Search ga_ls7e_ard_3 across February 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
2016-02-01 10:42:14	ga_ls7e_ard_3-0-0_104068_2016-02-01_final
2016-02-01 10:42:38	ga_ls7e_ard_3-0-0_104069_2016-02-01_final
2016-02-01 10:45:02	ga_ls7e_ard_3-0-0_104075_2016-02-01_final
2016-02-01 10:45:26	ga_ls7e_ard_3-0-0_104076_2016-02-01_final
2016-02-01 10:45:49	ga_ls7e_ard_3-0-0_104077_2016-02-01_final
2016-02-01 10:46:13	ga_ls7e_ard_3-0-0_104078_2016-02-01_final
2016-02-01 10:47:01	ga_ls7e_ard_3-0-0_104080_2016-02-01_final
2016-02-12 10:24:57	ga_ls7e_ard_3-0-0_101071_2016-02-12_final
2016-02-12 10:25:21	ga_ls7e_ard_3-0-0_101072_2016-02-12_final
2016-02-12 10:25:45	ga_ls7e_ard_3-0-0_101073_2016-02-12_final
2016-02-12 10:26:09	ga_ls7e_ard_3-0-0_101074_2016-02-12_final
2016-02-12 10:26:33	ga_ls7e_ard_3-1-0_101075_2016-02-12_final
2016-02-12 10:26:57	ga_ls7e_ard_3-0-0_101076_2016-02-12_final
2016-02-12 10:27:21	ga_ls7e_ard_3-0-0_101077_2016-02-12_final
2016-02-12 10:27:45	ga_ls7e_ard_3-0-0_101078_2016-02-12_final
2016-02-12 10:28:09	ga_ls7e_ard_3-0-0_101079_2016-02-12_final
2016-02-12 10:28:33	ga_ls7e_ard_3-0-0_101080_2016-02-12_final
2016-02-12 10:28:57	ga_ls7e_ard_3-0-0_101081_2016-02-12_final
2016-02-12 10:29:21	ga_ls7e_ard_3-0-0_101082_2016-02-12_final
2016-02-12 10:29:44	ga_ls7e_ard_3-0-0_101083_2016-02-12_final
2016-02-13 09:30:56	ga_ls7e_ard_3-0-0_092075_2016-02-13_final
2016-02-13 09:31:20	ga_ls7e_ard_3-0-0_092076_2016-02-13_final
2016-02-13 09:31:44	ga_ls7e_ard_3-0-0_092077_2016-02-13_final
2016-02-13 09:32:08	ga_ls7e_ard_3-0-0_092078_2016-02-13_final
2016-02-13 09:32:31	ga_ls7e_ard_3-0-0_092079_2016-02-13_final
2016-02-13 09:32:55	ga_ls7e_ard_3-0-0_092080_2016-02-13_final
2016-02-13 09:33:19	ga_ls7e_ard_3-0-0_092081_2016-02-13_final
2016-02-13 09:33:43	ga_ls7e_ard_3-0-0_092082_2016-02-13_final
2016-02-13 09:34:07	ga_ls7e_ard_3-0-0_092083_2016-02-13_final
2016-02-13 09:34:31	ga_ls7e_ard_3-0-0_092084_2016-02-13_final
2016-02-13 09:34:55	ga_ls7e_ard_3-0-0_092085_2016-02-13_final
2016-02-13 09:35:19	ga_ls7e_ard_3-0-0_092086_2016-02-13_final
2016-02-13 09:35:43	ga_ls7e_ard_3-0-0_092087_2016-02-13_final
2016-02-13 09:36:07	ga_ls7e_ard_3-0-0_092088_2016-02-13_final
2016-02-13 09:36:31	ga_ls7e_ard_3-0-0_092089_2016-02-13_final
2016-02-13 11:07:25	ga_ls7e_ard_3-0-0_108069_2016-02-13_final
2016-02-13 11:07:49	ga_ls7e_ard_3-0-0_108070_2016-02-13_final
2016-02-13 11:08:13	ga_ls7e_ard_3-1-0_108071_2016-02-13_final
2016-02-13 11:08:37	ga_ls7e_ard_3-0-0_108072_2016-02-13_final
2016-02-13 11:09:01	ga_ls7e_ard_3-0-0_108073_2016-02-13_final
2016-02-13 11:09:25	ga_ls7e_ard_3-0-0_108074_2016-02-13_final
2016-02-13 11:09:49	ga_ls7e_ard_3-1-0_108075_2016-02-13_final
2016-02-13 11:10:13	ga_ls7e_ard_3-0-0_108076_2016-02-13_final
2016-02-13 11:10:37	ga_ls7e_ard_3-0-0_108077_2016-02-13_final
2016-02-13 11:11:01	ga_ls7e_ard_3-0-0_108078_2016-02-13_final
2016-02-13 11:11:25	ga_ls7e_ard_3-0-0_108079_2016-02-13_final
2016-02-13 11:11:48	ga_ls7e_ard_3-0-0_108080_2016-02-13_final
2016-02-13 11:12:12	ga_ls7e_ard_3-0-0_108081_2016-02-13_final
2016-02-13 11:12:36	ga_ls7e_ard_3-0-0_108082_2016-02-13_final
2016-02-13 11:13:00	ga_ls7e_ard_3-0-0_108083_2016-02-13_final
2016-02-13 11:13:24	ga_ls7e_ard_3-0-0_108084_2016-02-13_final
2016-02-14 10:11:00	ga_ls7e_ard_3-0-0_099067_2016-02-14_final
2016-02-14 10:11:24	ga_ls7e_ard_3-0-0_099068_2016-02-14_final
2016-02-14 10:11:48	ga_ls7e_ard_3-0-0_099069_2016-02-14_final
2016-02-14 10:12:12	ga_ls7e_ard_3-0-0_099070_2016-02-14_final
2016-02-14 10:12:36	ga_ls7e_ard_3-0-0_099071_2016-02-14_final
2016-02-14 10:13:00	ga_ls7e_ard_3-0-0_099072_2016-02-14_final
2016-02-14 10:13:24	ga_ls7e_ard_3-0-0_099073_2016-02-14_final
2016-02-14 10:13:48	ga_ls7e_ard_3-0-0_099074_2016-02-14_final
2016-02-14 10:14:12	ga_ls7e_ard_3-0-0_099075_2016-02-14_final
2016-02-14 10:14:35	ga_ls7e_ard_3-0-0_099076_2016-02-14_final
2016-02-14 10:14:59	ga_ls7e_ard_3-0-0_099077_2016-02-14_final
2016-02-14 10:15:23	ga_ls7e_ard_3-0-0_099078_2016-02-14_final
2016-02-14 10:15:47	ga_ls7e_ard_3-0-0_099079_2016-02-14_final
2016-02-14 10:16:11	ga_ls7e_ard_3-0-0_099080_2016-02-14_final
2016-02-14 10:16:35	ga_ls7e_ard_3-0-0_099081_2016-02-14_final
2016-02-14 10:16:59	ga_ls7e_ard_3-0-0_099082_2016-02-14_final
2016-02-14 10:17:23	ga_ls7e_ard_3-0-0_099083_2016-02-14_final
2016-02-14 10:17:47	ga_ls7e_ard_3-0-0_099084_2016-02-14_final
2016-02-14 11:52:41	ga_ls7e_ard_3-0-0_115074_2016-02-14_final
2016-02-14 11:53:05	ga_ls7e_ard_3-0-0_115075_2016-02-14_final
2016-02-14 11:53:29	ga_ls7e_ard_3-0-0_115076_2016-02-14_final
2016-02-14 11:53:53	ga_ls7e_ard_3-1-0_115077_2016-02-14_final
2016-02-14 11:54:16	ga_ls7e_ard_3-0-0_115078_2016-02-14_final
2016-02-14 11:54:40	ga_ls7e_ard_3-0-0_115079_2016-02-14_final
2016-02-15 09:19:22	ga_ls7e_ard_3-0-0_090077_2016-02-14_final
2016-02-15 09:19:46	ga_ls7e_ard_3-0-0_090078_2016-02-14_final
2016-02-15 09:20:10	ga_ls7e_ard_3-0-0_090079_2016-02-14_final
2016-02-15 09:20:34	ga_ls7e_ard_3-0-0_090080_2016-02-14_final
2016-02-15 09:20:58	ga_ls7e_ard_3-0-0_090081_2016-02-14_final
2016-02-15 09:21:22	ga_ls7e_ard_3-1-0_090082_2016-02-14_final
2016-02-15 09:21:46	ga_ls7e_ard_3-0-0_090083_2016-02-14_final
2016-02-15 09:22:10	ga_ls7e_ard_3-0-0_090084_2016-02-14_final
2016-02-15 09:22:34	ga_ls7e_ard_3-1-0_090085_2016-02-14_final
2016-02-15 09:22:58	ga_ls7e_ard_3-0-0_090086_2016-02-14_final
2016-02-15 09:23:46	ga_ls7e_ard_3-0-0_090088_2016-02-14_final
2016-02-15 09:24:10	ga_ls7e_ard_3-0-0_090089_2016-02-14_final
2016-02-15 10:54:40	ga_ls7e_ard_3-0-0_106068_2016-02-15_final
2016-02-15 10:55:04	ga_ls7e_ard_3-0-0_106069_2016-02-15_final
2016-02-15 10:55:28	ga_ls7e_ard_3-0-0_106070_2016-02-15_final
2016-02-15 10:55:52	ga_ls7e_ard_3-0-0_106071_2016-02-15_final
2016-02-15 10:56:16	ga_ls7e_ard_3-0-0_106072_2016-02-15_final
2016-02-15 10:56:39	ga_ls7e_ard_3-0-0_106073_2016-02-15_final
2016-02-15 10:57:03	ga_ls7e_ard_3-0-0_106074_2016-02-15_final
2016-02-15 10:57:27	ga_ls7e_ard_3-1-0_106075_2016-02-15_final
2016-02-15 10:57:51	ga_ls7e_ard_3-0-0_106076_2016-02-15_final
2016-02-15 10:58:15	ga_ls7e_ard_3-0-0_106077_2016-02-15_final
2016-02-15 10:58:39	ga_ls7e_ard_3-0-0_106078_2016-02-15_final
2016-02-15 10:59:03	ga_ls7e_ard_3-0-0_106079_2016-02-15_final
2016-02-15 10:59:27	ga_ls7e_ard_3-0-0_106080_2016-02-15_final

Return to ga_ls7e_ard_3 across February 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

February

All days