Search ga_ls7e_ard_3 across October 2016

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
2016-10-06 09:54:33	ga_ls7e_ard_3-0-0_096070_2016-10-06_final
2016-10-06 09:54:56	ga_ls7e_ard_3-0-0_096071_2016-10-06_final
2016-10-06 09:55:20	ga_ls7e_ard_3-0-0_096072_2016-10-06_final
2016-10-06 09:55:44	ga_ls7e_ard_3-0-0_096073_2016-10-06_final
2016-10-06 09:56:08	ga_ls7e_ard_3-0-0_096074_2016-10-06_final
2016-10-06 09:56:32	ga_ls7e_ard_3-0-0_096075_2016-10-06_final
2016-10-06 09:56:56	ga_ls7e_ard_3-0-0_096076_2016-10-06_final
2016-10-06 09:57:20	ga_ls7e_ard_3-0-0_096077_2016-10-06_final
2016-10-06 09:57:44	ga_ls7e_ard_3-0-0_096078_2016-10-06_final
2016-10-06 09:58:08	ga_ls7e_ard_3-0-0_096079_2016-10-06_final
2016-10-06 09:58:32	ga_ls7e_ard_3-0-0_096080_2016-10-06_final
2016-10-06 09:58:56	ga_ls7e_ard_3-0-0_096081_2016-10-06_final
2016-10-06 09:59:20	ga_ls7e_ard_3-0-0_096082_2016-10-06_final
2016-10-06 09:59:44	ga_ls7e_ard_3-0-0_096083_2016-10-06_final
2016-10-06 10:00:08	ga_ls7e_ard_3-0-0_096084_2016-10-06_final
2016-10-06 10:00:32	ga_ls7e_ard_3-0-0_096085_2016-10-06_final
2016-10-06 10:00:56	ga_ls7e_ard_3-1-0_096086_2016-10-06_final
2016-10-06 11:32:14	ga_ls7e_ard_3-0-0_112067_2016-10-06_final
2016-10-06 11:35:01	ga_ls7e_ard_3-0-0_112074_2016-10-06_final
2016-10-06 11:35:25	ga_ls7e_ard_3-0-0_112075_2016-10-06_final
2016-10-06 11:35:49	ga_ls7e_ard_3-0-0_112076_2016-10-06_final
2016-10-06 11:36:13	ga_ls7e_ard_3-0-0_112077_2016-10-06_final
2016-10-06 11:36:37	ga_ls7e_ard_3-0-0_112078_2016-10-06_final
2016-10-06 11:37:01	ga_ls7e_ard_3-0-0_112079_2016-10-06_final
2016-10-06 11:37:25	ga_ls7e_ard_3-0-0_112080_2016-10-06_final
2016-10-06 11:37:49	ga_ls7e_ard_3-0-0_112081_2016-10-06_final
2016-10-06 11:38:13	ga_ls7e_ard_3-0-0_112082_2016-10-06_final
2016-10-07 10:37:00	ga_ls7e_ard_3-0-0_103068_2016-10-07_final
2016-10-07 10:37:24	ga_ls7e_ard_3-0-0_103069_2016-10-07_final
2016-10-07 10:37:48	ga_ls7e_ard_3-0-0_103070_2016-10-07_final
2016-10-07 10:38:12	ga_ls7e_ard_3-0-0_103071_2016-10-07_final
2016-10-07 10:38:36	ga_ls7e_ard_3-0-0_103072_2016-10-07_final
2016-10-07 10:39:00	ga_ls7e_ard_3-0-0_103073_2016-10-07_final
2016-10-07 10:39:24	ga_ls7e_ard_3-0-0_103074_2016-10-07_final
2016-10-07 10:39:48	ga_ls7e_ard_3-0-0_103075_2016-10-07_final
2016-10-07 10:40:12	ga_ls7e_ard_3-0-0_103076_2016-10-07_final
2016-10-07 10:40:36	ga_ls7e_ard_3-0-0_103077_2016-10-07_final
2016-10-07 10:41:00	ga_ls7e_ard_3-0-0_103078_2016-10-07_final
2016-10-07 10:41:24	ga_ls7e_ard_3-0-0_103079_2016-10-07_final
2016-10-07 10:41:48	ga_ls7e_ard_3-0-0_103080_2016-10-07_final
2016-10-07 10:42:12	ga_ls7e_ard_3-0-0_103081_2016-10-07_final
2016-10-07 10:42:36	ga_ls7e_ard_3-0-0_103082_2016-10-07_final
2016-10-08 09:43:23	ga_ls7e_ard_3-0-0_094073_2016-10-08_final
2016-10-08 09:43:47	ga_ls7e_ard_3-0-0_094074_2016-10-08_final
2016-10-08 09:44:11	ga_ls7e_ard_3-0-0_094075_2016-10-08_final
2016-10-08 09:44:35	ga_ls7e_ard_3-0-0_094076_2016-10-08_final
2016-10-08 09:44:58	ga_ls7e_ard_3-0-0_094077_2016-10-08_final
2016-10-08 09:45:22	ga_ls7e_ard_3-0-0_094078_2016-10-08_final
2016-10-08 09:45:46	ga_ls7e_ard_3-0-0_094079_2016-10-08_final
2016-10-08 09:46:10	ga_ls7e_ard_3-0-0_094080_2016-10-08_final
2016-10-08 09:46:34	ga_ls7e_ard_3-0-0_094081_2016-10-08_final
2016-10-08 09:46:58	ga_ls7e_ard_3-0-0_094082_2016-10-08_final
2016-10-08 09:47:22	ga_ls7e_ard_3-0-0_094083_2016-10-08_final
2016-10-08 09:47:46	ga_ls7e_ard_3-0-0_094084_2016-10-08_final
2016-10-08 09:48:10	ga_ls7e_ard_3-0-0_094085_2016-10-08_final
2016-10-08 09:48:34	ga_ls7e_ard_3-0-0_094086_2016-10-08_final
2016-10-08 09:48:58	ga_ls7e_ard_3-0-0_094087_2016-10-08_final
2016-10-08 11:19:52	ga_ls7e_ard_3-0-0_110067_2016-10-08_final
2016-10-08 11:21:04	ga_ls7e_ard_3-0-0_110070_2016-10-08_final
2016-10-08 11:21:28	ga_ls7e_ard_3-0-0_110071_2016-10-08_final
2016-10-08 11:21:52	ga_ls7e_ard_3-1-0_110072_2016-10-08_final
2016-10-08 11:22:16	ga_ls7e_ard_3-0-0_110073_2016-10-08_final
2016-10-08 11:22:40	ga_ls7e_ard_3-0-0_110074_2016-10-08_final
2016-10-08 11:23:04	ga_ls7e_ard_3-0-0_110075_2016-10-08_final
2016-10-08 11:23:28	ga_ls7e_ard_3-0-0_110076_2016-10-08_final
2016-10-08 11:23:52	ga_ls7e_ard_3-0-0_110077_2016-10-08_final
2016-10-08 11:24:15	ga_ls7e_ard_3-0-0_110078_2016-10-08_final
2016-10-08 11:26:15	ga_ls7e_ard_3-0-0_110083_2016-10-08_final
2016-10-08 11:26:39	ga_ls7e_ard_3-0-0_110084_2016-10-08_final
2016-10-09 10:25:50	ga_ls7e_ard_3-0-0_101071_2016-10-09_final
2016-10-09 10:26:14	ga_ls7e_ard_3-0-0_101072_2016-10-09_final
2016-10-09 10:26:38	ga_ls7e_ard_3-0-0_101073_2016-10-09_final
2016-10-09 10:27:02	ga_ls7e_ard_3-0-0_101074_2016-10-09_final
2016-10-09 10:27:26	ga_ls7e_ard_3-1-0_101075_2016-10-09_final
2016-10-09 10:27:50	ga_ls7e_ard_3-0-0_101076_2016-10-09_final
2016-10-09 10:28:14	ga_ls7e_ard_3-0-0_101077_2016-10-09_final
2016-10-09 10:28:38	ga_ls7e_ard_3-0-0_101078_2016-10-09_final
2016-10-09 10:29:02	ga_ls7e_ard_3-0-0_101079_2016-10-09_final
2016-10-09 10:29:26	ga_ls7e_ard_3-0-0_101080_2016-10-09_final
2016-10-09 10:29:50	ga_ls7e_ard_3-0-0_101081_2016-10-09_final
2016-10-10 09:31:49	ga_ls7e_ard_3-0-0_092075_2016-10-10_final
2016-10-10 09:32:13	ga_ls7e_ard_3-0-0_092076_2016-10-10_final
2016-10-10 09:32:37	ga_ls7e_ard_3-0-0_092077_2016-10-10_final
2016-10-10 09:33:01	ga_ls7e_ard_3-0-0_092078_2016-10-10_final
2016-10-10 09:33:25	ga_ls7e_ard_3-0-0_092079_2016-10-10_final
2016-10-10 09:33:49	ga_ls7e_ard_3-0-0_092080_2016-10-10_final
2016-10-10 09:34:13	ga_ls7e_ard_3-0-0_092081_2016-10-10_final
2016-10-10 09:34:37	ga_ls7e_ard_3-0-0_092082_2016-10-10_final
2016-10-10 09:35:00	ga_ls7e_ard_3-0-0_092083_2016-10-10_final
2016-10-31 11:25:58	ga_ls7e_ard_3-0-0_111067_2016-10-31_final
2016-10-31 11:26:22	ga_ls7e_ard_3-0-0_111068_2016-10-31_final
2016-10-31 11:28:45	ga_ls7e_ard_3-0-0_111074_2016-10-31_final
2016-10-31 11:29:09	ga_ls7e_ard_3-0-0_111075_2016-10-31_final
2016-10-31 11:29:33	ga_ls7e_ard_3-0-0_111076_2016-10-31_final
2016-10-31 11:29:57	ga_ls7e_ard_3-0-0_111077_2016-10-31_final
2016-10-31 11:30:21	ga_ls7e_ard_3-0-0_111078_2016-10-31_final
2016-10-31 11:30:45	ga_ls7e_ard_3-0-0_111079_2016-10-31_final
2016-10-31 11:31:09	ga_ls7e_ard_3-0-0_111080_2016-10-31_final
2016-10-31 11:31:33	ga_ls7e_ard_3-0-0_111081_2016-10-31_final
2016-10-31 11:31:57	ga_ls7e_ard_3-1-0_111082_2016-10-31_final

Return to ga_ls7e_ard_3 across October 2016 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

2016

October

All days