Search ga_ls7e_ard_3 across September 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
2016-09-03 09:14:25	ga_ls7e_ard_3-0-0_089078_2016-09-02_final
2016-09-03 09:14:48	ga_ls7e_ard_3-0-0_089079_2016-09-02_final
2016-09-03 09:15:12	ga_ls7e_ard_3-0-0_089080_2016-09-02_final
2016-09-03 09:15:36	ga_ls7e_ard_3-1-0_089081_2016-09-02_final
2016-09-03 09:16:00	ga_ls7e_ard_3-0-0_089082_2016-09-02_final
2016-09-03 09:16:24	ga_ls7e_ard_3-0-0_089083_2016-09-02_final
2016-09-03 09:16:48	ga_ls7e_ard_3-0-0_089084_2016-09-02_final
2016-09-04 09:53:17	ga_ls7e_ard_3-0-0_096067_2016-09-04_final
2016-09-04 09:54:29	ga_ls7e_ard_3-0-0_096070_2016-09-04_final
2016-09-04 09:54:53	ga_ls7e_ard_3-0-0_096071_2016-09-04_final
2016-09-04 09:55:17	ga_ls7e_ard_3-0-0_096072_2016-09-04_final
2016-09-04 09:55:41	ga_ls7e_ard_3-0-0_096073_2016-09-04_final
2016-09-04 09:56:05	ga_ls7e_ard_3-0-0_096074_2016-09-04_final
2016-09-25 10:11:52	ga_ls7e_ard_3-0-0_099067_2016-09-25_final
2016-09-25 10:12:16	ga_ls7e_ard_3-0-0_099068_2016-09-25_final
2016-09-25 10:12:40	ga_ls7e_ard_3-0-0_099069_2016-09-25_final
2016-09-25 10:13:04	ga_ls7e_ard_3-0-0_099070_2016-09-25_final
2016-09-25 10:13:28	ga_ls7e_ard_3-0-0_099071_2016-09-25_final
2016-09-25 10:13:52	ga_ls7e_ard_3-0-0_099072_2016-09-25_final
2016-09-25 10:14:16	ga_ls7e_ard_3-0-0_099073_2016-09-25_final
2016-09-25 10:14:40	ga_ls7e_ard_3-0-0_099074_2016-09-25_final
2016-09-25 10:15:04	ga_ls7e_ard_3-0-0_099075_2016-09-25_final
2016-09-25 10:15:28	ga_ls7e_ard_3-0-0_099076_2016-09-25_final
2016-09-25 10:15:52	ga_ls7e_ard_3-0-0_099077_2016-09-25_final
2016-09-25 10:16:16	ga_ls7e_ard_3-0-0_099078_2016-09-25_final
2016-09-25 10:16:40	ga_ls7e_ard_3-0-0_099079_2016-09-25_final
2016-09-25 10:17:04	ga_ls7e_ard_3-0-0_099080_2016-09-25_final
2016-09-25 10:17:27	ga_ls7e_ard_3-0-0_099081_2016-09-25_final
2016-09-25 10:17:51	ga_ls7e_ard_3-0-0_099082_2016-09-25_final
2016-09-25 10:18:15	ga_ls7e_ard_3-0-0_099083_2016-09-25_final
2016-09-25 10:18:39	ga_ls7e_ard_3-0-0_099084_2016-09-25_final
2016-09-25 11:53:33	ga_ls7e_ard_3-0-0_115074_2016-09-25_final
2016-09-25 11:53:57	ga_ls7e_ard_3-0-0_115075_2016-09-25_final
2016-09-25 11:54:21	ga_ls7e_ard_3-0-0_115076_2016-09-25_final
2016-09-25 11:54:45	ga_ls7e_ard_3-1-0_115077_2016-09-25_final
2016-09-25 11:55:09	ga_ls7e_ard_3-0-0_115078_2016-09-25_final
2016-09-25 11:55:33	ga_ls7e_ard_3-0-0_115079_2016-09-25_final
2016-09-26 09:20:15	ga_ls7e_ard_3-0-0_090077_2016-09-25_final
2016-09-26 09:20:38	ga_ls7e_ard_3-0-0_090078_2016-09-25_final
2016-09-26 09:21:02	ga_ls7e_ard_3-0-0_090079_2016-09-25_final
2016-09-26 09:21:26	ga_ls7e_ard_3-0-0_090080_2016-09-25_final
2016-09-26 09:21:50	ga_ls7e_ard_3-0-0_090081_2016-09-25_final
2016-09-26 09:22:14	ga_ls7e_ard_3-0-0_090082_2016-09-25_final
2016-09-26 09:22:38	ga_ls7e_ard_3-0-0_090083_2016-09-25_final
2016-09-26 09:23:02	ga_ls7e_ard_3-0-0_090084_2016-09-25_final
2016-09-26 09:23:26	ga_ls7e_ard_3-0-0_090085_2016-09-25_final
2016-09-26 09:23:50	ga_ls7e_ard_3-0-0_090086_2016-09-25_final
2016-09-26 09:24:38	ga_ls7e_ard_3-0-0_090088_2016-09-25_final
2016-09-26 09:25:02	ga_ls7e_ard_3-0-0_090089_2016-09-25_final
2016-09-26 09:25:26	ga_ls7e_ard_3-0-0_090090_2016-09-25_final
2016-09-26 10:55:32	ga_ls7e_ard_3-0-0_106068_2016-09-26_final
2016-09-26 10:55:56	ga_ls7e_ard_3-0-0_106069_2016-09-26_final
2016-09-26 10:56:20	ga_ls7e_ard_3-0-0_106070_2016-09-26_final
2016-09-26 10:56:44	ga_ls7e_ard_3-0-0_106071_2016-09-26_final
2016-09-26 10:57:08	ga_ls7e_ard_3-0-0_106072_2016-09-26_final
2016-09-26 10:57:32	ga_ls7e_ard_3-0-0_106073_2016-09-26_final
2016-09-26 10:57:56	ga_ls7e_ard_3-0-0_106074_2016-09-26_final
2016-09-26 10:58:20	ga_ls7e_ard_3-1-0_106075_2016-09-26_final
2016-09-26 10:58:44	ga_ls7e_ard_3-0-0_106076_2016-09-26_final
2016-09-26 10:59:31	ga_ls7e_ard_3-0-0_106078_2016-09-26_final
2016-09-26 10:59:55	ga_ls7e_ard_3-0-0_106079_2016-09-26_final
2016-09-26 11:00:19	ga_ls7e_ard_3-0-0_106080_2016-09-26_final
2016-09-26 11:00:43	ga_ls7e_ard_3-0-0_106081_2016-09-26_final
2016-09-26 11:01:07	ga_ls7e_ard_3-0-0_106082_2016-09-26_final
2016-09-26 11:01:31	ga_ls7e_ard_3-0-0_106083_2016-09-26_final
2016-09-27 10:00:19	ga_ls7e_ard_3-0-0_097069_2016-09-27_final
2016-09-27 10:00:43	ga_ls7e_ard_3-0-0_097070_2016-09-27_final
2016-09-27 10:01:07	ga_ls7e_ard_3-0-0_097071_2016-09-27_final
2016-09-27 10:01:31	ga_ls7e_ard_3-0-0_097072_2016-09-27_final
2016-09-27 10:01:55	ga_ls7e_ard_3-0-0_097073_2016-09-27_final
2016-09-27 10:02:19	ga_ls7e_ard_3-0-0_097074_2016-09-27_final
2016-09-27 10:02:42	ga_ls7e_ard_3-0-0_097075_2016-09-27_final
2016-09-27 10:03:54	ga_ls7e_ard_3-0-0_097078_2016-09-27_final
2016-09-27 10:04:18	ga_ls7e_ard_3-0-0_097079_2016-09-27_final
2016-09-27 10:04:42	ga_ls7e_ard_3-0-0_097080_2016-09-27_final
2016-09-27 10:05:06	ga_ls7e_ard_3-0-0_097081_2016-09-27_final
2016-09-27 10:05:30	ga_ls7e_ard_3-0-0_097082_2016-09-27_final
2016-09-27 10:05:54	ga_ls7e_ard_3-0-0_097083_2016-09-27_final
2016-09-27 10:06:18	ga_ls7e_ard_3-0-0_097084_2016-09-27_final
2016-09-27 10:06:42	ga_ls7e_ard_3-0-0_097085_2016-09-27_final
2016-09-27 11:38:24	ga_ls7e_ard_3-0-0_113067_2016-09-27_final
2016-09-27 11:41:12	ga_ls7e_ard_3-0-0_113074_2016-09-27_final
2016-09-27 11:41:36	ga_ls7e_ard_3-0-0_113075_2016-09-27_final
2016-09-27 11:41:59	ga_ls7e_ard_3-0-0_113076_2016-09-27_final
2016-09-27 11:42:23	ga_ls7e_ard_3-0-0_113077_2016-09-27_final
2016-09-27 11:42:47	ga_ls7e_ard_3-0-0_113078_2016-09-27_final
2016-09-27 11:43:11	ga_ls7e_ard_3-0-0_113079_2016-09-27_final
2016-09-27 11:43:35	ga_ls7e_ard_3-0-0_113080_2016-09-27_final
2016-09-27 11:43:59	ga_ls7e_ard_3-0-0_113081_2016-09-27_final
2016-09-27 11:44:23	ga_ls7e_ard_3-0-0_113082_2016-09-27_final
2016-09-28 10:43:11	ga_ls7e_ard_3-0-0_104068_2016-09-28_final
2016-09-28 10:43:35	ga_ls7e_ard_3-0-0_104069_2016-09-28_final
2016-09-28 10:43:59	ga_ls7e_ard_3-1-0_104070_2016-09-28_final
2016-09-28 10:44:23	ga_ls7e_ard_3-0-0_104071_2016-09-28_final
2016-09-28 10:44:46	ga_ls7e_ard_3-0-0_104072_2016-09-28_final
2016-09-28 10:45:10	ga_ls7e_ard_3-0-0_104073_2016-09-28_final
2016-09-28 10:45:34	ga_ls7e_ard_3-0-0_104074_2016-09-28_final
2016-09-28 10:46:46	ga_ls7e_ard_3-0-0_104077_2016-09-28_final
2016-09-28 10:47:10	ga_ls7e_ard_3-0-0_104078_2016-09-28_final
2016-09-28 10:47:34	ga_ls7e_ard_3-0-0_104079_2016-09-28_final

Return to ga_ls7e_ard_3 across September 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

September

All days