NDLI: Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation

Content Provider	IEEE Xplore Digital Library
Author	Tuia, D. Verrelst, J. Alonso, L. Perez-Cruz, F. Camps-Valls, G.
Copyright Year	2004
Abstract	This letter proposes a multioutput support vector regression (M-SVR) method for the simultaneous estimation of different biophysical parameters from remote sensing images. General retrieval problems require multioutput (and potentially nonlinear) regression methods. M-SVR extends the single-output SVR to multiple outputs maintaining the advantages of a sparse and compact solution by using an ε-insensitive cost function. The proposed M-SVR is evaluated in the estimation of chlorophyll content, leaf area index and fractional vegetation cover from a hyperspectral compact high-resolution imaging spectrometer images. The achieved improvement with respect to the single-output regression approach suggests that M-SVR can be considered a convenient alternative for nonparametric biophysical parameter estimation and model inversion.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	804
Ending Page	808
Page Count	5
File Size	467445
File Format	PDF
ISSN	1545598X
Volume Number	8
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Biological system modeling Estimation Support vector machines Parameter estimation Biomedical imaging Vegetation mapping support vector regression (SVR) Biophysical parameter estimation model inversion regression
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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