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Field sampling from a segmented image
conference contribution
posted on 2023-05-23, 04:18 authored by Debba, P, Stein, A, van der Meer, FD, Carranza, EJM, Arko LucieerArko LucieerThis 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.
History
Publication title
Computational Science and Its Applications (ICCSA) 2008 Proceedings, Part IVolume
5072Editors
O Gervasi, B Murgante, A Lagana, D Taniar, Y Mun, M GavrilovaPagination
756-768ISBN
978-3-540-69838-8Department/School
School of Geography, Planning and Spatial SciencesPublisher
Springer-VerlagPlace of publication
New YorkEvent title
Computational Science and Its Applications (ICCSA)Event Venue
Perugia, ItalyDate of Event (Start Date)
2008-06-30Date of Event (End Date)
2008-07-03Repository Status
- Restricted