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

54 results

Time (local)	Label
2020-11-04 10:39:46	ga_ls7e_ard_3-1-0_110067_2020-11-04_final
2020-11-04 10:41:22	ga_ls7e_ard_3-1-0_110071_2020-11-04_final
2020-11-04 10:41:46	ga_ls7e_ard_3-1-0_110072_2020-11-04_final
2020-11-04 10:42:10	ga_ls7e_ard_3-1-0_110073_2020-11-04_final
2020-11-04 10:42:34	ga_ls7e_ard_3-1-0_110074_2020-11-04_final
2020-11-04 10:42:58	ga_ls7e_ard_3-1-0_110075_2020-11-04_final
2020-11-04 10:43:22	ga_ls7e_ard_3-1-0_110076_2020-11-04_final
2020-11-04 10:43:45	ga_ls7e_ard_3-1-0_110077_2020-11-04_final
2020-11-04 10:44:09	ga_ls7e_ard_3-1-0_110078_2020-11-04_final
2020-11-04 10:44:33	ga_ls7e_ard_3-1-0_110079_2020-11-04_final
2020-11-04 10:45:21	ga_ls7e_ard_3-1-0_110081_2020-11-04_final
2020-11-04 10:45:45	ga_ls7e_ard_3-1-0_110082_2020-11-04_final
2020-11-04 10:46:33	ga_ls7e_ard_3-1-0_110084_2020-11-04_final
2020-11-05 09:45:41	ga_ls7e_ard_3-1-0_101071_2020-11-05_final
2020-11-05 09:46:05	ga_ls7e_ard_3-1-0_101072_2020-11-05_final
2020-11-05 09:46:28	ga_ls7e_ard_3-1-0_101073_2020-11-05_final
2020-11-05 09:46:52	ga_ls7e_ard_3-1-0_101074_2020-11-05_final
2020-11-05 09:47:16	ga_ls7e_ard_3-1-0_101075_2020-11-05_final
2020-11-05 09:47:40	ga_ls7e_ard_3-1-0_101076_2020-11-05_final
2020-11-05 09:48:04	ga_ls7e_ard_3-1-0_101077_2020-11-05_final
2020-11-05 09:48:28	ga_ls7e_ard_3-1-0_101078_2020-11-05_final
2020-11-05 09:48:52	ga_ls7e_ard_3-1-0_101079_2020-11-05_final
2020-11-05 09:49:16	ga_ls7e_ard_3-1-0_101080_2020-11-05_final
2020-11-05 09:49:40	ga_ls7e_ard_3-1-0_101081_2020-11-05_final
2020-11-05 09:50:04	ga_ls7e_ard_3-1-0_101082_2020-11-05_final
2020-11-05 09:50:28	ga_ls7e_ard_3-1-0_101083_2020-11-05_final
2020-12-04 09:11:08	ga_ls7e_ard_3-1-0_096067_2020-12-03_final
2020-12-04 09:12:20	ga_ls7e_ard_3-1-0_096070_2020-12-03_final
2020-12-04 09:12:44	ga_ls7e_ard_3-1-0_096071_2020-12-03_final
2020-12-04 09:13:07	ga_ls7e_ard_3-1-0_096072_2020-12-03_final
2020-12-04 09:13:31	ga_ls7e_ard_3-1-0_096073_2020-12-03_final
2020-12-04 09:13:55	ga_ls7e_ard_3-1-0_096074_2020-12-03_final
2020-12-04 09:14:19	ga_ls7e_ard_3-1-0_096075_2020-12-03_final
2020-12-04 09:14:43	ga_ls7e_ard_3-1-0_096076_2020-12-03_final
2020-12-04 09:15:07	ga_ls7e_ard_3-1-0_096077_2020-12-03_final
2020-12-04 09:15:31	ga_ls7e_ard_3-1-0_096078_2020-12-03_final
2020-12-04 09:15:55	ga_ls7e_ard_3-1-0_096079_2020-12-03_final
2020-12-04 09:16:19	ga_ls7e_ard_3-1-0_096080_2020-12-03_final
2020-12-04 09:16:43	ga_ls7e_ard_3-1-0_096081_2020-12-03_final
2020-12-04 09:17:07	ga_ls7e_ard_3-1-0_096082_2020-12-03_final
2020-12-04 09:17:31	ga_ls7e_ard_3-1-0_096083_2020-12-03_final
2020-12-04 09:17:55	ga_ls7e_ard_3-1-0_096084_2020-12-03_final
2020-12-04 09:18:19	ga_ls7e_ard_3-1-0_096085_2020-12-03_final
2020-12-04 09:18:43	ga_ls7e_ard_3-1-0_096086_2020-12-03_final
2020-12-04 10:52:48	ga_ls7e_ard_3-1-0_112074_2020-12-04_final
2020-12-04 10:53:12	ga_ls7e_ard_3-1-0_112075_2020-12-04_final
2020-12-04 10:53:36	ga_ls7e_ard_3-1-0_112076_2020-12-04_final
2020-12-04 10:54:00	ga_ls7e_ard_3-1-0_112077_2020-12-04_final
2020-12-04 10:54:24	ga_ls7e_ard_3-1-0_112078_2020-12-04_final
2020-12-04 10:54:48	ga_ls7e_ard_3-1-0_112079_2020-12-04_final
2020-12-04 10:55:12	ga_ls7e_ard_3-1-0_112080_2020-12-04_final
2020-12-04 10:55:36	ga_ls7e_ard_3-1-0_112081_2020-12-04_final
2020-12-04 10:56:00	ga_ls7e_ard_3-1-0_112082_2020-12-04_final
2020-12-04 10:56:24	ga_ls7e_ard_3-1-0_112083_2020-12-04_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years