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Abstract

This paper presents a statistical method for deriving the
optimal prospective field sampling scheme on a remote sensing image to represent different categories in the field. The iterated conditional modes algorithm (ICM) is used for segmentation followed by simulated annealing within each category. Derived field sampling points are more intense in heterogenous segments. This method is applied to airborne hyperspectral data from an agricultural field. The optimized sampling scheme shows superiority to simple random sampling and rectangular grid sampling in estimating common vegetation indices and is thus more representative of the whole study area.

Item Type:	Conference or Workshop Item (Paper)
Authors/Creators:	Debba, P and van der Meer, FD and Carranza, JM and Lucieer, A
Journal or Publication Title:	Computational Science and Its Applications (ICCSA 2008)
ISSN:	0302-9743
DOI / ID Number:	10.1007/978-3-540-69839-5_55
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