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
2018-01-02 11:52:58	ga_ls7e_ard_3-0-0_115074_2018-01-02_final
2018-01-02 11:53:21	ga_ls7e_ard_3-0-0_115075_2018-01-02_final
2018-01-04 11:42:10	ga_ls7e_ard_3-0-0_113078_2018-01-04_final
2018-01-04 11:42:34	ga_ls7e_ard_3-0-0_113079_2018-01-04_final
2018-01-04 11:42:58	ga_ls7e_ard_3-0-0_113080_2018-01-04_final
2018-01-04 11:43:22	ga_ls7e_ard_3-0-0_113081_2018-01-04_final
2018-01-04 11:43:46	ga_ls7e_ard_3-0-0_113082_2018-01-04_final
2018-01-04 11:44:10	ga_ls7e_ard_3-0-0_113083_2018-01-04_final
2018-01-04 11:44:34	ga_ls7e_ard_3-0-0_113084_2018-01-04_final
2018-01-11 11:46:39	ga_ls7e_ard_3-0-0_114074_2018-01-11_final
2018-01-11 11:47:03	ga_ls7e_ard_3-0-0_114075_2018-01-11_final
2018-01-11 11:47:27	ga_ls7e_ard_3-0-0_114076_2018-01-11_final
2018-01-11 11:47:51	ga_ls7e_ard_3-0-0_114077_2018-01-11_final
2018-01-11 11:48:15	ga_ls7e_ard_3-0-0_114078_2018-01-11_final
2018-01-11 11:48:39	ga_ls7e_ard_3-0-0_114079_2018-01-11_final
2018-01-11 11:49:03	ga_ls7e_ard_3-0-0_114080_2018-01-11_final
2018-01-18 11:52:44	ga_ls7e_ard_3-0-0_115074_2018-01-18_final
2018-01-18 11:53:08	ga_ls7e_ard_3-0-0_115075_2018-01-18_final
2018-01-20 11:41:56	ga_ls7e_ard_3-0-0_113078_2018-01-20_final
2018-01-20 11:42:20	ga_ls7e_ard_3-0-0_113079_2018-01-20_final
2018-01-20 11:42:44	ga_ls7e_ard_3-0-0_113080_2018-01-20_final
2018-01-20 11:43:08	ga_ls7e_ard_3-0-0_113081_2018-01-20_final
2018-01-20 11:43:32	ga_ls7e_ard_3-0-0_113082_2018-01-20_final
2018-01-20 11:43:56	ga_ls7e_ard_3-0-0_113083_2018-01-20_final
2018-01-20 11:44:20	ga_ls7e_ard_3-0-0_113084_2018-01-20_final
2018-02-05 11:42:04	ga_ls7e_ard_3-0-0_113079_2018-02-05_final
2018-02-05 11:42:28	ga_ls7e_ard_3-0-0_113080_2018-02-05_final
2018-02-05 11:43:16	ga_ls7e_ard_3-0-0_113082_2018-02-05_final
2018-02-05 11:43:40	ga_ls7e_ard_3-0-0_113083_2018-02-05_final
2018-02-05 11:44:04	ga_ls7e_ard_3-0-0_113084_2018-02-05_final
2018-02-28 11:46:01	ga_ls7e_ard_3-0-0_114074_2018-02-28_final
2018-02-28 11:46:25	ga_ls7e_ard_3-0-0_114075_2018-02-28_final
2018-02-28 11:46:48	ga_ls7e_ard_3-0-0_114076_2018-02-28_final
2018-02-28 11:47:12	ga_ls7e_ard_3-0-0_114077_2018-02-28_final
2018-02-28 11:47:36	ga_ls7e_ard_3-0-0_114078_2018-02-28_final
2018-02-28 11:48:00	ga_ls7e_ard_3-0-0_114079_2018-02-28_final
2018-02-28 11:48:24	ga_ls7e_ard_3-0-0_114080_2018-02-28_final
2018-03-02 11:36:49	ga_ls7e_ard_3-0-0_112082_2018-03-02_final
2018-03-02 11:37:13	ga_ls7e_ard_3-0-0_112083_2018-03-02_final
2018-03-23 11:51:54	ga_ls7e_ard_3-0-0_115074_2018-03-23_final
2018-03-23 11:52:18	ga_ls7e_ard_3-0-0_115075_2018-03-23_final
2018-03-23 11:52:42	ga_ls7e_ard_3-0-0_115076_2018-03-23_final
2018-03-25 11:41:07	ga_ls7e_ard_3-0-0_113078_2018-03-25_final
2018-03-25 11:41:31	ga_ls7e_ard_3-0-0_113079_2018-03-25_final
2018-03-25 11:41:55	ga_ls7e_ard_3-0-0_113080_2018-03-25_final
2018-04-08 11:51:40	ga_ls7e_ard_3-0-0_115074_2018-04-08_final
2018-04-08 11:52:04	ga_ls7e_ard_3-0-0_115075_2018-04-08_final
2018-04-08 11:52:28	ga_ls7e_ard_3-0-0_115076_2018-04-08_final
2018-04-10 11:41:16	ga_ls7e_ard_3-0-0_113079_2018-04-10_final
2018-04-10 11:41:40	ga_ls7e_ard_3-0-0_113080_2018-04-10_final
2018-04-10 11:42:52	ga_ls7e_ard_3-0-0_113083_2018-04-10_final
2018-04-10 11:43:16	ga_ls7e_ard_3-0-0_113084_2018-04-10_final
2018-06-22 11:35:26	ga_ls7e_ard_3-0-0_112083_2018-06-22_final
2018-06-22 11:35:50	ga_ls7e_ard_3-0-0_112084_2018-06-22_final
2018-06-27 11:50:17	ga_ls7e_ard_3-0-0_115074_2018-06-27_final
2018-06-27 11:50:41	ga_ls7e_ard_3-0-0_115075_2018-06-27_final
2018-06-27 11:51:05	ga_ls7e_ard_3-0-0_115076_2018-06-27_final
2018-06-29 11:39:53	ga_ls7e_ard_3-0-0_113079_2018-06-29_final
2018-06-29 11:40:17	ga_ls7e_ard_3-0-0_113080_2018-06-29_final
2018-06-29 11:40:41	ga_ls7e_ard_3-0-0_113081_2018-06-29_final
2018-06-29 11:41:05	ga_ls7e_ard_3-0-0_113082_2018-06-29_final
2018-06-29 11:41:29	ga_ls7e_ard_3-0-0_113083_2018-06-29_final
2018-06-29 11:41:52	ga_ls7e_ard_3-0-0_113084_2018-06-29_final
2018-07-29 11:49:42	ga_ls7e_ard_3-0-0_115074_2018-07-29_final
2018-07-29 11:50:05	ga_ls7e_ard_3-0-0_115075_2018-07-29_final
2018-07-29 11:50:29	ga_ls7e_ard_3-0-0_115076_2018-07-29_final
2018-11-13 11:32:25	ga_ls7e_ard_3-0-0_112083_2018-11-13_final
2019-05-24 11:26:15	ga_ls7e_ard_3-0-0_112083_2019-05-24_final
2019-05-24 11:26:39	ga_ls7e_ard_3-1-0_112084_2019-05-24_final
2019-05-29 11:41:02	ga_ls7e_ard_3-0-0_115074_2019-05-29_final
2019-05-29 11:41:26	ga_ls7e_ard_3-0-0_115075_2019-05-29_final
2019-05-29 11:41:50	ga_ls7e_ard_3-0-0_115076_2019-05-29_final
2019-09-18 11:36:33	ga_ls7e_ard_3-1-0_115074_2019-09-18_final
2019-09-18 11:36:57	ga_ls7e_ard_3-1-0_115075_2019-09-18_final
2019-09-18 11:37:21	ga_ls7e_ard_3-1-0_115076_2019-09-18_final
2019-09-20 11:26:06	ga_ls7e_ard_3-1-0_113079_2019-09-20_final
2019-09-20 11:26:30	ga_ls7e_ard_3-1-0_113080_2019-09-20_final
2019-09-20 11:26:54	ga_ls7e_ard_3-1-0_113081_2019-09-20_final
2019-09-20 11:27:18	ga_ls7e_ard_3-1-0_113082_2019-09-20_final
2019-09-20 11:27:42	ga_ls7e_ard_3-1-0_113083_2019-09-20_final
2019-09-20 11:28:06	ga_ls7e_ard_3-1-0_113084_2019-09-20_final
2019-10-20 11:35:12	ga_ls7e_ard_3-1-0_115074_2019-10-20_final
2019-10-20 11:35:36	ga_ls7e_ard_3-1-0_115075_2019-10-20_final
2019-10-20 11:36:00	ga_ls7e_ard_3-1-0_115076_2019-10-20_final
2019-10-22 11:24:45	ga_ls7e_ard_3-1-0_113079_2019-10-22_final
2019-10-22 11:25:09	ga_ls7e_ard_3-1-0_113080_2019-10-22_final
2019-10-22 11:25:33	ga_ls7e_ard_3-1-0_113081_2019-10-22_final
2019-10-22 11:25:57	ga_ls7e_ard_3-1-0_113082_2019-10-22_final
2019-10-22 11:26:21	ga_ls7e_ard_3-1-0_113083_2019-10-22_final
2019-10-22 11:26:45	ga_ls7e_ard_3-1-0_113084_2019-10-22_final
2019-12-07 11:32:59	ga_ls7e_ard_3-1-0_115074_2019-12-07_final
2019-12-07 11:33:23	ga_ls7e_ard_3-1-0_115075_2019-12-07_final
2019-12-07 11:33:47	ga_ls7e_ard_3-1-0_115076_2019-12-07_final
2019-12-09 11:22:31	ga_ls7e_ard_3-1-0_113079_2019-12-09_final
2019-12-09 11:22:55	ga_ls7e_ard_3-1-0_113080_2019-12-09_final
2019-12-09 11:23:19	ga_ls7e_ard_3-1-0_113081_2019-12-09_final
2019-12-09 11:23:43	ga_ls7e_ard_3-1-0_113082_2019-12-09_final
2019-12-09 11:24:07	ga_ls7e_ard_3-1-0_113083_2019-12-09_final
2019-12-09 11:24:31	ga_ls7e_ard_3-1-0_113084_2019-12-09_final
2019-12-18 11:17:29	ga_ls7e_ard_3-1-0_112083_2019-12-18_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