Sharpened mapping of tropical forest biophysical properties from coarse spatial resolution satellite sensor data


Foody, G.M. and Boyd, D.S. (2002) Sharpened mapping of tropical forest biophysical properties from coarse spatial resolution satellite sensor data. Neural Computing and Applications, 11, (1), 62-70.

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Description/Abstract

Forest biophysical properties are typically estimated
and mapped from remotely sensed data through the
application of a vegetation index. This generally
does not make full use of the information content
of the remotely sensed data, using only the data
acquired in a limited number of spectral channels,
and may provide a relatively crude spatial representation
of the biophysical variable of interest. Using
imagery acquired by the NOAA AVHRR, it is shown
that a standard neural network may use all the
spectral channels available in a remotely sensed
data set to derive more accurate estimates of the
biophysical properties of tropical forests in Ghana
than a series of vegetation indices. Additionally, the
spatial representation derived can be refined by
fusion with finer spatial resolution imagery, achieved
with the application of a further neural network.

Item Type: Article
Related URLs:
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
Divisions: University Structure - Pre August 2011 > School of Geography > Remote Sensing and Spatial Analysis
ePrint ID: 14912
Date Deposited: 09 Mar 2005
Last Modified: 27 Mar 2014 18:05
URI: http://eprints.soton.ac.uk/id/eprint/14912

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