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Journal of Applied Remote Sensing

Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?
Author(s): Andreja Švab Lenarčič; Nataša Đurić; Klemen Čotar; Klemen Ritlop; Krištof Oštir
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Paper Abstract

It is a broadly established belief that the segmentation result significantly affects subsequent image classification accuracy. However, the actual correlation between the two has never been evaluated. Such an evaluation would be of considerable importance for any attempts to automate the object-based classification process, as it would reduce the amount of user intervention required to fine-tune the segmentation parameters. We conducted an assessment of segmentation and classification by analyzing 100 different segmentation parameter combinations, 3 classifiers, 5 land cover classes, 20 segmentation evaluation metrics, and 7 classification accuracy measures. The reliability definition of segmentation evaluation metrics as indicators of land cover classification accuracy was based on the linear correlation between the two. All unsupervised metrics that are not based on number of segments have a very strong correlation with all classification measures and are therefore reliable as indicators of land cover classification accuracy. On the other hand, correlation at supervised metrics is dependent on so many factors that it cannot be trusted as a reliable classification quality indicator. Algorithms for land cover classification studied in this paper are widely used; therefore, presented results are applicable to a wider area.

Paper Details

Date Published: 24 October 2016
PDF: 21 pages
J. Appl. Remote Sens. 10(4) 045010 doi: 10.1117/1.JRS.10.045010
Published in: Journal of Applied Remote Sensing Volume 10, Issue 4
Show Author Affiliations
Andreja Švab Lenarčič, Slovenian Ctr. of Excellence for Space Sciences and Technologies (Slovenia)
Nataša Đurić, Slovenian Ctr. of Excellence for Space Sciences and Technologies (Slovenia)
Klemen Čotar, Slovenian Ctr. of Excellence for Space Sciences and Technologies (Slovenia)
Klemen Ritlop, Univ. of Ljubljana (Slovenia)
Krištof Oštir, Univ. of Ljubljana (Slovenia)
Research Ctr. of the Slovenian Academy of the Sciences and Arts (Slovenia)


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