_094082_2022-02-10_final
2022-02-11 08:28:22	ga_ls7e_ard_3-2-1_094084_2022-02-10_final
2022-02-13 09:51:29	ga_ls7e_ard_3-2-1_108076_2022-02-13_final
2022-02-14 08:58:57	ga_ls7e_ard_3-2-1_099084_2022-02-13_final
2022-02-14 10:33:50	ga_ls7e_ard_3-2-1_115074_2022-02-14_final
2022-02-16 08:41:11	ga_ls7e_ard_3-2-1_097071_2022-02-15_final
2022-02-16 08:45:35	ga_ls7e_ard_3-2-1_097082_2022-02-15_final
2022-02-16 10:23:40	ga_ls7e_ard_3-2-1_113080_2022-02-16_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_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
2022-02-27 08:25:36	ga_ls7e_ard_3-2-1_094081_2022-02-26_final
2022-02-27 08:26:00	ga_ls7e_ard_3-2-1_094082_2022-02-26_final
2022-03-01 08:11:03	ga_ls7e_ard_3-2-1_092076_2022-02-28_final
2022-03-02 08:57:24	ga_ls7e_ard_3-2-1_099084_2022-03-01_final
2022-03-03 09:35:47	ga_ls7e_ard_3-2-1_106072_2022-03-03_final
2022-03-10 09:40:28	ga_ls7e_ard_3-2-1_107070_2022-03-10_final
2022-03-10 09:40:52	ga_ls7e_ard_3-2-1_107071_2022-03-10_final
2022-03-10 09:44:52	ga_ls7e_ard_3-2-1_107081_2022-03-10_final
2022-03-11 08:45:57	ga_ls7e_ard_3-2-1_098073_2022-03-10_final
2022-03-13 08:34:11	ga_ls7e_ard_3-2-1_096075_2022-03-12_final
2022-03-14 09:16:32	ga_ls7e_ard_3-2-1_103073_2022-03-13_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
2022-03-21 09:23:14	ga_ls7e_ard_3-2-1_104076_2022-03-20_final
2022-03-21 09:23:38	ga_ls7e_ard_3-2-1_104077_2022-03-20_final
2022-03-21 09:24:26	ga_ls7e_ard_3-2-1_104079_2022-03-20_final
2022-03-22 08:27:07	ga_ls7e_ard_3-2-1_095075_2022-03-21_final
2022-03-26 08:02:49	ga_ls7e_ard_3-2-1_091077_2022-03-25_final
2022-03-26 09:43:18	ga_ls7e_ard_3-2-1_107081_2022-03-26_final
2022-03-27 08:44:24	ga_ls7e_ard_3-2-1_098073_2022-03-26_final
2022-03-27 08:44:47	ga_ls7e_ard_3-2-1_098074_2022-03-26_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-29 08:31:03	ga_ls7e_ard_3-2-1_096071_2022-03-28_final
2022-03-31 08:22:53	ga_ls7e_ard_3-2-1_094082_2022-03-30_final
2022-03-31 08:23:41	ga_ls7e_ard_3-2-1_094084_2022-03-30_final
2022-04-01 09:01:15	ga_ls7e_ard_3-2-1_101070_2022-03-31_final
2022-04-04 07:57:46	ga_ls7e_ard_3-2-1_090082_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