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
2022-01-29 10:35:28	ga_ls7e_ard_3-2-1_115074_2022-01-29_final
2022-01-29 10:35:52	ga_ls7e_ard_3-2-1_115075_2022-01-29_final
2022-01-29 10:36:16	ga_ls7e_ard_3-2-1_115076_2022-01-29_final
2022-01-31 10:22:55	ga_ls7e_ard_3-2-1_113074_2022-01-31_final
2022-01-31 10:23:19	ga_ls7e_ard_3-2-1_113075_2022-01-31_final
2022-01-31 10:23:43	ga_ls7e_ard_3-2-1_113076_2022-01-31_final
2022-01-31 10:24:07	ga_ls7e_ard_3-2-1_113077_2022-01-31_final
2022-01-31 10:24:31	ga_ls7e_ard_3-2-1_113078_2022-01-31_final
2022-01-31 10:24:55	ga_ls7e_ard_3-2-1_113079_2022-01-31_final
2022-01-31 10:25:19	ga_ls7e_ard_3-2-1_113080_2022-01-31_final
2022-01-31 10:25:42	ga_ls7e_ard_3-2-1_113081_2022-01-31_final
2022-01-31 10:26:06	ga_ls7e_ard_3-2-1_113082_2022-01-31_final
2022-01-31 10:26:30	ga_ls7e_ard_3-2-1_113083_2022-01-31_final
2022-02-16 10:21:16	ga_ls7e_ard_3-2-1_113074_2022-02-16_final
2022-02-16 10:21:40	ga_ls7e_ard_3-2-1_113075_2022-02-16_final
2022-02-16 10:22:04	ga_ls7e_ard_3-2-1_113076_2022-02-16_final
2022-02-16 10:22:52	ga_ls7e_ard_3-2-1_113078_2022-02-16_final
2022-02-16 10:23:16	ga_ls7e_ard_3-2-1_113079_2022-02-16_final
2022-02-16 10:24:04	ga_ls7e_ard_3-2-1_113081_2022-02-16_final
2022-02-18 10:10:19	ga_ls7e_ard_3-2-1_111078_2022-02-18_final
2022-02-18 10:10:43	ga_ls7e_ard_3-2-1_111079_2022-02-18_final
2022-02-18 10:11:07	ga_ls7e_ard_3-2-1_111080_2022-02-18_final
2022-02-18 10:11:55	ga_ls7e_ard_3-2-1_111082_2022-02-18_final
2022-02-18 10:12:19	ga_ls7e_ard_3-2-1_111083_2022-02-18_final
2022-02-18 10:12:43	ga_ls7e_ard_3-2-1_111084_2022-02-18_final
2022-02-23 10:26:47	ga_ls7e_ard_3-2-1_114074_2022-02-23_final
2022-02-23 10:27:11	ga_ls7e_ard_3-2-1_114075_2022-02-23_final
2022-02-23 10:27:35	ga_ls7e_ard_3-2-1_114076_2022-02-23_final
2022-02-23 10:28:23	ga_ls7e_ard_3-2-1_114078_2022-02-23_final
2022-02-23 10:28:47	ga_ls7e_ard_3-2-1_114079_2022-02-23_final
2022-02-25 10:14:38	ga_ls7e_ard_3-2-1_112075_2022-02-25_final
2022-02-25 10:15:50	ga_ls7e_ard_3-2-1_112078_2022-02-25_final
2022-02-25 10:16:38	ga_ls7e_ard_3-2-1_112080_2022-02-25_final
2022-02-25 10:17:26	ga_ls7e_ard_3-2-1_112082_2022-02-25_final
2022-02-25 10:17:50	ga_ls7e_ard_3-2-1_112083_2022-02-25_final
2022-02-27 10:05:17	ga_ls7e_ard_3-2-1_110083_2022-02-27_final
2022-03-13 10:12:40	ga_ls7e_ard_3-2-1_112074_2022-03-13_final
2022-03-13 10:13:04	ga_ls7e_ard_3-2-1_112075_2022-03-13_final
2022-03-13 10:13:28	ga_ls7e_ard_3-2-1_112076_2022-03-13_final
2022-03-13 10:13:52	ga_ls7e_ard_3-2-1_112077_2022-03-13_final
2022-03-13 10:14:15	ga_ls7e_ard_3-2-1_112078_2022-03-13_final
2022-03-13 10:14:39	ga_ls7e_ard_3-2-1_112079_2022-03-13_final
2022-03-13 10:15:03	ga_ls7e_ard_3-2-1_112080_2022-03-13_final
2022-03-13 10:15:27	ga_ls7e_ard_3-2-1_112081_2022-03-13_final
2022-03-13 10:16:15	ga_ls7e_ard_3-2-1_112083_2022-03-13_final
2022-03-13 10:16:39	ga_ls7e_ard_3-2-1_112084_2022-03-13_final
2022-03-15 10:03:17	ga_ls7e_ard_3-2-1_110082_2022-03-15_final
2022-03-15 10:03:41	ga_ls7e_ard_3-2-1_110083_2022-03-15_final
2022-03-15 10:04:05	ga_ls7e_ard_3-2-1_110084_2022-03-15_final
2022-03-18 10:30:41	ga_ls7e_ard_3-2-1_115074_2022-03-18_final
2022-03-18 10:31:05	ga_ls7e_ard_3-2-1_115075_2022-03-18_final
2022-03-18 10:31:29	ga_ls7e_ard_3-2-1_115076_2022-03-18_final
2022-03-20 10:17:21	ga_ls7e_ard_3-2-1_113072_2022-03-20_final
2022-03-20 10:18:09	ga_ls7e_ard_3-2-1_113074_2022-03-20_final
2022-03-20 10:18:33	ga_ls7e_ard_3-2-1_113075_2022-03-20_final
2022-03-20 10:18:56	ga_ls7e_ard_3-2-1_113076_2022-03-20_final
2022-03-20 10:19:20	ga_ls7e_ard_3-2-1_113077_2022-03-20_final
2022-03-20 10:19:44	ga_ls7e_ard_3-2-1_113078_2022-03-20_final
2022-03-20 10:20:08	ga_ls7e_ard_3-2-1_113079_2022-03-20_final
2022-03-20 10:20:32	ga_ls7e_ard_3-2-1_113080_2022-03-20_final
2022-03-20 10:20:56	ga_ls7e_ard_3-2-1_113081_2022-03-20_final
2022-03-20 10:21:20	ga_ls7e_ard_3-2-1_113082_2022-03-20_final
2022-03-20 10:21:44	ga_ls7e_ard_3-2-1_113083_2022-03-20_final
2022-03-22 10:07:12	ga_ls7e_ard_3-2-1_111078_2022-03-22_final
2022-03-22 10:07:36	ga_ls7e_ard_3-2-1_111079_2022-03-22_final
2022-03-22 10:08:00	ga_ls7e_ard_3-2-1_111080_2022-03-22_final
2022-03-22 10:08:47	ga_ls7e_ard_3-2-1_111082_2022-03-22_final
2022-03-22 10:09:11	ga_ls7e_ard_3-2-1_111083_2022-03-22_final
2022-03-27 10:23:40	ga_ls7e_ard_3-2-1_114074_2022-03-27_final
2022-03-27 10:24:04	ga_ls7e_ard_3-2-1_114075_2022-03-27_final
2022-03-27 10:24:28	ga_ls7e_ard_3-2-1_114076_2022-03-27_final
2022-03-27 10:24:52	ga_ls7e_ard_3-2-1_114077_2022-03-27_final
2022-03-27 10:25:16	ga_ls7e_ard_3-2-1_114078_2022-03-27_final
2022-03-27 10:25:40	ga_ls7e_ard_3-2-1_114079_2022-03-27_final
2022-03-27 10:26:04	ga_ls7e_ard_3-2-1_114080_2022-03-27_final
2022-03-29 10:11:07	ga_ls7e_ard_3-2-1_112074_2022-03-29_final
2022-03-29 10:11:31	ga_ls7e_ard_3-2-1_112075_2022-03-29_final
2022-03-29 10:11:55	ga_ls7e_ard_3-2-1_112076_2022-03-29_final
2022-03-29 10:12:19	ga_ls7e_ard_3-2-1_112077_2022-03-29_final
2022-03-29 10:12:43	ga_ls7e_ard_3-2-1_112078_2022-03-29_final
2022-03-29 10:13:07	ga_ls7e_ard_3-2-1_112079_2022-03-29_final
2022-03-29 10:13:31	ga_ls7e_ard_3-2-1_112080_2022-03-29_final
2022-03-29 10:13:55	ga_ls7e_ard_3-2-1_112081_2022-03-29_final
2022-03-29 10:14:19	ga_ls7e_ard_3-2-1_112082_2022-03-29_final
2022-03-29 10:14:43	ga_ls7e_ard_3-2-1_112083_2022-03-29_final
2022-03-29 10:15:07	ga_ls7e_ard_3-2-1_112084_2022-03-29_final
2022-03-31 10:01:46	ga_ls7e_ard_3-2-1_110082_2022-03-31_final
2022-04-03 10:29:10	ga_ls7e_ard_3-2-1_115074_2022-04-03_final
2022-04-03 10:29:34	ga_ls7e_ard_3-2-1_115075_2022-04-03_final
2022-04-03 10:29:58	ga_ls7e_ard_3-2-1_115076_2022-04-03_final
2022-04-05 10:15:49	ga_ls7e_ard_3-2-1_113072_2022-04-05_final
2022-04-05 10:16:37	ga_ls7e_ard_3-2-1_113074_2022-04-05_final
2022-04-05 10:17:00	ga_ls7e_ard_3-2-1_113075_2022-04-05_final
2022-04-05 10:17:24	ga_ls7e_ard_3-2-1_113076_2022-04-05_final
2022-04-05 10:17:48	ga_ls7e_ard_3-2-1_113077_2022-04-05_final
2022-04-05 10:18:12	ga_ls7e_ard_3-2-1_113078_2022-04-05_final
2022-04-05 10:18:36	ga_ls7e_ard_3-2-1_113079_2022-04-05_final
2022-04-05 10:19:00	ga_ls7e_ard_3-2-1_113080_2022-04-05_final
2022-04-05 10:19:24	ga_ls7e_ard_3-2-1_113081_2022-04-05_final
2022-04-05 10:19:48	ga_ls7e_ard_3-2-1_113082_2022-04-05_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years