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Forest canopy structure derived from spatial and spectral high resolution remote sensing data


Beusch, Martin; Koetz, Benjamin; Kneubühler, Mathias; Itten, Klaus I (2005). Forest canopy structure derived from spatial and spectral high resolution remote sensing data. In: 4th EARsel workshop on Imaging Spectroscopy, Warsaw, Poland, 27 April 2005 - 30 April 2005, 631-639.

Abstract

Forest canopy structure can be described by a variety of biophysical parameters, for example leaf area index (LAI) and fractional cover (fcover). These parameters are derived currently from remotely sensed data only with limited accuracy. The retrieval of biophysical parameters is often conducted by empirical models based on vegetation indices (VI) exploiting the spectral information but ignoring the spatial dimension contained in remote sensing data. However, texture information provided by high spatial resolution data can be potentially used as additional information related to the forest structure and might improve the models for the retrieval of biophysical parameters. The aim of this research is to evaluate several methods to combine spectral and textural information to derive the best retrieval method of LAI and fcover from spectral and high spatial resolution remote sensing data in a coniferous forest in the Swiss National Park.
Spectral data as well as spatial data contain information, which can be correlated with the field measurements of biophysical forest parameters. The relationship between spectral data and the field measurements proved to be slightly better than between spatial data and field parameter.

Abstract

Forest canopy structure can be described by a variety of biophysical parameters, for example leaf area index (LAI) and fractional cover (fcover). These parameters are derived currently from remotely sensed data only with limited accuracy. The retrieval of biophysical parameters is often conducted by empirical models based on vegetation indices (VI) exploiting the spectral information but ignoring the spatial dimension contained in remote sensing data. However, texture information provided by high spatial resolution data can be potentially used as additional information related to the forest structure and might improve the models for the retrieval of biophysical parameters. The aim of this research is to evaluate several methods to combine spectral and textural information to derive the best retrieval method of LAI and fcover from spectral and high spatial resolution remote sensing data in a coniferous forest in the Swiss National Park.
Spectral data as well as spatial data contain information, which can be correlated with the field measurements of biophysical forest parameters. The relationship between spectral data and the field measurements proved to be slightly better than between spatial data and field parameter.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:30 April 2005
Deposited On:08 Jul 2014 15:47
Last Modified:06 Apr 2017 19:23
Publisher:s.n.
ISBN:83-89502-02-X
Additional Information:Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy (2005)
Free access at:Official URL. An embargo period may apply.
Official URL:http://www.earsel.org/workshops/IS_Warsaw_2005/html/papers.htm

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