Search ga_ls7e_ard_3 across December 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
2017-12-02 09:19:59	ga_ls7e_ard_3-0-0_090077_2017-12-01_final
2017-12-02 09:20:47	ga_ls7e_ard_3-0-0_090079_2017-12-01_final
2017-12-03 10:00:03	ga_ls7e_ard_3-0-0_097069_2017-12-03_final
2017-12-03 10:00:27	ga_ls7e_ard_3-0-0_097070_2017-12-03_final
2017-12-03 10:00:51	ga_ls7e_ard_3-0-0_097071_2017-12-03_final
2017-12-03 10:01:15	ga_ls7e_ard_3-0-0_097072_2017-12-03_final
2017-12-03 10:01:38	ga_ls7e_ard_3-0-0_097073_2017-12-03_final
2017-12-09 09:30:30	ga_ls7e_ard_3-0-0_091088_2017-12-09_final
2017-12-09 09:30:54	ga_ls7e_ard_3-0-0_091089_2017-12-09_final
2017-12-09 11:02:12	ga_ls7e_ard_3-0-0_107070_2017-12-09_final
2017-12-09 11:02:36	ga_ls7e_ard_3-0-0_107071_2017-12-09_final
2017-12-09 11:02:59	ga_ls7e_ard_3-0-0_107072_2017-12-09_final
2017-12-09 11:03:23	ga_ls7e_ard_3-0-0_107073_2017-12-09_final
2017-12-09 11:03:47	ga_ls7e_ard_3-0-0_107074_2017-12-09_final
2017-12-09 11:04:11	ga_ls7e_ard_3-0-0_107075_2017-12-09_final
2017-12-09 11:04:35	ga_ls7e_ard_3-0-0_107076_2017-12-09_final
2017-12-09 11:04:59	ga_ls7e_ard_3-0-0_107077_2017-12-09_final
2017-12-09 11:05:23	ga_ls7e_ard_3-0-0_107078_2017-12-09_final
2017-12-09 11:05:47	ga_ls7e_ard_3-0-0_107079_2017-12-09_final
2017-12-09 11:06:11	ga_ls7e_ard_3-0-0_107080_2017-12-09_final
2017-12-09 11:06:35	ga_ls7e_ard_3-0-0_107081_2017-12-09_final
2017-12-09 11:06:59	ga_ls7e_ard_3-0-0_107082_2017-12-09_final
2017-12-09 11:07:23	ga_ls7e_ard_3-0-0_107083_2017-12-09_final
2017-12-09 11:07:47	ga_ls7e_ard_3-0-0_107084_2017-12-09_final
2017-12-10 10:05:22	ga_ls7e_ard_3-0-0_098067_2017-12-10_final
2017-12-10 10:05:46	ga_ls7e_ard_3-0-0_098068_2017-12-10_final
2017-12-10 10:06:10	ga_ls7e_ard_3-0-0_098069_2017-12-10_final
2017-12-10 10:06:34	ga_ls7e_ard_3-0-0_098070_2017-12-10_final
2017-12-10 10:06:58	ga_ls7e_ard_3-0-0_098071_2017-12-10_final
2017-12-10 10:07:22	ga_ls7e_ard_3-0-0_098072_2017-12-10_final
2017-12-10 10:07:46	ga_ls7e_ard_3-0-0_098073_2017-12-10_final
2017-12-10 10:08:09	ga_ls7e_ard_3-0-0_098074_2017-12-10_final
2017-12-10 10:08:33	ga_ls7e_ard_3-0-0_098075_2017-12-10_final
2017-12-10 10:08:57	ga_ls7e_ard_3-0-0_098076_2017-12-10_final
2017-12-10 10:09:21	ga_ls7e_ard_3-0-0_098077_2017-12-10_final
2017-12-10 10:09:45	ga_ls7e_ard_3-0-0_098078_2017-12-10_final
2017-12-10 10:10:09	ga_ls7e_ard_3-0-0_098079_2017-12-10_final
2017-12-10 10:10:33	ga_ls7e_ard_3-1-0_098080_2017-12-10_final
2017-12-10 10:10:57	ga_ls7e_ard_3-0-0_098081_2017-12-10_final
2017-12-10 10:11:21	ga_ls7e_ard_3-0-0_098082_2017-12-10_final
2017-12-10 10:11:45	ga_ls7e_ard_3-0-0_098083_2017-12-10_final
2017-12-10 10:12:09	ga_ls7e_ard_3-0-0_098084_2017-12-10_final
2017-12-10 10:12:33	ga_ls7e_ard_3-0-0_098085_2017-12-10_final
2017-12-10 11:47:03	ga_ls7e_ard_3-0-0_114074_2017-12-10_final
2017-12-10 11:47:26	ga_ls7e_ard_3-0-0_114075_2017-12-10_final
2017-12-10 11:47:50	ga_ls7e_ard_3-0-0_114076_2017-12-10_final
2017-12-10 11:48:14	ga_ls7e_ard_3-0-0_114077_2017-12-10_final
2017-12-10 11:48:38	ga_ls7e_ard_3-0-0_114078_2017-12-10_final
2017-12-10 11:49:02	ga_ls7e_ard_3-0-0_114079_2017-12-10_final
2017-12-10 11:49:26	ga_ls7e_ard_3-0-0_114080_2017-12-10_final
2017-12-11 09:14:07	ga_ls7e_ard_3-0-0_089078_2017-12-10_final
2017-12-11 09:14:31	ga_ls7e_ard_3-0-0_089079_2017-12-10_final
2017-12-11 09:14:55	ga_ls7e_ard_3-0-0_089080_2017-12-10_final
2017-12-11 09:15:19	ga_ls7e_ard_3-1-0_089081_2017-12-10_final
2017-12-11 09:15:43	ga_ls7e_ard_3-0-0_089082_2017-12-10_final
2017-12-11 09:16:07	ga_ls7e_ard_3-0-0_089083_2017-12-10_final
2017-12-11 09:16:31	ga_ls7e_ard_3-0-0_089084_2017-12-10_final
2017-12-11 09:16:55	ga_ls7e_ard_3-0-0_089085_2017-12-10_final
2017-12-11 10:49:01	ga_ls7e_ard_3-0-0_105068_2017-12-11_final
2017-12-11 10:49:25	ga_ls7e_ard_3-0-0_105069_2017-12-11_final
2017-12-11 10:49:49	ga_ls7e_ard_3-0-0_105070_2017-12-11_final
2017-12-11 10:50:13	ga_ls7e_ard_3-0-0_105071_2017-12-11_final
2017-12-11 10:50:37	ga_ls7e_ard_3-0-0_105072_2017-12-11_final
2017-12-11 10:51:01	ga_ls7e_ard_3-0-0_105073_2017-12-11_final
2017-12-11 10:51:25	ga_ls7e_ard_3-0-0_105074_2017-12-11_final
2017-12-11 10:51:48	ga_ls7e_ard_3-0-0_105075_2017-12-11_final
2017-12-11 10:52:12	ga_ls7e_ard_3-0-0_105076_2017-12-11_final
2017-12-11 10:52:36	ga_ls7e_ard_3-0-0_105077_2017-12-11_final
2017-12-11 10:53:00	ga_ls7e_ard_3-0-0_105078_2017-12-11_final
2017-12-11 10:53:24	ga_ls7e_ard_3-0-0_105079_2017-12-11_final
2017-12-11 10:53:48	ga_ls7e_ard_3-1-0_105080_2017-12-11_final
2017-12-11 10:54:36	ga_ls7e_ard_3-0-0_105082_2017-12-11_final
2017-12-12 09:54:11	ga_ls7e_ard_3-0-0_096070_2017-12-12_final
2017-12-12 09:54:35	ga_ls7e_ard_3-0-0_096071_2017-12-12_final
2017-12-12 09:54:59	ga_ls7e_ard_3-0-0_096072_2017-12-12_final
2017-12-12 09:55:23	ga_ls7e_ard_3-0-0_096073_2017-12-12_final
2017-12-12 09:55:47	ga_ls7e_ard_3-0-0_096074_2017-12-12_final
2017-12-12 09:56:11	ga_ls7e_ard_3-0-0_096075_2017-12-12_final
2017-12-12 09:56:35	ga_ls7e_ard_3-0-0_096076_2017-12-12_final
2017-12-12 09:56:58	ga_ls7e_ard_3-0-0_096077_2017-12-12_final
2017-12-12 09:57:22	ga_ls7e_ard_3-0-0_096078_2017-12-12_final
2017-12-12 09:57:46	ga_ls7e_ard_3-0-0_096079_2017-12-12_final
2017-12-12 09:58:10	ga_ls7e_ard_3-0-0_096080_2017-12-12_final
2017-12-12 09:58:34	ga_ls7e_ard_3-0-0_096081_2017-12-12_final
2017-12-12 09:58:58	ga_ls7e_ard_3-0-0_096082_2017-12-12_final
2017-12-12 09:59:22	ga_ls7e_ard_3-0-0_096083_2017-12-12_final
2017-12-12 09:59:46	ga_ls7e_ard_3-0-0_096084_2017-12-12_final
2017-12-12 10:00:10	ga_ls7e_ard_3-0-0_096085_2017-12-12_final
2017-12-12 10:00:34	ga_ls7e_ard_3-1-0_096086_2017-12-12_final
2017-12-12 11:31:52	ga_ls7e_ard_3-0-0_112067_2017-12-12_final
2017-12-12 11:34:40	ga_ls7e_ard_3-0-0_112074_2017-12-12_final
2017-12-12 11:35:04	ga_ls7e_ard_3-0-0_112075_2017-12-12_final
2017-12-12 11:35:28	ga_ls7e_ard_3-0-0_112076_2017-12-12_final
2017-12-12 11:35:52	ga_ls7e_ard_3-1-0_112077_2017-12-12_final
2017-12-12 11:36:15	ga_ls7e_ard_3-0-0_112078_2017-12-12_final
2017-12-12 11:36:39	ga_ls7e_ard_3-0-0_112079_2017-12-12_final
2017-12-12 11:37:03	ga_ls7e_ard_3-0-0_112080_2017-12-12_final
2017-12-12 11:37:27	ga_ls7e_ard_3-0-0_112081_2017-12-12_final
2017-12-12 11:37:51	ga_ls7e_ard_3-0-0_112082_2017-12-12_final
2017-12-12 11:38:15	ga_ls7e_ard_3-0-0_112083_2017-12-12_final

Return to ga_ls7e_ard_3 across December 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

December

All days