Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libra...

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Published inISPRS journal of photogrammetry and remote sensing Vol. 87; no. 100; pp. 205 - 215
Main Authors Belgiu, Mariana, Drǎguţ, Lucian, Strobl, Josef
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.01.2014
Elsevier
Subjects
Accuracy
Animal, plant and microbial ecology
Applied geophysics
Availability
Biological and medical sciences
Classifications
Comparison
Earth sciences
Earth, ocean, space
Exact sciences and technology
Experiment
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Image analysis
Image classification
Imagery
Internal geophysics
Land Cover
Libraries
OBIA
Operators
Tasks
Teledetection and vegetation maps
Urban
Urban
Accuracy
Comparison
Experiment
Land Cover
Image
OBIA
Availability
experimental studies
Human
Modification
libraries
accuracy
urban areas
classification
variability
image analysis
interpretation
imagery
Plant cover
land cover
high resolution
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Abstract The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.
AbstractList The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.
Author Strobl, Josef
Drǎguţ, Lucian
Belgiu, Mariana
Author_xml – sequence: 1
  givenname: Mariana
  orcidid: 0000-0002-2147-1894
  surname: Belgiu
  fullname: Belgiu, Mariana
  email: mariana.belgiu2@sbg.ac.at
  organization: Department of Geoinformatics (Z_GIS), Salzburg University, Schillerstr. 30, 5020 Salzburg, Austria
– sequence: 2
  givenname: Lucian
  surname: Drǎguţ
  fullname: Drǎguţ, Lucian
  email: lucian.dragut@cbg.uvt.ro
  organization: West University of Timisoara, Department of Geography, Vasile Parvan Avenue, 300223 Timisoara, Romania
– sequence: 3
  givenname: Josef
  surname: Strobl
  fullname: Strobl, Josef
  email: josef.strobl@sbg.ac.at
  organization: Department of Geoinformatics (Z_GIS), Salzburg University, Schillerstr. 30, 5020 Salzburg, Austria
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Issue 100
Keywords Urban
Accuracy
Comparison
Experiment
Land Cover
Image
OBIA
Availability
experimental studies
Human
Modification
libraries
accuracy
urban areas
classification
variability
image analysis
interpretation
imagery
Plant cover
land cover
high resolution
Language English
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Snippet The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and...
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SubjectTerms Accuracy
Animal, plant and microbial ecology
Applied geophysics
Availability
Biological and medical sciences
Classifications
Comparison
Earth sciences
Earth, ocean, space
Exact sciences and technology
Experiment
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Image analysis
Image classification
Imagery
Internal geophysics
Land Cover
Libraries
OBIA
Operators
Tasks
Teledetection and vegetation maps
Urban
Title Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery
URI https://dx.doi.org/10.1016/j.isprsjprs.2013.11.007
https://www.ncbi.nlm.nih.gov/pubmed/24623959
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