problem areas
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mj-msc.tex
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mj-msc.tex
@ -48,7 +48,7 @@
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\newcommand{\DP}{Douglas \& Peucker}
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\newcommand{\DP}{Douglas \& Peucker}
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\newcommand{\VW}{Visvalingam--Whyatt}
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\newcommand{\VW}{Visvalingam--Whyatt}
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\newcommand{\WM}{Wang--M{\"u}ller}
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\newcommand{\WM}{Wang--M{\"u}ller}
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% {\WM} algoritmo realizacija kartografinei upių generalizacijai vykdyti (PostGIS programinės įrangos pagrindu)
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% {\WM} algoritmo realizacija kartografinei upių generalizacijai
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\newcommand{\MYTITLE}{{\WM} algorithm realization for cartographic line generalization}
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\newcommand{\MYTITLE}{{\WM} algorithm realization for cartographic line generalization}
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\newcommand{\MYAUTHOR}{Motiejus Jakštys}
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\newcommand{\MYAUTHOR}{Motiejus Jakštys}
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@ -80,12 +80,15 @@
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\begin{abstract}
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\begin{abstract}
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\label{sec:abstract}
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\label{sec:abstract}
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Current open-source line generalization solutions have their roots in
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mathematics and geometry, and are not fit for natural objects like rivers
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Currently available line simplification algorithms are rooted in mathematics
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and coastlines. This paper discusses our implementation of {\WM}'s algorithm
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and geometry, and are not fit bendy natural features like rivers and
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under and open-source license, explains things that we would had
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coastlines. This paper discusses our implementation of {\WM} algorithm,
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appreciated in the original paper and compares our results to different
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with notes that we would have been appreciated before starting the
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generalization algorithms.
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re-implementation endeavor. This paper accompanies our implementation of
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{\WM} algorithm and will be helpful to anyone trying to understand the
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original {\WM} paper, or our implementation.
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\end{abstract}
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\end{abstract}
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\newpage
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\newpage
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@ -268,18 +271,34 @@ figure~\onpage{fig:salvis-generalized-chaikin-50k}.
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\label{fig:salvis-overlaid-generalized-chaikin-50k}
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\label{fig:salvis-overlaid-generalized-chaikin-50k}
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\end{figure}
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\end{figure}
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There are a few problems with {\VW} and {\DP} immediately visible in
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The resulting generalized and smoothened example
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figure~\onpage{fig:salvis-generalized-chaikin-50k}:
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(figure~\onpage{fig:salvis-generalized-chaikin-50k}) yields a more
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aesthetically pleasant result, however, it obscures natural river features.
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Given the absence of rocks, the only natural features that influence the river
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direction are topographic:
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\begin{itemize}
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\begin{itemize}
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\item problem 1
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\item problem 2
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\item Relatively straight river (completely straight or with small-angled
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bends over a relatively long distance) implies greater slope, more
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water, and/or faster flow.
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\item Bendy river, on the contrary, implies slower flow, smaller slope,
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and/or less water.
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\end{itemize}
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\end{itemize}
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Therefore, a more robust generalization algorithm is worthwhile for lookout.
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Both {\VW} and {\DP} have a tendency to remove the small bends altogether,
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which is a valuable characterization of the river. Therefore, a more robust
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generalization algorithm is worthwhile for lookout.
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\subsubsection{Modern approaches}
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\subsubsection{Modern approaches}
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% TODO:
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% https://pdfs.semanticscholar.org/e80b/1c64345583eb8f7a6c53834d1d40852595d5.pdf
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% A New Algorithm for Cartographic Simplification of Streams and Lakes Using
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% Deviation Angles and Error Bands
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Due to their simplicity and ubiquity, {\DP} and {\VW} have been established as
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Due to their simplicity and ubiquity, {\DP} and {\VW} have been established as
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go-to algorithms for line generalization. During recent years, alternatives
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go-to algorithms for line generalization. During recent years, alternatives
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have emerged. These modern replacements fall into roughly two categories:
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have emerged. These modern replacements fall into roughly two categories:
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