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

Record type: Article

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.

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Citation

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), pp. 62-70.

More information

Published date: 2002

Identifiers

Local EPrints ID: 14912
URI: http://eprints.soton.ac.uk/id/eprint/14912
PURE UUID: d2bb6f12-5c82-40ee-921d-0caf7bd461d8

Catalogue record

Date deposited: 09 Mar 2005
Last modified: 17 Jul 2017 16:52

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Contributors

Author: G.M. Foody
Author: D.S. Boyd

University divisions


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