Moving from pixels to parcels: The use of possibility theory to explore the uncertainty associated object oriented remote sensing

Alexis Comber, Alan Brown, Katie Medcalf, Richard Lucas, Daniel Clewley, Johanna Breyer, Peter Bunting, Steve Keyworth

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

This paper explores the issues relating to uncertainty in the application of object oriented classifications of remote sensing data. Object oriented remote sensing software such as eCognition (now known as Definiens Developer) provides the user with flexibility in the way that data is classified through segmentation routines and user-specified fuzzy rules. However the aggregation of fuzzy data objects such as pixels to higher level parcels for the purpose of policy reporting is not straightforward. This paper explores the uncertainty issues relating to the aggregation from fine detailed (uncertain) objects of one classification system to coarser grain (uncertain) objects of another classification scheme. We show Possibility Theory to be an appropriate formalism for managing the non-additive uncertainty commonly associated with classified remote sensing data. Results are presented for a small area of upland Wales to illustrate the value of the approach
Original languageEnglish
Title of host publicationHeadway in Spatial Data Handling
Subtitle of host publication13th International Symposium on Spatial Data Handling
EditorsAnne Ruas, Christopher Gold
PublisherSpringer Nature
Pages487-500
Number of pages14
ISBN (Print)978-3540685654, 3540685650
DOIs
Publication statusPublished - 2008

Publication series

NameLecture Notes in Geoinformation and Cartography

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