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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 Lucieer
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.

History

Publication title

Computational Science and Its Applications (ICCSA) 2008 Proceedings, Part I

Volume

5072

Editors

O Gervasi, B Murgante, A Lagana, D Taniar, Y Mun, M Gavrilova

Pagination

756-768

ISBN

978-3-540-69838-8

Department/School

School of Geography, Planning and Spatial Sciences

Publisher

Springer-Verlag

Place of publication

New York

Event title

Computational Science and Its Applications (ICCSA)

Event Venue

Perugia, Italy

Date of Event (Start Date)

2008-06-30

Date of Event (End Date)

2008-07-03

Repository Status

  • Restricted

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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