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
2016-10-08 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
2016-10-10 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
2016-10-25 10:25:47	ga_ls7e_ard_3-0-0_101071_2016-10-25_final
2016-10-25 10:26:11	ga_ls7e_ard_3-0-0_101072_2016-10-25_final
2016-10-25 10:26:35	ga_ls7e_ard_3-0-0_101073_2016-10-25_final
2016-10-25 10:26:59	ga_ls7e_ard_3-0-0_101074_2016-10-25_final
2016-10-25 10:27:23	ga_ls7e_ard_3-1-0_101075_2016-10-25_final
2016-10-25 10:27:47	ga_ls7e_ard_3-0-0_101076_2016-10-25_final
2016-10-25 10:28:11	ga_ls7e_ard_3-0-0_101077_2016-10-25_final
2016-10-25 10:28:35	ga_ls7e_ard_3-0-0_101078_2016-10-25_final
2016-10-25 10:28:59	ga_ls7e_ard_3-0-0_101079_2016-10-25_final
2016-10-25 10:29:23	ga_ls7e_ard_3-0-0_101080_2016-10-25_final
2016-10-25 10:29:47	ga_ls7e_ard_3-0-0_101081_2016-10-25_final
2016-10-25 10:30:11	ga_ls7e_ard_3-0-0_101082_2016-10-25_final
2016-10-25 10:30:35	ga_ls7e_ard_3-0-0_101083_2016-10-25_final
2016-10-26 09:31:46	ga_ls7e_ard_3-0-0_092075_2016-10-26_final
2016-10-26 09:32:10	ga_ls7e_ard_3-0-0_092076_2016-10-26_final
2016-10-26 09:32:33	ga_ls7e_ard_3-0-0_092077_2016-10-26_final
2016-10-26 09:32:57	ga_ls7e_ard_3-0-0_092078_2016-10-26_final
2016-10-26 09:33:21	ga_ls7e_ard_3-0-0_092079_2016-10-26_final
2016-10-26 09:33:45	ga_ls7e_ard_3-0-0_092080_2016-10-26_final
2016-10-26 09:34:09	ga_ls7e_ard_3-0-0_092081_2016-10-26_final
2016-10-26 09:34:33	ga_ls7e_ard_3-0-0_092082_2016-10-26_final
2016-10-26 09:34:57	ga_ls7e_ard_3-0-0_092083_2016-10-26_final
2016-10-26 09:35:45	ga_ls7e_ard_3-0-0_092085_2016-10-26_final
2016-10-26 09:36:09	ga_ls7e_ard_3-0-0_092086_2016-10-26_final
2016-10-26 09:36:33	ga_ls7e_ard_3-0-0_092087_2016-10-26_final
2016-10-26 11:08:15	ga_ls7e_ard_3-0-0_108069_2016-10-26_final
2016-10-26 11:08:39	ga_ls7e_ard_3-0-0_108070_2016-10-26_final
2016-10-26 11:09:03	ga_ls7e_ard_3-0-0_108071_2016-10-26_final
2016-10-26 11:09:27	ga_ls7e_ard_3-0-0_108072_2016-10-26_final
2016-10-26 11:09:51	ga_ls7e_ard_3-0-0_108073_2016-10-26_final
2016-10-26 11:10:15	ga_ls7e_ard_3-0-0_108074_2016-10-26_final
2016-10-26 11:10:39	ga_ls7e_ard_3-1-0_108075_2016-10-26_final
2016-10-26 11:11:03	ga_ls7e_ard_3-0-0_108076_2016-10-26_final
2016-10-26 11:11:26	ga_ls7e_ard_3-0-0_108077_2016-10-26_final
2016-10-26 11:11:50	ga_ls7e_ard_3-0-0_108078_2016-10-26_final
2016-10-26 11:12:14	ga_ls7e_ard_3-0-0_108079_2016-10-26_final
2016-10-26 11:12:38	ga_ls7e_ard_3-0-0_108080_2016-10-26_final
2016-10-26 11:13:02	ga_ls7e_ard_3-0-0_108081_2016-10-26_final
2016-10-26 11:13:26	ga_ls7e_ard_3-0-0_108082_2016-10-26_final
2016-10-26 11:13:50	ga_ls7e_ard_3-0-0_108083_2016-10-26_final
2016-10-26 11:14:14	ga_ls7e_ard_3-0-0_108084_2016-10-26_final
2016-10-27 10:11:49	ga_ls7e_ard_3-0-0_099067_2016-10-27_final
2016-10-27 10:12:13	ga_ls7e_ard_3-0-0_099068_2016-10-27_final
2016-10-27 10:12:37	ga_ls7e_ard_3-0-0_099069_2016-10-27_final
2016-10-27 10:13:01	ga_ls7e_ard_3-0-0_099070_2016-10-27_final
2016-10-27 10:13:25	ga_ls7e_ard_3-0-0_099071_2016-10-27_final
2016-10-27 10:13:49	ga_ls7e_ard_3-0-0_099072_2016-10-27_final
2016-10-27 10:14:13	ga_ls7e_ard_3-0-0_099073_2016-10-27_final
2016-10-27 10:14:37	ga_ls7e_ard_3-0-0_099074_2016-10-27_final
2016-10-27 10:15:01	ga_ls7e_ard_3-0-0_099075_2016-10-27_final
2016-10-27 10:15:25	ga_ls7e_ard_3-0-0_099076_2016-10-27_final
2016-10-27 10:15:49	ga_ls7e_ard_3-0-0_099077_2016-10-27_final
2016-10-27 10:16:13	ga_ls7e_ard_3-0-0_099078_2016-10-27_final
2016-10-27 10:16:37	ga_ls7e_ard_3-0-0_099079_2016-10-27_final
2016-10-27 10:17:01	ga_ls7e_ard_3-0-0_099080_2016-10-27_final
2016-10-27 10:17:25	ga_ls7e_ard_3-0-0_099081_2016-10-27_final
2016-10-27 10:17:49	ga_ls7e_ard_3-0-0_099082_2016-10-27_final
2016-10-27 10:18:13	ga_ls7e_ard_3-0-0_099083_2016-10-27_final
2016-10-27 10:18:36	ga_ls7e_ard_3-0-0_099084_2016-10-27_final
2016-10-27 11:53:30	ga_ls7e_ard_3-0-0_115074_2016-10-27_final
2016-10-27 11:55:06	ga_ls7e_ard_3-0-0_115078_2016-10-27_final
2016-10-27 11:55:30	ga_ls7e_ard_3-0-0_115079_2016-10-27_final
2016-10-28 09:20:11	ga_ls7e_ard_3-0-0_090077_2016-10-27_final
2016-10-28 09:20:35	ga_ls7e_ard_3-0-0_090078_2016-10-27_final
2016-10-28 09:20:59	ga_ls7e_ard_3-0-0_090079_2016-10-27_final
2016-10-28 09:21:23	ga_ls7e_ard_3-0-0_090080_2016-10-27_final
2016-10-28 09:21:47	ga_ls7e_ard_3-0-0_090081_2016-10-27_final
2016-10-28 09:22:35	ga_ls7e_ard_3-0-0_090083_2016-10-27_final
2016-10-28 09:22:59	ga_ls7e_ard_3-0-0_090084_2016-10-27_final
2016-10-28 09:23:23	ga_ls7e_ard_3-1-0_090085_2016-10-27_final
2016-10-28 09:23:47	ga_ls7e_ard_3-0-0_090086_2016-10-27_final
2016-10-28 09:24:35	ga_ls7e_ard_3-0-0_090088_2016-10-27_final
2016-10-28 09:24:59	ga_ls7e_ard_3-0-0_090089_2016-10-27_final
2016-10-28 09:25:23	ga_ls7e_ard_3-0-0_090090_2016-10-27_final
2016-10-28 10:55:29	ga_ls7e_ard_3-0-0_106068_2016-10-28_final
2016-10-28 10:55:53	ga_ls7e_ard_3-0-0_106069_2016-10-28_final
2016-10-28 10:56:17	ga_ls7e_ard_3-0-0_106070_2016-10-28_final
2016-10-28 10:56:40	ga_ls7e_ard_3-0-0_106071_2016-10-28_final
2016-10-28 10:57:04	ga_ls7e_ard_3-0-0_106072_2016-10-28_final
2016-10-28 10:57:28	ga_ls7e_ard_3-0-0_106073_2016-10-28_final
2016-10-28 10:57:52	ga_ls7e_ard_3-0-0_106074_2016-10-28_final
2016-10-28 10:58:16	ga_ls7e_ard_3-1-0_106075_2016-10-28_final
2016-10-28 10:58:40	ga_ls7e_ard_3-0-0_106076_2016-10-28_final
2016-10-28 11:00:16	ga_ls7e_ard_3-0-0_106080_2016-10-28_final
2016-10-28 11:00:40	ga_ls7e_ard_3-0-0_106081_2016-10-28_final
2016-10-28 11:01:04	ga_ls7e_ard_3-0-0_106082_2016-10-28_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2016

October

All days