Title
Accuracy assessment of contextual classification results for vegetation mapping Accuracy assessment of contextual classification results for vegetation mapping
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
article
Publication
Enschede ,
Subject
Economics
Physics
Source (journal)
International journal of applied earth observation and geoinformation / International Institute for Aerial Survey and Earth Sciences. - Enschede
Volume/pages
15(2012) , p. 7-15
ISSN
0303-2434
ISI
000300136500002
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
A new procedure for quantitatively assessing the geometric accuracy of thematic maps, obtained from classifying hyperspectral remote sensing data, is presented. More specifically, the methodology is aimed at the comparison between results from any of the currently popular contextual classification strategies. The proposed procedure characterises the shapes of all objects in a classified image by defining an appropriate reference and a new quality measure. The results from the proposed procedure are represented in an intuitive way, by means of an error matrix, analogous to the confusion matrix used in traditional thematic accuracy representation. A suitable application for the methodology is vegetation mapping, where lots of closely related and spatially connected land cover types are to be distinguished. Consequently, the procedure is tested on a heathland vegetation mapping problem, related to Natura 2000 habitat monitoring. Object-based mapping and Markov Random Field classification results are compared, showing that the selected Markov Random Fields approach is more suitable for the fine-scale problem at hand, which is confirmed by the proposed procedure.
E-info
https://repository.uantwerpen.be/docman/iruaauth/6b8f45/896d576e304.pdf
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