eCite Digital Repository

Field sampling from a segmented image


Debba, P and Stein, A and van der Meer, FD and Carranza, EJM and Lucieer, A, Field sampling from a segmented image, Computational Science and Its Applications (ICCSA) 2008 Proceedings, Part I, 30 June - 3 July 2008, Perugia, Italy, pp. 756-768. ISBN 978-3-540-69838-8 (2008) [Refereed Conference Paper]


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 Details

Item Type:Refereed Conference Paper
Keywords:Remote sensing; Image segmentation; Simulated annealing; Optimized field sampling
Research Division:Engineering
Research Group:Geomatic engineering
Research Field:Photogrammetry and remote sensing
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Lucieer, A (Professor Arko Lucieer)
ID Code:54606
Year Published:2008
Deposited By:Geography and Environmental Studies
Deposited On:2009-02-26
Last Modified:2014-08-21

Repository Staff Only: item control page