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
2021-07-22 08:21:00	ga_ls7e_ard_3-2-0_090080_2021-07-21_final
2021-07-25 08:49:14	ga_ls7e_ard_3-2-0_095074_2021-07-24_final
2021-07-29 10:02:39	ga_ls7e_ard_3-2-0_107073_2021-07-29_final
2021-07-31 09:49:19	ga_ls7e_ard_3-2-0_105071_2021-07-31_final
2021-08-02 09:39:10	ga_ls7e_ard_3-2-0_103077_2021-08-02_final
2021-08-04 09:27:50	ga_ls7e_ard_3-2-0_101080_2021-08-03_final
2021-08-05 08:31:44	ga_ls7e_ard_3-2-0_092079_2021-08-04_final
2021-08-05 08:32:08	ga_ls7e_ard_3-2-0_092080_2021-08-04_final
2021-08-08 09:01:34	ga_ls7e_ard_3-2-0_097077_2021-08-07_final
2021-08-19 10:21:19	ga_ls7e_ard_3-2-0_110078_2021-08-19_final
2021-08-21 10:09:59	ga_ls7e_ard_3-2-0_108081_2021-08-21_final
2021-08-23 09:57:27	ga_ls7e_ard_3-2-0_106081_2021-08-23_final
2021-08-24 09:02:57	ga_ls7e_ard_3-2-0_097084_2021-08-23_final
2021-08-24 10:39:02	ga_ls7e_ard_3-2-0_113077_2021-08-24_final
2021-08-24 10:39:26	ga_ls7e_ard_3-2-0_113078_2021-08-24_final
2021-08-28 08:34:42	ga_ls7e_ard_3-2-0_093076_2021-08-27_final
2021-08-29 09:19:52	ga_ls7e_ard_3-2-0_100081_2021-08-28_final
2021-09-02 08:54:48	ga_ls7e_ard_3-2-0_096081_2021-09-01_final
2021-09-02 08:56:24	ga_ls7e_ard_3-2-0_096085_2021-09-01_final
2021-09-06 10:08:36	ga_ls7e_ard_3-2-0_108081_2021-09-06_final
2021-09-09 10:38:51	ga_ls7e_ard_3-2-0_113080_2021-09-09_final
2021-09-11 10:21:07	ga_ls7e_ard_3-2-0_111067_2021-09-11_final
2021-09-22 10:06:47	ga_ls7e_ard_3-2-0_108080_2021-09-22_final
2021-09-22 10:07:11	ga_ls7e_ard_3-2-0_108081_2021-09-22_final
2021-09-26 09:40:06	ga_ls7e_ard_3-2-0_104076_2021-09-26_final
2021-09-27 10:24:28	ga_ls7e_ard_3-2-0_111079_2021-09-27_final
2021-09-29 10:11:08	ga_ls7e_ard_3-2-0_109077_2021-09-29_final
2021-10-11 08:57:31	ga_ls7e_ard_3-2-0_097081_2021-10-10_final
2021-10-11 10:35:36	ga_ls7e_ard_3-2-0_113079_2021-10-11_final
2021-10-12 09:39:06	ga_ls7e_ard_3-2-0_104077_2021-10-12_final
2021-10-13 10:24:16	ga_ls7e_ard_3-2-0_111082_2021-10-13_final
2021-10-19 09:43:03	ga_ls7e_ard_3-2-0_105073_2021-10-19_final
2021-10-20 08:49:44	ga_ls7e_ard_3-2-0_096079_2021-10-19_final
2021-10-20 08:51:20	ga_ls7e_ard_3-2-0_096083_2021-10-19_final
2021-10-20 10:28:13	ga_ls7e_ard_3-2-0_112078_2021-10-20_final
2021-10-22 10:15:41	ga_ls7e_ard_3-2-0_110078_2021-10-22_final
2021-10-26 09:52:11	ga_ls7e_ard_3-2-0_106082_2021-10-26_final
2021-10-28 09:36:27	ga_ls7e_ard_3-2-0_104074_2021-10-28_final
2021-10-28 09:39:15	ga_ls7e_ard_3-2-0_104081_2021-10-28_final
2021-10-30 09:25:06	ga_ls7e_ard_3-2-0_102077_2021-10-29_final
2021-10-31 08:31:47	ga_ls7e_ard_3-2-0_093083_2021-10-30_final
2021-10-31 10:09:52	ga_ls7e_ard_3-2-0_109081_2021-10-31_final
2021-11-01 09:12:10	ga_ls7e_ard_3-2-0_100076_2021-10-31_final
2021-11-03 08:59:37	ga_ls7e_ard_3-2-0_098076_2021-11-02_final
2021-11-05 08:46:40	ga_ls7e_ard_3-2-0_096075_2021-11-04_final
2021-11-05 08:47:52	ga_ls7e_ard_3-2-0_096078_2021-11-04_final
2021-11-14 10:19:17	ga_ls7e_ard_3-2-1_111077_2021-11-14_final
2021-11-15 09:23:10	ga_ls7e_ard_3-2-1_102076_2021-11-14_final
2021-11-16 08:29:27	ga_ls7e_ard_3-2-1_093081_2021-11-15_final
2021-11-16 10:04:44	ga_ls7e_ard_3-2-1_109072_2021-11-16_final
2021-12-04 08:15:47	ga_ls7e_ard_3-2-1_091082_2021-12-03_final
2021-12-05 08:58:57	ga_ls7e_ard_3-2-1_098082_2021-12-04_final
2021-12-08 09:26:46	ga_ls7e_ard_3-2-1_103075_2021-12-07_final
2021-12-10 09:14:13	ga_ls7e_ard_3-2-1_101075_2021-12-09_final
2021-12-14 10:28:47	ga_ls7e_ard_3-2-1_113077_2021-12-14_final
2021-12-18 10:01:41	ga_ls7e_ard_3-2-1_109072_2021-12-18_final
2021-12-20 08:13:03	ga_ls7e_ard_3-2-1_091079_2021-12-19_final
2021-12-23 08:43:15	ga_ls7e_ard_3-2-1_096078_2021-12-22_final
2021-12-30 08:47:32	ga_ls7e_ard_3-2-1_097075_2021-12-29_final
2022-01-03 08:24:24	ga_ls7e_ard_3-2-1_093080_2022-01-02_final
2022-01-05 09:48:43	ga_ls7e_ard_3-2-1_107075_2022-01-05_final
2022-01-08 08:42:04	ga_ls7e_ard_3-2-1_096079_2022-01-07_final
2022-01-12 08:16:58	ga_ls7e_ard_3-2-1_092079_2022-01-11_final
2022-01-12 09:56:15	ga_ls7e_ard_3-2-1_108080_2022-01-12_final
2022-01-13 08:58:08	ga_ls7e_ard_3-2-1_099074_2022-01-12_final
2022-01-14 09:44:30	ga_ls7e_ard_3-2-1_106082_2022-01-14_final
2022-01-16 09:27:10	ga_ls7e_ard_3-2-1_104070_2022-01-15_final
2022-01-17 10:15:07	ga_ls7e_ard_3-2-1_111082_2022-01-17_final
2022-01-18 09:15:25	ga_ls7e_ard_3-2-1_102072_2022-01-17_final
2022-01-19 08:25:17	ga_ls7e_ard_3-2-1_093086_2022-01-18_final
2022-01-24 08:38:33	ga_ls7e_ard_3-2-1_096074_2022-01-23_final
2022-01-24 10:19:49	ga_ls7e_ard_3-2-1_112080_2022-01-24_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-02-10 09:20:54	ga_ls7e_ard_3-2-1_103076_2022-02-09_final
2022-02-11 08:27:58	ga_ls7e_ard_3-2-1_094083_2022-02-10_final
2022-02-11 08:29:34	ga_ls7e_ard_3-2-1_094087_2022-02-10_final
2022-02-17 09:27:57	ga_ls7e_ard_3-2-1_104080_2022-02-16_final
2022-02-22 09:46:25	ga_ls7e_ard_3-2-1_107081_2022-02-22_final
2022-02-25 08:38:09	ga_ls7e_ard_3-2-1_096081_2022-02-24_final
2022-02-25 10:16:38	ga_ls7e_ard_3-2-1_112080_2022-02-25_final
2022-02-27 08:26:24	ga_ls7e_ard_3-2-1_094083_2022-02-26_final
2022-02-28 09:05:58	ga_ls7e_ard_3-2-1_101074_2022-02-27_final
2022-02-28 09:06:46	ga_ls7e_ard_3-2-1_101076_2022-02-27_final
2022-03-02 08:53:25	ga_ls7e_ard_3-2-1_099074_2022-03-01_final
2022-03-05 09:23:14	ga_ls7e_ard_3-2-1_104072_2022-03-04_final
2022-03-08 08:18:09	ga_ls7e_ard_3-2-1_093080_2022-03-07_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
2022-03-17 09:50:43	ga_ls7e_ard_3-2-1_108082_2022-03-17_final
2022-03-19 09:36:10	ga_ls7e_ard_3-2-1_106077_2022-03-19_final
2022-03-20 10:18:33	ga_ls7e_ard_3-2-1_113075_2022-03-20_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-21 09:24:02	ga_ls7e_ard_3-2-1_104078_2022-03-20_final
2022-03-21 09:24:26	ga_ls7e_ard_3-2-1_104079_2022-03-20_final
2022-03-24 08:15:22	ga_ls7e_ard_3-2-1_093077_2022-03-23_final
2022-03-29 08:31:27	ga_ls7e_ard_3-2-1_096072_2022-03-28_final
2022-03-30 09:16:12	ga_ls7e_ard_3-2-1_103076_2022-03-29_final
2022-03-31 08:21:41	ga_ls7e_ard_3-2-1_094079_2022-03-30_final
2022-04-01 09:02:51	ga_ls7e_ard_3-2-1_101074_2022-03-31_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