Search ga_ls7e_ard_3 across 2017

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
2017-12-03 10:06:26	ga_ls7e_ard_3-0-0_097085_2017-12-03_final
2017-12-07 09:37:17	ga_ls7e_ard_3-0-0_093074_2017-12-07_final
2017-12-07 09:37:41	ga_ls7e_ard_3-0-0_093075_2017-12-07_final
2017-12-07 09:38:05	ga_ls7e_ard_3-0-0_093076_2017-12-07_final
2017-12-07 09:38:29	ga_ls7e_ard_3-0-0_093077_2017-12-07_final
2017-12-07 09:38:53	ga_ls7e_ard_3-0-0_093078_2017-12-07_final
2017-12-07 09:39:17	ga_ls7e_ard_3-0-0_093079_2017-12-07_final
2017-12-07 09:39:41	ga_ls7e_ard_3-0-0_093080_2017-12-07_final
2017-12-07 09:40:05	ga_ls7e_ard_3-0-0_093081_2017-12-07_final
2017-12-07 09:40:29	ga_ls7e_ard_3-0-0_093082_2017-12-07_final
2017-12-07 09:40:53	ga_ls7e_ard_3-0-0_093083_2017-12-07_final
2017-12-07 09:41:17	ga_ls7e_ard_3-0-0_093084_2017-12-07_final
2017-12-07 09:41:40	ga_ls7e_ard_3-0-0_093085_2017-12-07_final
2017-12-07 09:42:04	ga_ls7e_ard_3-0-0_093086_2017-12-07_final
2017-12-07 09:42:28	ga_ls7e_ard_3-1-0_093087_2017-12-07_final
2017-12-07 09:42:52	ga_ls7e_ard_3-0-0_093088_2017-12-07_final
2017-12-08 10:19:20	ga_ls7e_ard_3-0-0_100071_2017-12-08_final
2017-12-08 10:19:44	ga_ls7e_ard_3-0-0_100072_2017-12-08_final
2017-12-08 10:20:08	ga_ls7e_ard_3-0-0_100073_2017-12-08_final
2017-12-08 10:20:32	ga_ls7e_ard_3-0-0_100074_2017-12-08_final
2017-12-08 10:20:56	ga_ls7e_ard_3-0-0_100075_2017-12-08_final
2017-12-09 09:26:06	ga_ls7e_ard_3-0-0_091077_2017-12-08_final
2017-12-09 09:26:30	ga_ls7e_ard_3-0-0_091078_2017-12-08_final
2017-12-09 09:26:54	ga_ls7e_ard_3-0-0_091079_2017-12-08_final
2017-12-09 09:27:18	ga_ls7e_ard_3-0-0_091080_2017-12-08_final
2017-12-09 09:27:42	ga_ls7e_ard_3-0-0_091081_2017-12-08_final
2017-12-09 09:28:06	ga_ls7e_ard_3-0-0_091082_2017-12-08_final
2017-12-09 09:28:30	ga_ls7e_ard_3-0-0_091083_2017-12-08_final
2017-12-09 09:28:54	ga_ls7e_ard_3-0-0_091084_2017-12-08_final
2017-12-09 09:29:18	ga_ls7e_ard_3-0-0_091085_2017-12-08_final
2017-12-09 09:29:42	ga_ls7e_ard_3-1-0_091086_2017-12-08_final
2017-12-22 10:30:22	ga_ls7e_ard_3-0-0_102068_2017-12-22_final
2017-12-22 10:30:46	ga_ls7e_ard_3-0-0_102069_2017-12-22_final
2017-12-22 10:31:09	ga_ls7e_ard_3-0-0_102070_2017-12-22_final
2017-12-22 10:31:33	ga_ls7e_ard_3-0-0_102071_2017-12-22_final
2017-12-22 10:31:57	ga_ls7e_ard_3-0-0_102072_2017-12-22_final
2017-12-22 10:32:21	ga_ls7e_ard_3-1-0_102073_2017-12-22_final
2017-12-22 10:32:45	ga_ls7e_ard_3-0-0_102074_2017-12-22_final
2017-12-22 10:33:09	ga_ls7e_ard_3-0-0_102075_2017-12-22_final
2017-12-22 10:33:33	ga_ls7e_ard_3-0-0_102076_2017-12-22_final
2017-12-22 10:33:57	ga_ls7e_ard_3-0-0_102077_2017-12-22_final
2017-12-22 10:34:21	ga_ls7e_ard_3-0-0_102078_2017-12-22_final
2017-12-22 10:34:45	ga_ls7e_ard_3-0-0_102079_2017-12-22_final
2017-12-22 10:35:09	ga_ls7e_ard_3-0-0_102080_2017-12-22_final
2017-12-22 10:35:33	ga_ls7e_ard_3-0-0_102081_2017-12-22_final
2017-12-22 10:35:57	ga_ls7e_ard_3-0-0_102082_2017-12-22_final
2017-12-23 09:37:07	ga_ls7e_ard_3-0-0_093074_2017-12-23_final
2017-12-23 09:37:31	ga_ls7e_ard_3-0-0_093075_2017-12-23_final
2017-12-23 09:37:55	ga_ls7e_ard_3-0-0_093076_2017-12-23_final
2017-12-23 09:38:19	ga_ls7e_ard_3-0-0_093077_2017-12-23_final
2017-12-23 09:38:43	ga_ls7e_ard_3-0-0_093078_2017-12-23_final
2017-12-23 09:39:07	ga_ls7e_ard_3-0-0_093079_2017-12-23_final
2017-12-23 09:39:31	ga_ls7e_ard_3-0-0_093080_2017-12-23_final
2017-12-23 09:39:55	ga_ls7e_ard_3-0-0_093081_2017-12-23_final
2017-12-23 09:40:19	ga_ls7e_ard_3-0-0_093082_2017-12-23_final
2017-12-23 09:40:43	ga_ls7e_ard_3-0-0_093083_2017-12-23_final
2017-12-23 09:41:07	ga_ls7e_ard_3-0-0_093084_2017-12-23_final
2017-12-23 09:41:31	ga_ls7e_ard_3-0-0_093085_2017-12-23_final
2017-12-23 09:41:55	ga_ls7e_ard_3-0-0_093086_2017-12-23_final
2017-12-23 09:42:18	ga_ls7e_ard_3-1-0_093087_2017-12-23_final
2017-12-23 11:14:24	ga_ls7e_ard_3-0-0_109070_2017-12-23_final
2017-12-23 11:14:48	ga_ls7e_ard_3-0-0_109071_2017-12-23_final
2017-12-23 11:15:12	ga_ls7e_ard_3-0-0_109072_2017-12-23_final
2017-12-23 11:15:36	ga_ls7e_ard_3-0-0_109073_2017-12-23_final
2017-12-23 11:16:00	ga_ls7e_ard_3-0-0_109074_2017-12-23_final
2017-12-23 11:16:24	ga_ls7e_ard_3-0-0_109075_2017-12-23_final
2017-12-23 11:16:48	ga_ls7e_ard_3-0-0_109076_2017-12-23_final
2017-12-23 11:17:12	ga_ls7e_ard_3-0-0_109077_2017-12-23_final
2017-12-23 11:17:36	ga_ls7e_ard_3-0-0_109078_2017-12-23_final
2017-12-23 11:18:00	ga_ls7e_ard_3-0-0_109079_2017-12-23_final
2017-12-23 11:18:48	ga_ls7e_ard_3-1-0_109081_2017-12-23_final
2017-12-23 11:19:12	ga_ls7e_ard_3-0-0_109082_2017-12-23_final
2017-12-23 11:19:36	ga_ls7e_ard_3-0-0_109083_2017-12-23_final
2017-12-24 10:19:10	ga_ls7e_ard_3-0-0_100071_2017-12-24_final
2017-12-24 10:19:34	ga_ls7e_ard_3-0-0_100072_2017-12-24_final
2017-12-24 10:19:58	ga_ls7e_ard_3-0-0_100073_2017-12-24_final
2017-12-24 10:20:22	ga_ls7e_ard_3-0-0_100074_2017-12-24_final
2017-12-24 10:20:46	ga_ls7e_ard_3-0-0_100075_2017-12-24_final
2017-12-24 10:21:10	ga_ls7e_ard_3-0-0_100076_2017-12-24_final
2017-12-24 10:21:34	ga_ls7e_ard_3-0-0_100077_2017-12-24_final
2017-12-24 10:21:58	ga_ls7e_ard_3-0-0_100078_2017-12-24_final
2017-12-24 10:22:22	ga_ls7e_ard_3-0-0_100079_2017-12-24_final
2017-12-24 10:22:46	ga_ls7e_ard_3-0-0_100080_2017-12-24_final
2017-12-24 10:23:10	ga_ls7e_ard_3-0-0_100081_2017-12-24_final
2017-12-24 10:23:34	ga_ls7e_ard_3-0-0_100082_2017-12-24_final
2017-12-24 10:23:58	ga_ls7e_ard_3-0-0_100083_2017-12-24_final
2017-12-24 10:24:22	ga_ls7e_ard_3-0-0_100084_2017-12-24_final
2017-12-25 11:02:01	ga_ls7e_ard_3-0-0_107070_2017-12-25_final
2017-12-25 11:02:25	ga_ls7e_ard_3-0-0_107071_2017-12-25_final
2017-12-25 11:02:49	ga_ls7e_ard_3-0-0_107072_2017-12-25_final
2017-12-25 11:03:13	ga_ls7e_ard_3-0-0_107073_2017-12-25_final
2017-12-25 11:03:37	ga_ls7e_ard_3-0-0_107074_2017-12-25_final
2017-12-25 11:04:01	ga_ls7e_ard_3-0-0_107075_2017-12-25_final
2017-12-25 11:04:25	ga_ls7e_ard_3-0-0_107076_2017-12-25_final
2017-12-25 11:04:49	ga_ls7e_ard_3-0-0_107077_2017-12-25_final
2017-12-25 11:05:13	ga_ls7e_ard_3-0-0_107078_2017-12-25_final
2017-12-25 11:06:01	ga_ls7e_ard_3-0-0_107080_2017-12-25_final
2017-12-25 11:06:25	ga_ls7e_ard_3-0-0_107081_2017-12-25_final
2017-12-25 11:06:49	ga_ls7e_ard_3-0-0_107082_2017-12-25_final
2017-12-25 11:07:13	ga_ls7e_ard_3-0-0_107083_2017-12-25_final

Return to ga_ls7e_ard_3 across 2017 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

2017

All months