Search ga_ls7e_ard_3 across July 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
2017-07-09 09:36:07	ga_ls7e_ard_3-0-0_092086_2017-07-09_final
2017-07-09 09:36:31	ga_ls7e_ard_3-0-0_092087_2017-07-09_final
2017-07-09 09:36:55	ga_ls7e_ard_3-0-0_092088_2017-07-09_final
2017-07-09 09:37:18	ga_ls7e_ard_3-0-0_092089_2017-07-09_final
2017-07-09 11:08:13	ga_ls7e_ard_3-0-0_108069_2017-07-09_final
2017-07-09 11:08:37	ga_ls7e_ard_3-0-0_108070_2017-07-09_final
2017-07-09 11:09:00	ga_ls7e_ard_3-0-0_108071_2017-07-09_final
2017-07-09 11:09:24	ga_ls7e_ard_3-0-0_108072_2017-07-09_final
2017-07-09 11:09:48	ga_ls7e_ard_3-0-0_108073_2017-07-09_final
2017-07-09 11:10:12	ga_ls7e_ard_3-0-0_108074_2017-07-09_final
2017-07-09 11:10:36	ga_ls7e_ard_3-1-0_108075_2017-07-09_final
2017-07-09 11:11:00	ga_ls7e_ard_3-0-0_108076_2017-07-09_final
2017-07-09 11:11:24	ga_ls7e_ard_3-0-0_108077_2017-07-09_final
2017-07-09 11:11:48	ga_ls7e_ard_3-0-0_108078_2017-07-09_final
2017-07-09 11:12:12	ga_ls7e_ard_3-0-0_108079_2017-07-09_final
2017-07-09 11:12:36	ga_ls7e_ard_3-0-0_108080_2017-07-09_final
2017-07-09 11:13:00	ga_ls7e_ard_3-0-0_108081_2017-07-09_final
2017-07-09 11:13:24	ga_ls7e_ard_3-0-0_108082_2017-07-09_final
2017-07-09 11:13:48	ga_ls7e_ard_3-0-0_108083_2017-07-09_final
2017-07-09 11:14:12	ga_ls7e_ard_3-0-0_108084_2017-07-09_final
2017-07-10 10:12:35	ga_ls7e_ard_3-0-0_099069_2017-07-10_final
2017-07-10 10:12:59	ga_ls7e_ard_3-0-0_099070_2017-07-10_final
2017-07-10 10:13:23	ga_ls7e_ard_3-0-0_099071_2017-07-10_final
2017-07-10 10:13:47	ga_ls7e_ard_3-0-0_099072_2017-07-10_final
2017-07-10 10:14:11	ga_ls7e_ard_3-0-0_099073_2017-07-10_final
2017-07-10 10:14:35	ga_ls7e_ard_3-0-0_099074_2017-07-10_final
2017-07-10 10:14:59	ga_ls7e_ard_3-0-0_099075_2017-07-10_final
2017-07-10 10:16:11	ga_ls7e_ard_3-0-0_099078_2017-07-10_final
2017-07-10 10:16:35	ga_ls7e_ard_3-0-0_099079_2017-07-10_final
2017-07-10 10:16:59	ga_ls7e_ard_3-0-0_099080_2017-07-10_final
2017-07-10 10:17:23	ga_ls7e_ard_3-0-0_099081_2017-07-10_final
2017-07-10 10:17:46	ga_ls7e_ard_3-0-0_099082_2017-07-10_final
2017-07-10 10:18:10	ga_ls7e_ard_3-0-0_099083_2017-07-10_final
2017-07-10 10:18:34	ga_ls7e_ard_3-0-0_099084_2017-07-10_final
2017-07-10 11:53:28	ga_ls7e_ard_3-0-0_115074_2017-07-10_final
2017-07-10 11:53:52	ga_ls7e_ard_3-0-0_115075_2017-07-10_final
2017-07-10 11:54:16	ga_ls7e_ard_3-0-0_115076_2017-07-10_final
2017-07-10 11:54:40	ga_ls7e_ard_3-1-0_115077_2017-07-10_final
2017-07-10 11:55:04	ga_ls7e_ard_3-0-0_115078_2017-07-10_final
2017-07-10 11:55:28	ga_ls7e_ard_3-0-0_115079_2017-07-10_final
2017-07-11 09:20:33	ga_ls7e_ard_3-0-0_090078_2017-07-10_final
2017-07-11 09:20:57	ga_ls7e_ard_3-0-0_090079_2017-07-10_final
2017-07-11 09:21:21	ga_ls7e_ard_3-0-0_090080_2017-07-10_final
2017-07-11 09:21:45	ga_ls7e_ard_3-0-0_090081_2017-07-10_final
2017-07-11 09:22:09	ga_ls7e_ard_3-0-0_090082_2017-07-10_final
2017-07-11 09:22:33	ga_ls7e_ard_3-0-0_090083_2017-07-10_final
2017-07-11 09:22:57	ga_ls7e_ard_3-0-0_090084_2017-07-10_final
2017-07-11 09:23:21	ga_ls7e_ard_3-1-0_090085_2017-07-10_final
2017-07-11 09:23:45	ga_ls7e_ard_3-0-0_090086_2017-07-10_final
2017-07-11 09:24:33	ga_ls7e_ard_3-0-0_090088_2017-07-10_final
2017-07-11 09:24:57	ga_ls7e_ard_3-0-0_090089_2017-07-10_final
2017-07-11 09:25:21	ga_ls7e_ard_3-0-0_090090_2017-07-10_final
2017-07-11 10:55:27	ga_ls7e_ard_3-0-0_106068_2017-07-11_final
2017-07-11 10:55:51	ga_ls7e_ard_3-0-0_106069_2017-07-11_final
2017-07-11 10:56:15	ga_ls7e_ard_3-0-0_106070_2017-07-11_final
2017-07-11 10:56:39	ga_ls7e_ard_3-0-0_106071_2017-07-11_final
2017-07-11 10:57:03	ga_ls7e_ard_3-0-0_106072_2017-07-11_final
2017-07-11 10:57:27	ga_ls7e_ard_3-0-0_106073_2017-07-11_final
2017-07-11 10:57:51	ga_ls7e_ard_3-0-0_106074_2017-07-11_final
2017-07-11 10:58:15	ga_ls7e_ard_3-1-0_106075_2017-07-11_final
2017-07-11 10:58:39	ga_ls7e_ard_3-0-0_106076_2017-07-11_final
2017-07-11 10:59:02	ga_ls7e_ard_3-0-0_106077_2017-07-11_final
2017-07-11 10:59:26	ga_ls7e_ard_3-0-0_106078_2017-07-11_final
2017-07-11 11:01:26	ga_ls7e_ard_3-0-0_106083_2017-07-11_final
2017-07-12 10:00:14	ga_ls7e_ard_3-0-0_097069_2017-07-12_final
2017-07-12 10:00:38	ga_ls7e_ard_3-0-0_097070_2017-07-12_final
2017-07-12 10:01:02	ga_ls7e_ard_3-0-0_097071_2017-07-12_final
2017-07-12 10:01:25	ga_ls7e_ard_3-0-0_097072_2017-07-12_final
2017-07-12 10:01:49	ga_ls7e_ard_3-0-0_097073_2017-07-12_final
2017-07-12 10:02:13	ga_ls7e_ard_3-0-0_097074_2017-07-12_final
2017-07-12 10:02:37	ga_ls7e_ard_3-0-0_097075_2017-07-12_final
2017-07-12 10:03:01	ga_ls7e_ard_3-1-0_097076_2017-07-12_final
2017-07-12 10:03:25	ga_ls7e_ard_3-0-0_097077_2017-07-12_final
2017-07-12 10:03:49	ga_ls7e_ard_3-0-0_097078_2017-07-12_final
2017-07-12 10:04:13	ga_ls7e_ard_3-0-0_097079_2017-07-12_final
2017-07-12 10:04:37	ga_ls7e_ard_3-0-0_097080_2017-07-12_final
2017-07-12 10:05:01	ga_ls7e_ard_3-0-0_097081_2017-07-12_final
2017-07-12 10:05:25	ga_ls7e_ard_3-0-0_097082_2017-07-12_final
2017-07-12 10:05:49	ga_ls7e_ard_3-0-0_097083_2017-07-12_final
2017-07-12 10:06:13	ga_ls7e_ard_3-0-0_097084_2017-07-12_final
2017-07-12 10:06:37	ga_ls7e_ard_3-0-0_097085_2017-07-12_final
2017-07-12 11:38:19	ga_ls7e_ard_3-0-0_113067_2017-07-12_final
2017-07-12 11:41:06	ga_ls7e_ard_3-0-0_113074_2017-07-12_final
2017-07-12 11:41:30	ga_ls7e_ard_3-0-0_113075_2017-07-12_final
2017-07-12 11:41:54	ga_ls7e_ard_3-0-0_113076_2017-07-12_final
2017-07-12 11:42:18	ga_ls7e_ard_3-0-0_113077_2017-07-12_final
2017-07-12 11:42:42	ga_ls7e_ard_3-0-0_113078_2017-07-12_final
2017-07-12 11:43:06	ga_ls7e_ard_3-0-0_113079_2017-07-12_final
2017-07-12 11:43:54	ga_ls7e_ard_3-0-0_113081_2017-07-12_final
2017-07-12 11:44:18	ga_ls7e_ard_3-0-0_113082_2017-07-12_final
2017-07-12 11:44:42	ga_ls7e_ard_3-0-0_113083_2017-07-12_final
2017-07-16 09:37:30	ga_ls7e_ard_3-0-0_093074_2017-07-16_final
2017-07-16 09:37:54	ga_ls7e_ard_3-0-0_093075_2017-07-16_final
2017-07-16 09:38:18	ga_ls7e_ard_3-0-0_093076_2017-07-16_final
2017-07-16 09:38:42	ga_ls7e_ard_3-0-0_093077_2017-07-16_final
2017-07-16 09:39:06	ga_ls7e_ard_3-0-0_093078_2017-07-16_final
2017-07-16 09:39:30	ga_ls7e_ard_3-0-0_093079_2017-07-16_final
2017-07-16 09:39:54	ga_ls7e_ard_3-0-0_093080_2017-07-16_final
2017-07-16 09:40:18	ga_ls7e_ard_3-0-0_093081_2017-07-16_final
2017-07-16 09:40:42	ga_ls7e_ard_3-0-0_093082_2017-07-16_final

Return to ga_ls7e_ard_3 across July 2017 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

2017

July

All days