Search ga_ls7e_ard_3 across November 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
2016-11-22 09:14:15	ga_ls7e_ard_3-0-0_089078_2016-11-21_final
2016-11-22 09:14:39	ga_ls7e_ard_3-0-0_089079_2016-11-21_final
2016-11-22 09:15:03	ga_ls7e_ard_3-0-0_089080_2016-11-21_final
2016-11-22 09:15:26	ga_ls7e_ard_3-1-0_089081_2016-11-21_final
2016-11-22 09:15:50	ga_ls7e_ard_3-0-0_089082_2016-11-21_final
2016-11-22 09:16:14	ga_ls7e_ard_3-0-0_089083_2016-11-21_final
2016-11-24 10:36:46	ga_ls7e_ard_3-0-0_103068_2016-11-24_final
2016-11-24 10:37:10	ga_ls7e_ard_3-0-0_103069_2016-11-24_final
2016-11-24 10:37:34	ga_ls7e_ard_3-0-0_103070_2016-11-24_final
2016-11-24 10:37:58	ga_ls7e_ard_3-0-0_103071_2016-11-24_final
2016-11-24 10:39:10	ga_ls7e_ard_3-0-0_103074_2016-11-24_final
2016-11-24 10:39:34	ga_ls7e_ard_3-0-0_103075_2016-11-24_final
2016-11-24 10:39:58	ga_ls7e_ard_3-0-0_103076_2016-11-24_final
2016-11-24 10:40:22	ga_ls7e_ard_3-0-0_103077_2016-11-24_final
2016-11-24 10:40:46	ga_ls7e_ard_3-0-0_103078_2016-11-24_final
2016-11-24 10:41:10	ga_ls7e_ard_3-0-0_103079_2016-11-24_final
2016-11-24 10:41:34	ga_ls7e_ard_3-0-0_103080_2016-11-24_final
2016-11-24 10:41:58	ga_ls7e_ard_3-0-0_103081_2016-11-24_final
2016-11-24 10:42:22	ga_ls7e_ard_3-0-0_103082_2016-11-24_final
2016-11-25 09:40:45	ga_ls7e_ard_3-1-0_094067_2016-11-25_final
2016-11-25 09:43:09	ga_ls7e_ard_3-0-0_094073_2016-11-25_final
2016-11-25 09:43:33	ga_ls7e_ard_3-0-0_094074_2016-11-25_final
2016-11-25 09:43:57	ga_ls7e_ard_3-0-0_094075_2016-11-25_final
2016-11-25 09:44:21	ga_ls7e_ard_3-0-0_094076_2016-11-25_final
2016-11-25 09:44:44	ga_ls7e_ard_3-0-0_094077_2016-11-25_final
2016-11-25 09:45:08	ga_ls7e_ard_3-0-0_094078_2016-11-25_final
2016-11-25 09:45:32	ga_ls7e_ard_3-0-0_094079_2016-11-25_final
2016-11-25 09:45:56	ga_ls7e_ard_3-0-0_094080_2016-11-25_final
2016-11-25 09:46:20	ga_ls7e_ard_3-0-0_094081_2016-11-25_final
2016-11-25 09:46:44	ga_ls7e_ard_3-0-0_094082_2016-11-25_final
2016-11-25 09:47:08	ga_ls7e_ard_3-0-0_094083_2016-11-25_final
2016-11-25 09:47:32	ga_ls7e_ard_3-0-0_094084_2016-11-25_final
2016-11-25 09:47:56	ga_ls7e_ard_3-0-0_094085_2016-11-25_final
2016-11-25 11:19:38	ga_ls7e_ard_3-0-0_110067_2016-11-25_final
2016-11-25 11:20:50	ga_ls7e_ard_3-0-0_110070_2016-11-25_final
2016-11-25 11:21:14	ga_ls7e_ard_3-0-0_110071_2016-11-25_final
2016-11-25 11:21:38	ga_ls7e_ard_3-1-0_110072_2016-11-25_final
2016-11-25 11:22:02	ga_ls7e_ard_3-0-0_110073_2016-11-25_final
2016-11-25 11:22:26	ga_ls7e_ard_3-0-0_110074_2016-11-25_final
2016-11-25 11:22:50	ga_ls7e_ard_3-0-0_110075_2016-11-25_final
2016-11-25 11:23:14	ga_ls7e_ard_3-0-0_110076_2016-11-25_final
2016-11-25 11:23:38	ga_ls7e_ard_3-0-0_110077_2016-11-25_final
2016-11-25 11:24:01	ga_ls7e_ard_3-0-0_110078_2016-11-25_final
2016-11-25 11:24:25	ga_ls7e_ard_3-0-0_110079_2016-11-25_final
2016-11-25 11:24:49	ga_ls7e_ard_3-0-0_110080_2016-11-25_final
2016-11-25 11:25:13	ga_ls7e_ard_3-0-0_110081_2016-11-25_final
2016-11-25 11:25:37	ga_ls7e_ard_3-0-0_110082_2016-11-25_final
2016-11-25 11:26:01	ga_ls7e_ard_3-0-0_110083_2016-11-25_final
2016-11-25 11:26:25	ga_ls7e_ard_3-0-0_110084_2016-11-25_final
2016-11-26 10:25:36	ga_ls7e_ard_3-0-0_101071_2016-11-26_final
2016-11-26 10:26:00	ga_ls7e_ard_3-0-0_101072_2016-11-26_final
2016-11-26 10:26:24	ga_ls7e_ard_3-0-0_101073_2016-11-26_final
2016-11-26 10:26:48	ga_ls7e_ard_3-0-0_101074_2016-11-26_final
2016-11-26 10:27:12	ga_ls7e_ard_3-1-0_101075_2016-11-26_final
2016-11-26 10:27:36	ga_ls7e_ard_3-0-0_101076_2016-11-26_final
2016-11-26 10:28:00	ga_ls7e_ard_3-0-0_101077_2016-11-26_final
2016-11-26 10:28:24	ga_ls7e_ard_3-0-0_101078_2016-11-26_final
2016-11-26 10:28:48	ga_ls7e_ard_3-0-0_101079_2016-11-26_final
2016-11-26 10:29:12	ga_ls7e_ard_3-0-0_101080_2016-11-26_final
2016-11-26 10:29:36	ga_ls7e_ard_3-0-0_101081_2016-11-26_final
2016-11-26 10:30:00	ga_ls7e_ard_3-0-0_101082_2016-11-26_final
2016-11-26 10:30:24	ga_ls7e_ard_3-0-0_101083_2016-11-26_final
2016-11-27 09:31:35	ga_ls7e_ard_3-0-0_092075_2016-11-27_final
2016-11-27 09:32:23	ga_ls7e_ard_3-0-0_092077_2016-11-27_final
2016-11-27 09:32:47	ga_ls7e_ard_3-0-0_092078_2016-11-27_final
2016-11-27 09:33:10	ga_ls7e_ard_3-0-0_092079_2016-11-27_final
2016-11-27 09:33:34	ga_ls7e_ard_3-0-0_092080_2016-11-27_final
2016-11-27 09:33:58	ga_ls7e_ard_3-0-0_092081_2016-11-27_final
2016-11-27 09:34:22	ga_ls7e_ard_3-0-0_092082_2016-11-27_final
2016-11-27 09:34:46	ga_ls7e_ard_3-0-0_092083_2016-11-27_final
2016-11-27 09:35:10	ga_ls7e_ard_3-0-0_092084_2016-11-27_final
2016-11-27 09:35:34	ga_ls7e_ard_3-0-0_092085_2016-11-27_final
2016-11-27 09:35:58	ga_ls7e_ard_3-0-0_092086_2016-11-27_final
2016-11-30 10:00:05	ga_ls7e_ard_3-0-0_097069_2016-11-30_final
2016-11-30 10:00:29	ga_ls7e_ard_3-0-0_097070_2016-11-30_final
2016-11-30 10:00:53	ga_ls7e_ard_3-0-0_097071_2016-11-30_final
2016-11-30 10:01:16	ga_ls7e_ard_3-0-0_097072_2016-11-30_final
2016-11-30 10:01:40	ga_ls7e_ard_3-0-0_097073_2016-11-30_final
2016-11-30 10:02:04	ga_ls7e_ard_3-0-0_097074_2016-11-30_final
2016-11-30 10:02:28	ga_ls7e_ard_3-0-0_097075_2016-11-30_final
2016-11-30 10:02:52	ga_ls7e_ard_3-0-0_097076_2016-11-30_final
2016-11-30 10:03:16	ga_ls7e_ard_3-0-0_097077_2016-11-30_final
2016-11-30 10:03:40	ga_ls7e_ard_3-0-0_097078_2016-11-30_final
2016-11-30 10:04:04	ga_ls7e_ard_3-0-0_097079_2016-11-30_final
2016-11-30 10:04:28	ga_ls7e_ard_3-0-0_097080_2016-11-30_final
2016-11-30 10:04:52	ga_ls7e_ard_3-0-0_097081_2016-11-30_final
2016-11-30 10:05:16	ga_ls7e_ard_3-0-0_097082_2016-11-30_final
2016-11-30 10:05:40	ga_ls7e_ard_3-0-0_097083_2016-11-30_final
2016-11-30 10:06:04	ga_ls7e_ard_3-0-0_097084_2016-11-30_final
2016-11-30 11:38:10	ga_ls7e_ard_3-0-0_113067_2016-11-30_final
2016-11-30 11:40:57	ga_ls7e_ard_3-0-0_113074_2016-11-30_final
2016-11-30 11:41:21	ga_ls7e_ard_3-0-0_113075_2016-11-30_final
2016-11-30 11:41:45	ga_ls7e_ard_3-0-0_113076_2016-11-30_final
2016-11-30 11:42:09	ga_ls7e_ard_3-0-0_113077_2016-11-30_final
2016-11-30 11:42:33	ga_ls7e_ard_3-0-0_113078_2016-11-30_final
2016-11-30 11:42:57	ga_ls7e_ard_3-0-0_113079_2016-11-30_final
2016-11-30 11:43:21	ga_ls7e_ard_3-0-0_113080_2016-11-30_final
2016-11-30 11:43:45	ga_ls7e_ard_3-0-0_113081_2016-11-30_final
2016-11-30 11:44:09	ga_ls7e_ard_3-0-0_113082_2016-11-30_final
2016-11-30 11:44:33	ga_ls7e_ard_3-0-0_113083_2016-11-30_final

Return to ga_ls7e_ard_3 across November 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

November

All days