From 48e7af6997026ce555c9a8a9bb627b681e36b392 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Motiejus=20Jak=C5=A1tys?= Date: Mon, 25 May 2020 11:40:16 +0300 Subject: [PATCH] change descriptions --- II/Referatas/bib.bib | 11 ++++++++ II/Referatas/mj-referatas.tex | 47 +++++++++++++++++++++++----------- II/Referatas/zeimena.gpkg | Bin 167936 -> 167936 bytes 3 files changed, 43 insertions(+), 15 deletions(-) diff --git a/II/Referatas/bib.bib b/II/Referatas/bib.bib index 1ed1238..297bd84 100644 --- a/II/Referatas/bib.bib +++ b/II/Referatas/bib.bib @@ -24,6 +24,17 @@ pages={477} } +@article{visvalingam1993line, + title={Line generalisation by repeated elimination of points}, + author={Visvalingam, Maheswari and Whyatt, James D}, + journal={The cartographic journal}, + volume={30}, + number={1}, + pages={46--51}, + year={1993}, + publisher={Taylor \& Francis} +} + @article{muller1991generalization, title={Generalization of spatial databases}, author={Muller, Jean-Claude}, diff --git a/II/Referatas/mj-referatas.tex b/II/Referatas/mj-referatas.tex index a87a69e..5a437fc 100644 --- a/II/Referatas/mj-referatas.tex +++ b/II/Referatas/mj-referatas.tex @@ -22,6 +22,8 @@ } \iffalse +https://bost.ocks.org/mike/simplify/ + small scale: 1:XXXXXX large scale: 1:XXX @@ -67,16 +69,16 @@ how is tolerance bound to scale? 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 large-scale map, downscaled lines +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 large-scale maps will look professionally downscaled. +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 large-scale +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}, @@ -88,9 +90,32 @@ they 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. -In this paper we explore algorithms which are derived from cartographic -knowledge and processes, so their output is as similar as an experienced -cartographer would create, thus most correct and visually appealing. +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: +\begin{itemize} + \item Cartographic knowledge was encoded to an algorithm (bottom-up + approach). One among these are \cite{wang1998line}. + \item Mathematical shape transformation which yields a more + cartographically suitable down-scaling. E.g. \cite{jiang2003line}, + \cite{dyken2009simultaneous}, \cite{mustafa2006dynamic}, + \cite{nollenburg2008morphing}. +\end{itemize} + +During research, code has been written for all of the algorithms above, +however, it is nowhere to be found completely, or in a usable form. There is +one exception: \cite{wang1998line} is available for general use in a commercial +product, but the author of this paper does not have means to try it. + +Therefore, this paper will be comparing algorithms that readily available for +general public: +\begin{itemize} + \item \cite{douglas1973algorithms} via + \href{https://postgis.net/docs/ST_Simplify.html}{PostGIS Simplify}. + + \item \cite{visvalingam1993line} via + \href{https://postgis.net/docs/ST_SimplifyVW.html}{PostGIS SimplifyVW}. +\end{itemize} For comparison reasons, this article will be using Lakaja and large part of Žeimena (see figure~\ref{fig:zeimena} on page~\pageref{fig:zeimena}). This location was @@ -106,13 +131,6 @@ combination of two curly rivers, and author's familiarity with the location. \section{Mathematical and geometrical algorithms} -To understand why geometrical algorithms are not entirely suitable for -downscaling, let's pick some visual examples. Start with -\cite{douglas1973algorithms}, one of the most well-known line simplification -algorithms, which is often used for generalization. Žeimena example is -generalized with different tolerances in figure~\ref{fig:douglas-peucker} on -page~\pageref{fig:douglas-peucker}. - As one can observe in figure~\ref{fig:douglas-300}, the Douglas \& Peucker with 300m tolerance preserves most of the shape, and 1000m (figure~\ref{fig:douglas-1000}) is still recognizeable. @@ -164,11 +182,10 @@ For further investigation: \cite{stanislawski2012automated} studied different types of metric assessments, such as Hausdorff distance, segment length, vector shift, surface displacement, -and tortuosity for the generalization of linear geographic elements. Their +and tortuosity for the generalization of linear geographic elements. This research can provide references to the appropriate settings of the line generalization parameters for the maps at various scales. - \section{Conclusions and Further Work} \label{sec:conclusions_and_further_work} diff --git a/II/Referatas/zeimena.gpkg b/II/Referatas/zeimena.gpkg index 7433894cc3fe2cb6fde957b0f00ba6a6ba41cd3d..8e3e2d113b8807389d8cb6c8491c4e0b2ade9601 100644 GIT binary patch delta 25 gcmZozz}2vTYl1YR_(U0JM)Agk)&$0_2}}$60cZ;dEdT%j delta 25 gcmZozz}2vTYl1YR=tLQ3M$yKE)&$0_2}}$60cX_+DF6Tf