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II/Referatas/mj-referatas.tex
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@ -30,7 +30,7 @@
\newcommand{\WM}{Wang--M{\"u}ller}
\title{
Cartografic Generalization of Lines \\
Cartografic Generalization of Lines using free software \\
(example of rivers) \\ \vspace{4mm}
}
@ -78,12 +78,14 @@ Todėl, kad nėra kilpų.
\begin{abstract}
\label{sec:abstract}
Current open-source line generalization solutions have their roots in
mathematics and geometry, thus emit poor cartographic output. Therefore, if one
is using open-source technology to create a small-scale map, downscaled lines
(e.g. rivers) will not be professionally scale-adjusted. This paper explores
line generalization algorithms and suggests one for an avid GIS developer to
implement. Once it is usable from within open-source GIS software (e.g. QGIS or
PostGIS), rivers on these small-scale maps will look professionally downscaled.
mathematics and geometry, thus emit poor cartographic output. Therefore, if
one is using open-source technology to generalize cartographic objects,
their downscaled counterparts will be incorrectly scale-adjusted. This
paper explores the available down-scaling implementations, highlights some
of their deficiencies, and suggests a viable algorithm for an avid GIS
developer. Once the new algorithm becomes usable from within open-source
GIS software (e.g. QGIS or PostGIS), small-scale maps created by free
software will have a chance to be of higher quality.
\end{abstract}
\newpage
@ -94,25 +96,6 @@ PostGIS), rivers on these small-scale maps will look professionally downscaled.
\section{Introduction}
\label{sec:introduction}
Cartographic generalization is one of the key processes of creating small-scale
maps: how can one approximate object features, without losing its main
cartographic properties? The problem is universally challenging across many
geographical entities (\cite{muller1991generalization},
\cite{mcmaster1992generalization}). This paper focuses on line generalization
for natural rivers: which algorithm should be picked when down-scaling a river
map?
We examine readily available open-source algorithms using a concrete
cartographical example, and make a suggestion on which algorithm could be
implemented next.
\section{What's available}
Line generalization algorithms are well studied, but expose deficiencies in
large-scale reduction (\cite{monmonier1986toward}, \cite{mcmaster1993spatial}).
Most of these techniques are based on mathematical shape representation, rather
than cartographic characteristics of the line.
A number of cartographic line generalization algorithms have been researched,
which claim to better process cartographic objects like lines. These fall into
two rough categories:
@ -125,12 +108,24 @@ two rough categories:
\cite{nollenburg2008morphing}.
\end{itemize}
During research for the mentioned papers, code has been written for all of the
algorithms above, however, is not to be found in a usable form.
\cite{wang1998line} is available in a commercial product, but the author of
this paper does not have means to try it.
During research for the mentioned articles, prototype code has been written for
most of the algorithms. However, none of them seem to be available for use
except for the two "classical" ones -- {\DP} and {\VW}.
To sum up, this paper will be comparing the following algorithms:
\cite{wang1998line} is available in a commercial product, which seems the only
algorithm specifically created for cartographic generalization and available
for general use. This poses a significant problem for map creation: without a
good simplification algorithm, every down-scaled map, of which creator did not
acquire a license for the said product will be of sub-par quality. The more
barriers there are for creating maps in open-source software, the less
open-source will fit the needs of the public, leading to even smaller
open-source applicability and community. We believe that availability of
high-quality open-source tools benefits the society as a whole, as opposed to a
single company producing the said tools, therefore we think it's worth
investing the effort into creating open algorithm implementations.
This paper will be reviewing and comparing two widely available algorithms that
are often used for line generalization:
\begin{itemize}
\item \cite{douglas1973algorithms} via
\href{https://postgis.net/docs/ST_Simplify.html}{PostGIS Simplify}.
@ -139,6 +134,10 @@ To sum up, this paper will be comparing the following algorithms:
\href{https://postgis.net/docs/ST_SimplifyVW.html}{PostGIS SimplifyVW}.
\end{itemize}
Review of the available algorithms will be followed by desiderata for a
possible open-source addition. In the end, we will issue a recommendation,
which algorithm can be picked up and implemented by a willing GIS developer.
\section{Visual comparison}
Lakaja and large part of Žeimena (see figure~\ref{fig:zeimena} on
@ -206,7 +205,7 @@ bends on the original map should be retained.
\includegraphics[width=.0625\linewidth]{zeimena-douglas-4000} &
\includegraphics[width=.0625\linewidth]{zeimena-visvalingam-4000} \tabularnewline \hline
\end{tabularx}
\caption{{\DP} and {\VW} side-by-side on Žeimena}
\caption{{\DP} and {\VW} on Žeimena}
\label{tab:comparison-zeimena}
\end{figure}