Search ga_ls7e_ard_3 across 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
2016-10-28 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
2016-12-23 10:05:20	ga_ls7e_ard_3-0-0_098067_2016-12-23_final
2016-12-23 10:05:44	ga_ls7e_ard_3-0-0_098068_2016-12-23_final
2016-12-23 10:06:08	ga_ls7e_ard_3-0-0_098069_2016-12-23_final
2016-12-23 10:06:32	ga_ls7e_ard_3-0-0_098070_2016-12-23_final
2016-12-23 10:06:56	ga_ls7e_ard_3-0-0_098071_2016-12-23_final
2016-12-23 10:07:20	ga_ls7e_ard_3-0-0_098072_2016-12-23_final
2016-12-23 10:07:44	ga_ls7e_ard_3-0-0_098073_2016-12-23_final
2016-12-23 10:09:19	ga_ls7e_ard_3-0-0_098077_2016-12-23_final
2016-12-23 10:09:43	ga_ls7e_ard_3-0-0_098078_2016-12-23_final
2016-12-23 10:10:07	ga_ls7e_ard_3-0-0_098079_2016-12-23_final
2016-12-23 10:10:31	ga_ls7e_ard_3-0-0_098080_2016-12-23_final
2016-12-23 10:10:55	ga_ls7e_ard_3-0-0_098081_2016-12-23_final
2016-12-23 10:11:19	ga_ls7e_ard_3-0-0_098082_2016-12-23_final
2016-12-23 10:11:43	ga_ls7e_ard_3-0-0_098083_2016-12-23_final
2016-12-23 10:12:07	ga_ls7e_ard_3-0-0_098084_2016-12-23_final
2016-12-23 10:12:31	ga_ls7e_ard_3-0-0_098085_2016-12-23_final
2016-12-23 11:47:01	ga_ls7e_ard_3-0-0_114074_2016-12-23_final
2016-12-23 11:47:25	ga_ls7e_ard_3-0-0_114075_2016-12-23_final
2016-12-23 11:47:48	ga_ls7e_ard_3-0-0_114076_2016-12-23_final
2016-12-23 11:48:12	ga_ls7e_ard_3-0-0_114077_2016-12-23_final
2016-12-23 11:48:36	ga_ls7e_ard_3-0-0_114078_2016-12-23_final
2016-12-23 11:49:00	ga_ls7e_ard_3-0-0_114079_2016-12-23_final
2016-12-23 11:49:24	ga_ls7e_ard_3-0-0_114080_2016-12-23_final
2016-12-24 09:13:42	ga_ls7e_ard_3-0-0_089077_2016-12-23_final
2016-12-24 09:14:06	ga_ls7e_ard_3-0-0_089078_2016-12-23_final
2016-12-24 09:14:30	ga_ls7e_ard_3-0-0_089079_2016-12-23_final
2016-12-24 09:14:53	ga_ls7e_ard_3-0-0_089080_2016-12-23_final
2016-12-24 09:15:17	ga_ls7e_ard_3-1-0_089081_2016-12-23_final
2016-12-24 09:15:41	ga_ls7e_ard_3-0-0_089082_2016-12-23_final
2016-12-24 09:16:05	ga_ls7e_ard_3-0-0_089083_2016-12-23_final
2016-12-24 09:16:29	ga_ls7e_ard_3-0-0_089084_2016-12-23_final
2016-12-24 09:16:53	ga_ls7e_ard_3-0-0_089085_2016-12-23_final
2016-12-24 09:17:17	ga_ls7e_ard_3-0-0_089086_2016-12-23_final
2016-12-24 10:48:59	ga_ls7e_ard_3-0-0_105068_2016-12-24_final
2016-12-24 10:49:23	ga_ls7e_ard_3-0-0_105069_2016-12-24_final
2016-12-24 10:53:46	ga_ls7e_ard_3-1-0_105080_2016-12-24_final
2016-12-24 10:54:10	ga_ls7e_ard_3-0-0_105081_2016-12-24_final
2016-12-24 10:54:34	ga_ls7e_ard_3-0-0_105082_2016-12-24_final
2016-12-25 09:52:57	ga_ls7e_ard_3-0-0_096067_2016-12-25_final
2016-12-25 09:54:09	ga_ls7e_ard_3-0-0_096070_2016-12-25_final
2016-12-25 09:54:33	ga_ls7e_ard_3-0-0_096071_2016-12-25_final
2016-12-25 09:55:45	ga_ls7e_ard_3-0-0_096074_2016-12-25_final
2016-12-25 09:56:09	ga_ls7e_ard_3-0-0_096075_2016-12-25_final
2016-12-25 09:56:33	ga_ls7e_ard_3-0-0_096076_2016-12-25_final
2016-12-25 09:56:57	ga_ls7e_ard_3-0-0_096077_2016-12-25_final
2016-12-25 09:57:21	ga_ls7e_ard_3-0-0_096078_2016-12-25_final
2016-12-25 09:57:45	ga_ls7e_ard_3-0-0_096079_2016-12-25_final
2016-12-25 09:58:09	ga_ls7e_ard_3-0-0_096080_2016-12-25_final
2016-12-25 09:58:33	ga_ls7e_ard_3-0-0_096081_2016-12-25_final
2016-12-25 09:58:57	ga_ls7e_ard_3-0-0_096082_2016-12-25_final
2016-12-25 09:59:20	ga_ls7e_ard_3-0-0_096083_2016-12-25_final
2016-12-25 09:59:44	ga_ls7e_ard_3-0-0_096084_2016-12-25_final
2016-12-25 10:00:08	ga_ls7e_ard_3-0-0_096085_2016-12-25_final
2016-12-25 10:00:32	ga_ls7e_ard_3-1-0_096086_2016-12-25_final
2016-12-25 11:31:51	ga_ls7e_ard_3-0-0_112067_2016-12-25_final
2016-12-25 11:34:38	ga_ls7e_ard_3-0-0_112074_2016-12-25_final
2016-12-25 11:35:02	ga_ls7e_ard_3-0-0_112075_2016-12-25_final
2016-12-25 11:35:26	ga_ls7e_ard_3-0-0_112076_2016-12-25_final
2016-12-25 11:35:50	ga_ls7e_ard_3-0-0_112077_2016-12-25_final
2016-12-25 11:36:14	ga_ls7e_ard_3-0-0_112078_2016-12-25_final
2016-12-25 11:36:38	ga_ls7e_ard_3-0-0_112079_2016-12-25_final
2016-12-25 11:37:02	ga_ls7e_ard_3-0-0_112080_2016-12-25_final
2016-12-25 11:37:26	ga_ls7e_ard_3-0-0_112081_2016-12-25_final
2016-12-25 11:37:50	ga_ls7e_ard_3-0-0_112082_2016-12-25_final
2016-12-25 11:38:14	ga_ls7e_ard_3-0-0_112083_2016-12-25_final
2016-12-25 11:38:37	ga_ls7e_ard_3-1-0_112084_2016-12-25_final
2016-12-26 10:36:37	ga_ls7e_ard_3-0-0_103068_2016-12-26_final
2016-12-26 10:37:01	ga_ls7e_ard_3-0-0_103069_2016-12-26_final
2016-12-27 09:42:58	ga_ls7e_ard_3-0-0_094073_2016-12-27_final
2016-12-27 09:43:22	ga_ls7e_ard_3-0-0_094074_2016-12-27_final
2016-12-27 09:43:46	ga_ls7e_ard_3-0-0_094075_2016-12-27_final
2016-12-27 09:44:10	ga_ls7e_ard_3-0-0_094076_2016-12-27_final
2016-12-27 09:44:34	ga_ls7e_ard_3-0-0_094077_2016-12-27_final
2016-12-27 09:44:58	ga_ls7e_ard_3-0-0_094078_2016-12-27_final
2016-12-27 09:45:22	ga_ls7e_ard_3-0-0_094079_2016-12-27_final
2016-12-27 09:45:46	ga_ls7e_ard_3-0-0_094080_2016-12-27_final
2016-12-27 09:46:10	ga_ls7e_ard_3-0-0_094081_2016-12-27_final
2016-12-27 09:46:34	ga_ls7e_ard_3-0-0_094082_2016-12-27_final
2016-12-27 09:46:58	ga_ls7e_ard_3-1-0_094083_2016-12-27_final
2016-12-27 09:47:22	ga_ls7e_ard_3-0-0_094084_2016-12-27_final
2016-12-27 11:19:28	ga_ls7e_ard_3-0-0_110067_2016-12-27_final
2016-12-27 11:21:51	ga_ls7e_ard_3-0-0_110073_2016-12-27_final
2016-12-27 11:22:39	ga_ls7e_ard_3-1-0_110075_2016-12-27_final
2016-12-27 11:23:03	ga_ls7e_ard_3-0-0_110076_2016-12-27_final
2016-12-27 11:23:27	ga_ls7e_ard_3-0-0_110077_2016-12-27_final
2016-12-27 11:23:51	ga_ls7e_ard_3-0-0_110078_2016-12-27_final
2016-12-27 11:24:15	ga_ls7e_ard_3-0-0_110079_2016-12-27_final
2016-12-27 11:24:39	ga_ls7e_ard_3-0-0_110080_2016-12-27_final
2016-12-27 11:25:03	ga_ls7e_ard_3-0-0_110081_2016-12-27_final
2016-12-27 11:25:27	ga_ls7e_ard_3-0-0_110082_2016-12-27_final

Return to ga_ls7e_ard_3 across 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

All months