Search ga_ls7e_ard_3 across October 2020

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
2020-10-14 08:47:20	ga_ls7e_ard_3-1-0_091076_2020-10-13_final
2020-10-14 08:47:44	ga_ls7e_ard_3-1-0_091077_2020-10-13_final
2020-10-14 08:48:08	ga_ls7e_ard_3-1-0_091078_2020-10-13_final
2020-10-14 08:48:32	ga_ls7e_ard_3-1-0_091079_2020-10-13_final
2020-10-14 08:48:56	ga_ls7e_ard_3-1-0_091080_2020-10-13_final
2020-10-14 08:49:20	ga_ls7e_ard_3-1-0_091081_2020-10-13_final
2020-10-14 08:49:43	ga_ls7e_ard_3-1-0_091082_2020-10-13_final
2020-10-14 08:50:07	ga_ls7e_ard_3-1-0_091083_2020-10-13_final
2020-10-14 08:50:31	ga_ls7e_ard_3-1-0_091084_2020-10-13_final
2020-10-14 08:50:55	ga_ls7e_ard_3-1-0_091085_2020-10-13_final
2020-10-14 08:51:19	ga_ls7e_ard_3-1-0_091086_2020-10-13_final
2020-10-14 08:51:43	ga_ls7e_ard_3-1-0_091087_2020-10-13_final
2020-10-14 08:52:07	ga_ls7e_ard_3-1-0_091088_2020-10-13_final
2020-10-14 08:52:31	ga_ls7e_ard_3-1-0_091089_2020-10-13_final
2020-10-14 08:52:55	ga_ls7e_ard_3-1-0_091090_2020-10-13_final
2020-10-15 09:27:20	ga_ls7e_ard_3-1-0_098068_2020-10-14_final
2020-10-16 08:35:38	ga_ls7e_ard_3-1-0_089078_2020-10-15_final
2020-10-16 08:36:02	ga_ls7e_ard_3-1-0_089079_2020-10-15_final
2020-10-16 08:36:26	ga_ls7e_ard_3-1-0_089080_2020-10-15_final
2020-10-16 08:36:50	ga_ls7e_ard_3-1-0_089081_2020-10-15_final
2020-10-16 08:37:14	ga_ls7e_ard_3-1-0_089082_2020-10-15_final
2020-10-17 09:15:39	ga_ls7e_ard_3-1-0_096070_2020-10-16_final
2020-10-17 09:16:02	ga_ls7e_ard_3-1-0_096071_2020-10-16_final
2020-10-17 09:16:26	ga_ls7e_ard_3-1-0_096072_2020-10-16_final
2020-10-17 09:16:50	ga_ls7e_ard_3-1-0_096073_2020-10-16_final
2020-10-17 09:17:14	ga_ls7e_ard_3-1-0_096074_2020-10-16_final
2020-10-17 09:17:38	ga_ls7e_ard_3-1-0_096075_2020-10-16_final
2020-10-17 09:18:02	ga_ls7e_ard_3-1-0_096076_2020-10-16_final
2020-10-17 09:18:26	ga_ls7e_ard_3-1-0_096077_2020-10-16_final
2020-10-17 09:18:50	ga_ls7e_ard_3-1-0_096078_2020-10-16_final
2020-10-17 09:19:14	ga_ls7e_ard_3-1-0_096079_2020-10-16_final
2020-10-17 09:19:38	ga_ls7e_ard_3-1-0_096080_2020-10-16_final
2020-10-17 09:20:02	ga_ls7e_ard_3-1-0_096081_2020-10-16_final
2020-10-17 10:53:20	ga_ls7e_ard_3-1-0_112067_2020-10-17_final
2020-10-17 10:56:07	ga_ls7e_ard_3-1-0_112074_2020-10-17_final
2020-10-17 10:56:31	ga_ls7e_ard_3-1-0_112075_2020-10-17_final
2020-10-17 10:56:55	ga_ls7e_ard_3-1-0_112076_2020-10-17_final
2020-10-17 10:57:19	ga_ls7e_ard_3-1-0_112077_2020-10-17_final
2020-10-17 10:57:43	ga_ls7e_ard_3-1-0_112078_2020-10-17_final
2020-10-17 10:58:07	ga_ls7e_ard_3-1-0_112079_2020-10-17_final
2020-10-17 10:58:31	ga_ls7e_ard_3-1-0_112080_2020-10-17_final
2020-10-17 10:58:55	ga_ls7e_ard_3-1-0_112081_2020-10-17_final
2020-10-17 10:59:19	ga_ls7e_ard_3-1-0_112082_2020-10-17_final
2020-10-17 10:59:43	ga_ls7e_ard_3-1-0_112083_2020-10-17_final
2020-10-17 11:00:06	ga_ls7e_ard_3-1-0_112084_2020-10-17_final
2020-10-18 09:58:02	ga_ls7e_ard_3-1-0_103068_2020-10-18_final
2020-10-18 09:58:26	ga_ls7e_ard_3-1-0_103069_2020-10-18_final
2020-10-18 09:58:50	ga_ls7e_ard_3-1-0_103070_2020-10-18_final
2020-10-18 09:59:14	ga_ls7e_ard_3-1-0_103071_2020-10-18_final
2020-10-18 09:59:38	ga_ls7e_ard_3-1-0_103072_2020-10-18_final
2020-10-18 10:00:02	ga_ls7e_ard_3-1-0_103073_2020-10-18_final
2020-10-18 10:00:26	ga_ls7e_ard_3-1-0_103074_2020-10-18_final
2020-10-18 10:00:50	ga_ls7e_ard_3-1-0_103075_2020-10-18_final
2020-10-18 10:01:14	ga_ls7e_ard_3-1-0_103076_2020-10-18_final
2020-10-18 10:01:38	ga_ls7e_ard_3-1-0_103077_2020-10-18_final
2020-10-18 10:02:02	ga_ls7e_ard_3-1-0_103078_2020-10-18_final
2020-10-18 10:02:26	ga_ls7e_ard_3-1-0_103079_2020-10-18_final
2020-10-18 10:02:50	ga_ls7e_ard_3-1-0_103080_2020-10-18_final
2020-10-18 10:03:14	ga_ls7e_ard_3-1-0_103081_2020-10-18_final
2020-10-18 10:03:37	ga_ls7e_ard_3-1-0_103082_2020-10-18_final
2020-10-19 09:01:57	ga_ls7e_ard_3-1-0_094067_2020-10-18_final
2020-10-19 09:04:21	ga_ls7e_ard_3-1-0_094073_2020-10-18_final
2020-10-19 09:04:45	ga_ls7e_ard_3-1-0_094074_2020-10-18_final
2020-10-19 09:05:09	ga_ls7e_ard_3-1-0_094075_2020-10-18_final
2020-10-19 09:05:33	ga_ls7e_ard_3-1-0_094076_2020-10-18_final
2020-10-19 09:05:57	ga_ls7e_ard_3-1-0_094077_2020-10-18_final
2020-10-19 09:06:21	ga_ls7e_ard_3-1-0_094078_2020-10-18_final
2020-10-19 09:06:45	ga_ls7e_ard_3-1-0_094079_2020-10-18_final
2020-10-19 09:07:08	ga_ls7e_ard_3-1-0_094080_2020-10-18_final
2020-10-19 09:07:32	ga_ls7e_ard_3-1-0_094081_2020-10-18_final
2020-10-19 09:07:56	ga_ls7e_ard_3-1-0_094082_2020-10-18_final
2020-10-19 09:08:20	ga_ls7e_ard_3-1-0_094083_2020-10-18_final
2020-10-19 09:08:44	ga_ls7e_ard_3-1-0_094084_2020-10-18_final
2020-10-19 09:09:08	ga_ls7e_ard_3-1-0_094085_2020-10-18_final
2020-10-19 10:40:50	ga_ls7e_ard_3-1-0_110067_2020-10-19_final
2020-10-19 10:42:02	ga_ls7e_ard_3-1-0_110070_2020-10-19_final
2020-10-19 10:42:26	ga_ls7e_ard_3-1-0_110071_2020-10-19_final
2020-10-19 10:42:50	ga_ls7e_ard_3-1-0_110072_2020-10-19_final
2020-10-19 10:43:14	ga_ls7e_ard_3-1-0_110073_2020-10-19_final
2020-10-19 10:43:38	ga_ls7e_ard_3-1-0_110074_2020-10-19_final
2020-10-19 10:44:02	ga_ls7e_ard_3-1-0_110075_2020-10-19_final
2020-10-19 10:44:25	ga_ls7e_ard_3-1-0_110076_2020-10-19_final
2020-10-19 10:44:49	ga_ls7e_ard_3-1-0_110077_2020-10-19_final
2020-10-19 10:45:13	ga_ls7e_ard_3-1-0_110078_2020-10-19_final
2020-10-19 10:45:37	ga_ls7e_ard_3-1-0_110079_2020-10-19_final
2020-10-19 10:46:01	ga_ls7e_ard_3-1-0_110080_2020-10-19_final
2020-10-19 10:46:25	ga_ls7e_ard_3-1-0_110081_2020-10-19_final
2020-10-19 10:46:49	ga_ls7e_ard_3-1-0_110082_2020-10-19_final
2020-10-19 10:47:13	ga_ls7e_ard_3-1-0_110083_2020-10-19_final
2020-10-19 10:47:37	ga_ls7e_ard_3-1-0_110084_2020-10-19_final
2020-10-20 09:46:45	ga_ls7e_ard_3-1-0_101071_2020-10-20_final
2020-10-20 09:47:09	ga_ls7e_ard_3-1-0_101072_2020-10-20_final
2020-10-20 09:47:33	ga_ls7e_ard_3-1-0_101073_2020-10-20_final
2020-10-20 09:47:56	ga_ls7e_ard_3-1-0_101074_2020-10-20_final
2020-10-20 09:48:20	ga_ls7e_ard_3-1-0_101075_2020-10-20_final
2020-10-20 09:48:44	ga_ls7e_ard_3-1-0_101076_2020-10-20_final
2020-10-20 09:49:08	ga_ls7e_ard_3-1-0_101077_2020-10-20_final
2020-10-20 09:49:32	ga_ls7e_ard_3-1-0_101078_2020-10-20_final
2020-10-20 09:49:56	ga_ls7e_ard_3-1-0_101079_2020-10-20_final
2020-10-20 09:50:20	ga_ls7e_ard_3-1-0_101080_2020-10-20_final

Return to ga_ls7e_ard_3 across October 2020 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

2020

October

All days