Search ga_ls7e_ard_3 across October 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
2017-10-12 10:25:43	ga_ls7e_ard_3-0-0_101071_2017-10-12_final
2017-10-12 10:26:06	ga_ls7e_ard_3-1-0_101072_2017-10-12_final
2017-10-12 10:26:30	ga_ls7e_ard_3-0-0_101073_2017-10-12_final
2017-10-12 10:26:54	ga_ls7e_ard_3-0-0_101074_2017-10-12_final
2017-10-12 10:27:18	ga_ls7e_ard_3-1-0_101075_2017-10-12_final
2017-10-12 10:27:42	ga_ls7e_ard_3-0-0_101076_2017-10-12_final
2017-10-12 10:28:06	ga_ls7e_ard_3-0-0_101077_2017-10-12_final
2017-10-12 10:28:30	ga_ls7e_ard_3-0-0_101078_2017-10-12_final
2017-10-12 10:28:54	ga_ls7e_ard_3-0-0_101079_2017-10-12_final
2017-10-12 10:29:18	ga_ls7e_ard_3-0-0_101080_2017-10-12_final
2017-10-12 10:29:42	ga_ls7e_ard_3-0-0_101081_2017-10-12_final
2017-10-12 10:30:06	ga_ls7e_ard_3-0-0_101082_2017-10-12_final
2017-10-13 09:31:41	ga_ls7e_ard_3-0-0_092075_2017-10-13_final
2017-10-13 09:32:05	ga_ls7e_ard_3-0-0_092076_2017-10-13_final
2017-10-13 09:33:17	ga_ls7e_ard_3-0-0_092079_2017-10-13_final
2017-10-13 09:33:41	ga_ls7e_ard_3-0-0_092080_2017-10-13_final
2017-10-13 09:34:05	ga_ls7e_ard_3-0-0_092081_2017-10-13_final
2017-10-13 09:34:29	ga_ls7e_ard_3-0-0_092082_2017-10-13_final
2017-10-13 09:34:53	ga_ls7e_ard_3-1-0_092083_2017-10-13_final
2017-10-13 09:35:17	ga_ls7e_ard_3-0-0_092084_2017-10-13_final
2017-10-13 11:08:34	ga_ls7e_ard_3-0-0_108070_2017-10-13_final
2017-10-13 11:08:58	ga_ls7e_ard_3-1-0_108071_2017-10-13_final
2017-10-13 11:09:22	ga_ls7e_ard_3-0-0_108072_2017-10-13_final
2017-10-13 11:09:46	ga_ls7e_ard_3-0-0_108073_2017-10-13_final
2017-10-13 11:10:34	ga_ls7e_ard_3-1-0_108075_2017-10-13_final
2017-10-13 11:10:58	ga_ls7e_ard_3-0-0_108076_2017-10-13_final
2017-10-13 11:11:22	ga_ls7e_ard_3-0-0_108077_2017-10-13_final
2017-10-13 11:11:46	ga_ls7e_ard_3-0-0_108078_2017-10-13_final
2017-10-13 11:12:10	ga_ls7e_ard_3-0-0_108079_2017-10-13_final
2017-10-13 11:12:34	ga_ls7e_ard_3-0-0_108080_2017-10-13_final
2017-10-13 11:12:58	ga_ls7e_ard_3-0-0_108081_2017-10-13_final
2017-10-13 11:13:22	ga_ls7e_ard_3-0-0_108082_2017-10-13_final
2017-10-13 11:13:46	ga_ls7e_ard_3-0-0_108083_2017-10-13_final
2017-10-13 11:14:10	ga_ls7e_ard_3-0-0_108084_2017-10-13_final
2017-10-14 10:11:45	ga_ls7e_ard_3-0-0_099067_2017-10-14_final
2017-10-14 10:12:09	ga_ls7e_ard_3-0-0_099068_2017-10-14_final
2017-10-14 10:12:33	ga_ls7e_ard_3-0-0_099069_2017-10-14_final
2017-10-14 10:12:57	ga_ls7e_ard_3-0-0_099070_2017-10-14_final
2017-10-14 10:13:21	ga_ls7e_ard_3-0-0_099071_2017-10-14_final
2017-10-14 10:13:45	ga_ls7e_ard_3-0-0_099072_2017-10-14_final
2017-10-14 10:14:09	ga_ls7e_ard_3-0-0_099073_2017-10-14_final
2017-10-14 10:14:33	ga_ls7e_ard_3-0-0_099074_2017-10-14_final
2017-10-14 10:14:57	ga_ls7e_ard_3-0-0_099075_2017-10-14_final
2017-10-14 10:15:21	ga_ls7e_ard_3-0-0_099076_2017-10-14_final
2017-10-14 10:15:45	ga_ls7e_ard_3-0-0_099077_2017-10-14_final
2017-10-14 10:16:09	ga_ls7e_ard_3-0-0_099078_2017-10-14_final
2017-10-14 10:16:33	ga_ls7e_ard_3-0-0_099079_2017-10-14_final
2017-10-14 10:16:57	ga_ls7e_ard_3-0-0_099080_2017-10-14_final
2017-10-14 10:17:21	ga_ls7e_ard_3-0-0_099081_2017-10-14_final
2017-10-14 10:17:45	ga_ls7e_ard_3-0-0_099082_2017-10-14_final
2017-10-14 10:18:09	ga_ls7e_ard_3-0-0_099083_2017-10-14_final
2017-10-14 10:18:32	ga_ls7e_ard_3-0-0_099084_2017-10-14_final
2017-10-14 11:53:26	ga_ls7e_ard_3-0-0_115074_2017-10-14_final
2017-10-14 11:53:50	ga_ls7e_ard_3-0-0_115075_2017-10-14_final
2017-10-14 11:54:14	ga_ls7e_ard_3-0-0_115076_2017-10-14_final
2017-10-14 11:54:38	ga_ls7e_ard_3-1-0_115077_2017-10-14_final
2017-10-14 11:55:02	ga_ls7e_ard_3-0-0_115078_2017-10-14_final
2017-10-14 11:55:26	ga_ls7e_ard_3-0-0_115079_2017-10-14_final
2017-10-15 09:21:43	ga_ls7e_ard_3-0-0_090081_2017-10-14_final
2017-10-15 09:22:07	ga_ls7e_ard_3-1-0_090082_2017-10-14_final
2017-10-15 09:22:31	ga_ls7e_ard_3-0-0_090083_2017-10-14_final
2017-10-15 09:22:55	ga_ls7e_ard_3-0-0_090084_2017-10-14_final
2017-10-15 09:23:19	ga_ls7e_ard_3-1-0_090085_2017-10-14_final
2017-10-15 09:23:43	ga_ls7e_ard_3-0-0_090086_2017-10-14_final
2017-10-15 09:24:31	ga_ls7e_ard_3-0-0_090088_2017-10-14_final
2017-10-15 09:24:55	ga_ls7e_ard_3-0-0_090089_2017-10-14_final
2017-10-15 09:25:19	ga_ls7e_ard_3-0-0_090090_2017-10-14_final
2017-10-15 10:55:25	ga_ls7e_ard_3-0-0_106068_2017-10-15_final
2017-10-15 10:55:49	ga_ls7e_ard_3-0-0_106069_2017-10-15_final
2017-10-15 10:56:13	ga_ls7e_ard_3-0-0_106070_2017-10-15_final
2017-10-15 10:56:37	ga_ls7e_ard_3-0-0_106071_2017-10-15_final
2017-10-15 10:57:01	ga_ls7e_ard_3-1-0_106072_2017-10-15_final
2017-10-15 10:57:25	ga_ls7e_ard_3-0-0_106073_2017-10-15_final
2017-10-15 10:57:49	ga_ls7e_ard_3-0-0_106074_2017-10-15_final
2017-10-15 10:58:13	ga_ls7e_ard_3-1-0_106075_2017-10-15_final
2017-10-15 10:58:37	ga_ls7e_ard_3-0-0_106076_2017-10-15_final
2017-10-15 10:59:01	ga_ls7e_ard_3-0-0_106077_2017-10-15_final
2017-10-15 10:59:25	ga_ls7e_ard_3-0-0_106078_2017-10-15_final
2017-10-15 10:59:49	ga_ls7e_ard_3-0-0_106079_2017-10-15_final
2017-10-15 11:00:12	ga_ls7e_ard_3-0-0_106080_2017-10-15_final
2017-10-15 11:00:36	ga_ls7e_ard_3-0-0_106081_2017-10-15_final
2017-10-15 11:01:00	ga_ls7e_ard_3-0-0_106082_2017-10-15_final
2017-10-15 11:01:24	ga_ls7e_ard_3-0-0_106083_2017-10-15_final
2017-10-16 10:00:36	ga_ls7e_ard_3-0-0_097070_2017-10-16_final
2017-10-16 10:01:00	ga_ls7e_ard_3-0-0_097071_2017-10-16_final
2017-10-16 10:01:24	ga_ls7e_ard_3-0-0_097072_2017-10-16_final
2017-10-16 10:01:48	ga_ls7e_ard_3-0-0_097073_2017-10-16_final
2017-10-18 09:47:03	ga_ls7e_ard_3-0-0_095067_2017-10-18_final
2017-10-18 09:50:38	ga_ls7e_ard_3-0-0_095076_2017-10-18_final
2017-10-18 09:51:02	ga_ls7e_ard_3-0-0_095077_2017-10-18_final
2017-10-18 09:51:26	ga_ls7e_ard_3-0-0_095078_2017-10-18_final
2017-10-18 09:52:38	ga_ls7e_ard_3-0-0_095081_2017-10-18_final
2017-10-18 09:53:02	ga_ls7e_ard_3-0-0_095082_2017-10-18_final
2017-10-18 09:53:26	ga_ls7e_ard_3-0-0_095083_2017-10-18_final
2017-10-18 09:53:50	ga_ls7e_ard_3-0-0_095084_2017-10-18_final
2017-10-18 09:54:14	ga_ls7e_ard_3-0-0_095085_2017-10-18_final
2017-10-18 09:54:38	ga_ls7e_ard_3-0-0_095086_2017-10-18_final
2017-10-18 09:55:02	ga_ls7e_ard_3-0-0_095087_2017-10-18_final
2017-10-20 09:37:29	ga_ls7e_ard_3-0-0_093074_2017-10-20_final
2017-10-20 09:38:41	ga_ls7e_ard_3-0-0_093077_2017-10-20_final

Return to ga_ls7e_ard_3 across October 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

October

All days