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

68 results

Time (local)	Label
2020-10-01 10:54:21	ga_ls7e_ard_3-1-0_112067_2020-10-01_final
2020-10-01 10:57:33	ga_ls7e_ard_3-1-0_112075_2020-10-01_final
2020-10-01 10:57:57	ga_ls7e_ard_3-1-0_112076_2020-10-01_final
2020-10-01 10:58:20	ga_ls7e_ard_3-1-0_112077_2020-10-01_final
2020-10-01 10:58:44	ga_ls7e_ard_3-1-0_112078_2020-10-01_final
2020-10-01 10:59:08	ga_ls7e_ard_3-1-0_112079_2020-10-01_final
2020-10-01 10:59:32	ga_ls7e_ard_3-1-0_112080_2020-10-01_final
2020-10-01 10:59:56	ga_ls7e_ard_3-1-0_112081_2020-10-01_final
2020-10-01 11:01:08	ga_ls7e_ard_3-1-0_112084_2020-10-01_final
2020-10-02 10:04:15	ga_ls7e_ard_3-1-0_103081_2020-10-02_final
2020-10-03 10:41:52	ga_ls7e_ard_3-1-0_110067_2020-10-03_final
2020-10-03 10:43:04	ga_ls7e_ard_3-1-0_110070_2020-10-03_final
2020-10-03 10:43:28	ga_ls7e_ard_3-1-0_110071_2020-10-03_final
2020-10-03 10:44:39	ga_ls7e_ard_3-1-0_110074_2020-10-03_final
2020-10-03 10:45:03	ga_ls7e_ard_3-1-0_110075_2020-10-03_final
2020-10-03 10:45:27	ga_ls7e_ard_3-1-0_110076_2020-10-03_final
2020-10-03 10:45:51	ga_ls7e_ard_3-1-0_110077_2020-10-03_final
2020-10-03 10:46:15	ga_ls7e_ard_3-1-0_110078_2020-10-03_final
2020-10-03 10:46:39	ga_ls7e_ard_3-1-0_110079_2020-10-03_final
2020-10-03 10:47:27	ga_ls7e_ard_3-1-0_110081_2020-10-03_final
2020-10-03 10:47:51	ga_ls7e_ard_3-1-0_110082_2020-10-03_final
2020-10-03 10:48:15	ga_ls7e_ard_3-1-0_110083_2020-10-03_final
2020-10-04 09:48:11	ga_ls7e_ard_3-1-0_101072_2020-10-04_final
2020-10-04 09:48:35	ga_ls7e_ard_3-1-0_101073_2020-10-04_final
2020-10-04 09:49:22	ga_ls7e_ard_3-1-0_101075_2020-10-04_final
2020-10-05 10:30:11	ga_ls7e_ard_3-1-0_108069_2020-10-05_final
2020-10-05 10:30:34	ga_ls7e_ard_3-1-0_108070_2020-10-05_final
2020-10-05 10:30:58	ga_ls7e_ard_3-1-0_108071_2020-10-05_final
2020-10-05 10:31:22	ga_ls7e_ard_3-1-0_108072_2020-10-05_final
2020-10-05 10:31:46	ga_ls7e_ard_3-1-0_108073_2020-10-05_final
2020-10-05 10:32:10	ga_ls7e_ard_3-1-0_108074_2020-10-05_final
2020-10-05 10:32:34	ga_ls7e_ard_3-1-0_108075_2020-10-05_final
2020-10-05 10:32:58	ga_ls7e_ard_3-1-0_108076_2020-10-05_final
2020-10-05 10:33:22	ga_ls7e_ard_3-1-0_108077_2020-10-05_final
2020-10-05 10:33:46	ga_ls7e_ard_3-1-0_108078_2020-10-05_final
2020-10-05 10:34:10	ga_ls7e_ard_3-1-0_108079_2020-10-05_final
2020-10-05 10:34:34	ga_ls7e_ard_3-1-0_108080_2020-10-05_final
2020-10-06 09:37:41	ga_ls7e_ard_3-1-0_099077_2020-10-06_final
2020-10-06 09:39:41	ga_ls7e_ard_3-1-0_099082_2020-10-06_final
2020-10-07 10:17:17	ga_ls7e_ard_3-1-0_106068_2020-10-07_final
2020-10-07 10:18:05	ga_ls7e_ard_3-1-0_106070_2020-10-07_final
2020-10-07 10:18:53	ga_ls7e_ard_3-1-0_106072_2020-10-07_final
2020-10-07 10:19:41	ga_ls7e_ard_3-1-0_106074_2020-10-07_final
2020-10-07 10:20:05	ga_ls7e_ard_3-1-0_106075_2020-10-07_final
2020-10-07 10:20:29	ga_ls7e_ard_3-1-0_106076_2020-10-07_final
2020-10-07 10:20:53	ga_ls7e_ard_3-1-0_106077_2020-10-07_final
2020-10-07 10:21:17	ga_ls7e_ard_3-1-0_106078_2020-10-07_final
2020-10-07 10:21:41	ga_ls7e_ard_3-1-0_106079_2020-10-07_final
2020-10-07 10:22:05	ga_ls7e_ard_3-1-0_106080_2020-10-07_final
2020-10-07 10:22:29	ga_ls7e_ard_3-1-0_106081_2020-10-07_final
2020-10-07 10:22:52	ga_ls7e_ard_3-1-0_106082_2020-10-07_final
2020-10-07 10:23:16	ga_ls7e_ard_3-1-0_106083_2020-10-07_final
2020-10-08 09:26:48	ga_ls7e_ard_3-1-0_097081_2020-10-07_final
2020-10-08 11:00:05	ga_ls7e_ard_3-1-0_113067_2020-10-08_final
2020-10-08 11:02:53	ga_ls7e_ard_3-1-0_113074_2020-10-08_final
2020-10-08 11:03:17	ga_ls7e_ard_3-1-0_113075_2020-10-08_final
2020-10-08 11:03:41	ga_ls7e_ard_3-1-0_113076_2020-10-08_final
2020-10-08 11:04:05	ga_ls7e_ard_3-1-0_113077_2020-10-08_final
2020-10-08 11:04:28	ga_ls7e_ard_3-1-0_113078_2020-10-08_final
2020-10-08 11:04:52	ga_ls7e_ard_3-1-0_113079_2020-10-08_final
2020-10-08 11:05:16	ga_ls7e_ard_3-1-0_113080_2020-10-08_final
2020-10-08 11:05:40	ga_ls7e_ard_3-1-0_113081_2020-10-08_final
2020-10-09 10:06:00	ga_ls7e_ard_3-1-0_104071_2020-10-09_final
2020-10-09 10:07:12	ga_ls7e_ard_3-1-0_104074_2020-10-09_final
2020-10-09 10:08:00	ga_ls7e_ard_3-1-0_104076_2020-10-09_final
2020-10-09 10:08:23	ga_ls7e_ard_3-1-0_104077_2020-10-09_final
2020-10-09 10:09:11	ga_ls7e_ard_3-1-0_104079_2020-10-09_final
2020-10-09 10:09:35	ga_ls7e_ard_3-1-0_104080_2020-10-09_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