Preliminary Analysis of Quality of Contour Lines Using Smoothing Algorithms.

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Title: Preliminary Analysis of Quality of Contour Lines Using Smoothing Algorithms.
Authors: BORISOV, Mirko1 mborisov@uns.ac.rs, PAL, Andrej2 andrej.pal@ogr.ntf.uni-lj.si, VRTUNSKI, Milan1 milanv@uns.ac.rs, JOVANOVIĆ, Dušan1 dusanbuk@uns.ac.rs, PETROVIĆ, Vladimir M.3 vladimirpetrovic.gis@gmail.com, VULIĆ, Milivoj1 milivoj.vulic@guest.arnes.si
Source: Technical Gazette / Tehnički Vjesnik. 2019, Vol. 26 Issue 5, p1305-1313. 9p.
Subjects: Algorithms, Filters & filtration, Generalization, Cartography
Abstract: In this paper several well-known filtering techniques were compared in the purpose of automatic line generalization. The used methods for line simplification are digital first order low-pass filter, Savitzky-Golay (SG) filter and Whittaker filter. Two versions of the algorithm for line feature generalization were tested, from source scale 1:25 000 towards target scale of 1:100 000 and from source scale 1:25 000 towards scale of 1:50 000. Also, GPS data filtering for the target scale 1:50 000 was tested. The first version of the algorithm considers that there are no control data, and the filtering parameter is dictated by the desired accuracy for the target scale. The second version involves control data in the target scale. This means that the optimal value for the filtering parameter is the value for which the difference between input and control data is the smallest. Analysis showed that the SG filter yielded the best results in general. The proposed filters can be considered as a new solution for automated cartographic line simplification. [ABSTRACT FROM AUTHOR]
Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Preliminary Analysis of Quality of Contour Lines Using Smoothing Algorithms.
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  Data: <searchLink fieldCode="AR" term="%22BORISOV%2C+Mirko%22">BORISOV, Mirko</searchLink><relatesTo>1</relatesTo><i> mborisov@uns.ac.rs</i><br /><searchLink fieldCode="AR" term="%22PAL%2C+Andrej%22">PAL, Andrej</searchLink><relatesTo>2</relatesTo><i> andrej.pal@ogr.ntf.uni-lj.si</i><br /><searchLink fieldCode="AR" term="%22VRTUNSKI%2C+Milan%22">VRTUNSKI, Milan</searchLink><relatesTo>1</relatesTo><i> milanv@uns.ac.rs</i><br /><searchLink fieldCode="AR" term="%22JOVANOVIĆ%2C+Dušan%22">JOVANOVIĆ, Dušan</searchLink><relatesTo>1</relatesTo><i> dusanbuk@uns.ac.rs</i><br /><searchLink fieldCode="AR" term="%22PETROVIĆ%2C+Vladimir+M%2E%22">PETROVIĆ, Vladimir M.</searchLink><relatesTo>3</relatesTo><i> vladimirpetrovic.gis@gmail.com</i><br /><searchLink fieldCode="AR" term="%22VULIĆ%2C+Milivoj%22">VULIĆ, Milivoj</searchLink><relatesTo>1</relatesTo><i> milivoj.vulic@guest.arnes.si</i>
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  Data: <searchLink fieldCode="JN" term="%22Technical+Gazette+%2F+Tehnički+Vjesnik%22">Technical Gazette / Tehnički Vjesnik</searchLink>. 2019, Vol. 26 Issue 5, p1305-1313. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Filters+%26+filtration%22">Filters & filtration</searchLink><br /><searchLink fieldCode="DE" term="%22Generalization%22">Generalization</searchLink><br /><searchLink fieldCode="DE" term="%22Cartography%22">Cartography</searchLink>
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  Data: In this paper several well-known filtering techniques were compared in the purpose of automatic line generalization. The used methods for line simplification are digital first order low-pass filter, Savitzky-Golay (SG) filter and Whittaker filter. Two versions of the algorithm for line feature generalization were tested, from source scale 1:25 000 towards target scale of 1:100 000 and from source scale 1:25 000 towards scale of 1:50 000. Also, GPS data filtering for the target scale 1:50 000 was tested. The first version of the algorithm considers that there are no control data, and the filtering parameter is dictated by the desired accuracy for the target scale. The second version involves control data in the target scale. This means that the optimal value for the filtering parameter is the value for which the difference between input and control data is the smallest. Analysis showed that the SG filter yielded the best results in general. The proposed filters can be considered as a new solution for automated cartographic line simplification. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.17559/TV-20180827150721
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Filters & filtration
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      – SubjectFull: Generalization
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      – SubjectFull: Cartography
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      – TitleFull: Preliminary Analysis of Quality of Contour Lines Using Smoothing Algorithms.
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            NameFull: BORISOV, Mirko
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            NameFull: PAL, Andrej
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            NameFull: VRTUNSKI, Milan
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            NameFull: JOVANOVIĆ, Dušan
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            NameFull: PETROVIĆ, Vladimir M.
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            NameFull: VULIĆ, Milivoj
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            – D: 01
              M: 09
              Text: 2019
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              Y: 2019
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              Value: 26
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